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1 PHYSIOLOGICAL STRESS DURING FAILED SPOTANEOUS BREATHING TRIALS IN PROLONGED MECHANICAL VENTILATION PATIENTS By HARSHAVARDHAN DEOGHA RE A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2010
2 2010 Harshavardhan Deoghare
3 To my dearest family
4 ACKNOWLEDGMENTS I would like to express my sincere gratitude to my major advisor, Dr. Da nny Martin, for his scientific support and his generous assistance with the preparation of this dissertation and other manuscripts, which immensely facilitated me in my doctoral program. Moreover I am very grateful for multiple opportunities he has provide d me with to participate in international research meetings, which markedly broadened my scientific horizon. I sincerely appreciate the ongoing support of my doctoral committee, consisting of Dr. Paul Davenport (Professor & Interim Chairman Respiratory P hysiology Department of Physiological Sciences) Dr. David Fuller (Associate Professor University of Florida Department of Physical Therapy) and Dr Orit Shechtman (Associate Professor at the Department of Occupational Therapy) I will always be grate ful for their wisdom, support and patience. Their dedication and commitment to this project, as well as their generous help in meticulously reviewing manuscripts is immensely appreciated. I am also thankful to my lab colleagues Tseng tien Huang and Barbara Smith for their help with data collection and for the many lively discussions that improved the research. I am especially thankful to the patients who inspired my research. My doctoral studies were supported by the University of Florida Alumni Fellowship (August 2004 July 2008), Research Assistantship (NIH R01 HD042705) August 2008 December 2009) and Student OPS employment (College of Veterinary Medicine, Department of Physiological Sciences) (March 2010 August 2010). I cannot express enough gratitude tow ards my parents Lata and Vasant Deoghare for their love and dedication I acknowledge their sacrifice that made it possible for me to pursue this path and allowed me to be as ambitious as I wanted.
5 Most importantly, I would like to thank my wife Anagha for encouraging me to start this journey which in retrospect turned out to be the most fulfilling experience of my life. Her support, encouragement, quiet patience and unwavering love are undeniably the bedrock of my life. Finally, I also want to acknowledge the little sacrifices my beautiful daughter Kelika has been making every day. I love her and I owe her every bit of the pride I take in my degree today.
6 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 9 LIST OF FIGURES ................................ ................................ ................................ ........ 10 LIST OF ABBREVIATIONS ................................ ................................ ........................... 11 ABSTRACT ................................ ................................ ................................ ................... 12 CHAPTER 1 SPECIFIC AIMS ................................ ................................ ................................ ..... 14 2 REVIEW OF LITERATURE ................................ ................................ .................... 18 Prolonged Mechanical Ventilation and Weaning Failure ................................ ......... 18 Prolonged Mechanical Ventilation Healthcare Implications .............................. 18 Pathophysiology of Mechanical Ventilation Weaning Failure ........................... 20 Respiratory load capacity imbalance ................................ ......................... 20 Hemodynamic imbal ance ................................ ................................ ........... 22 Psychological factors ................................ ................................ ................. 25 Weaning Predictors in Prolonged Mechanical Ventilation Patients .................. 28 Autonomic Nervous System and Maintenance of Homeostasis .............................. 32 Autonomic Nervous System Basic Physiology ................................ ................. 32 Parasympathetic division ................................ ................................ ........... 33 Sympathetic division ................................ ................................ .................. 34 Neurotransmitters ................................ ................................ ...................... 35 Receptors ................................ ................................ ................................ ... 36 Adrenal medulla ................................ ................................ ......................... 37 Autonomic Control of the Heart ................................ ................................ ........ 39 Parasympathetic stimulation ................................ ................................ ...... 42 Sympathetic stimulation ................................ ................................ ............. 43 Reflex control of heart rate ................................ ................................ ......... 44 Heart Rate Variability Analysis ................................ ................................ ................ 47 Measure of Autonomic Tone ................................ ................................ ............ 47 Heart Rate Vari ability Autonomic Nervous System Testing .............................. 48 Heart Rate Variability Frequency Domain Analysis ................................ .......... 49 Summary and Significance ................................ ................................ ..................... 52 3 MATERIALS AND METHODS ................................ ................................ ................ 61 Research Design ................................ ................................ ................................ .... 61 Power Analysis & Sample Size Estimation ................................ ............................. 61
7 Methods and Measurements ................................ ................................ .................. 63 Patients ................................ ................................ ................................ ............ 63 Inclu sion criteria ................................ ................................ ......................... 63 Exclusion criteria ................................ ................................ ........................ 64 Spontaneous Breathing Trials ................................ ................................ .......... 64 Data Collection ................................ ................................ ................................ 65 Heart rate variability ................................ ................................ ................... 65 Breathing variables analysis ................................ ................................ ...... 66 Blood gas analysis ................................ ................................ ..................... 67 Physiological dead space ratio ................................ ................................ ... 67 Plasma catecholamine levels analysis ................................ ....................... 68 Statistical Analysis ................................ ................................ ............................ 70 4 RESULTS ................................ ................................ ................................ ............... 75 Demographic Data ................................ ................................ ................................ .. 75 Arterial Blood Gas Analysis ................................ ................................ .................... 76 Heart Rate Variability Frequency Domain Analysis ................................ ................ 76 Pl asma Levels of Catecholamine ................................ ................................ ............ 76 Breathing Pattern Analysis ................................ ................................ ...................... 76 Physiological Dead Space ................................ ................................ ...................... 77 5 DISCUSSION ................................ ................................ ................................ ......... 84 Principal Findings ................................ ................................ ................................ ... 84 Mechanical Ventilator Weaning HRV Changes ................................ ....................... 84 Mechanical Ventilator weaning Endocrine Stress Response ................................ .. 88 Role of Dead Space in Prolonged Mechanical Ventilation Patient .......................... 92 6 SUCCESSFUL SPONTANEOUS BREATHING TRIALS ................................ ........ 97 Demographic Data ................................ ................................ ................................ .. 97 Heart Rate Variability Fr equency Domain Analysis ................................ ................ 98 Plasma Catecholamine Levels at SBT Failure ................................ ........................ 98 Breathing Pattern Change between Early and Late SBT ................................ ........ 98 Conclusion ................................ ................................ ................................ .............. 98 7 CONCLUSION AND FUTURE DIRECTIONS ................................ ....................... 107 APPENDIX A BASIC ELECTRO PHYSIOLOGY OF HEART ................................ ....................... 109 B BASIC ELECTROCARDIOGRAM ................................ ................................ ........ 115 C THE POINCARE PLOT ................................ ................................ ....................... 117 LIST OF REFERENCES ................................ ................................ ............................. 119
8 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 140
9 LIST OF TABLES Table page 2 1 Respiratory load capacity imbalance factors causing weaning failure ................ 54 2 2 Comparison sympathetic parasympathetic division ................................ ............ 55 2 3 Frequency domain analysis of Heart rate variability ................................ ........... 56 4 1 Demographic Data ................................ ................................ .............................. 78 4 2 Blood Chemistry Values ................................ ................................ ..................... 79 4 3 Vital Signs ................................ ................................ ................................ .......... 80 4 4 Arterial Blood Gas Data ................................ ................................ ...................... 81 4 5 Heart Rate Variability Analysis: Frequency Domain Measures .......................... 82 4 6 Plasma Catecholamine ................................ ................................ ....................... 82 4 7 Breathing Pattern Variables ................................ ................................ ................ 83 6 1 Demographic Data ................................ ................................ ............................ 100 6 2 Blood Chemistry Values ................................ ................................ ................... 101 6 3 Vital Signs ................................ ................................ ................................ ........ 102 6 4 Arterial Blood Gas Data ................................ ................................ .................... 103 6 5 Breathing Pattern Variables ................................ ................................ .............. 104 6 6 Plasma Catecholamine ................................ ................................ ..................... 105 6 7 Heart Rate Variability Analysis: Frequency Domain Measures ........................ 106
10 LIST OF FIGURES Figure page 2 1 Schematic representation cardiopulmonary interactions ................................ .... 57 2 2 A simplified model of heart rate regulation ................................ ......................... 58 2 3 Frequency Domain Analysis ................................ ................................ ............... 59 2 4 Heart Rate Variability Frequency Domain Analysis ................................ ............ 60 3 1 Power analysis and sa mple size estimation (Specific Aim # 1) .......................... 71 3 2 Power analysis & sample size estimation (Specific Aim #2) ............................... 72 3 3 Single breath CO 2 waveform. ................................ ................................ ............. 73 3 4 Calculation of dead space from single breath CO 2 waveform. ............................ 74 A 1 Sinoatrial Node Action Potentials ................................ ................................ ..... 114 B 1 Normal EKG waveform ................................ ................................ ..................... 116
11 LIST OF ABBREVIATION S ICU Intensive care unit MV Mechanical ventilation SBT Spontaneous breathing trial NIP Negative inspiratory pr essure; ANS Autonomic nervous system; HRV heart rate variability; PSD Power spectral density; HFP H igh frequency power; LFP low frequency power; NU normalized unit; HPLC High Performance Liquid Chromatography RR Respiratory rate; RSA Respi ratory sinus arrhythmia; VD ventilator dependant; Vti Inspired tidal volume V E Minute Ventilation
12 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy PHYSIOLOGICAL STRESS DETECTI ON DURING FAILED SPOTANEOUS BREATHING TRIALS IN PROLON GED MECHANICAL VENTILATION PATIENTS By Harshavardhan Deoghare August 2010 Chair: Anatole D. Martin Major: Rehabilitation Science Fail ing a spontaneous breathing trial (SBT) is a stressful experience for patients requiring prolonged mechanical ventilation (PMV). The objective of this study was to quantify the physiological stress during failed SBT in PMV patients. 10 PMV patients, (5021 MV support days) who were undergoing weaning were studied. Heart rate variability (HRV) indices, plasma catecholamines and arterial blood gases (ABG) were measured while the patients received MV support and at the point of SBT failure. Breathing variables were compared at the first and last 5 min of SBT. SBT failure was defined by standard criteria. Average duration of SBT was 67 65 minutes. At SBT failure, normalized high frequency variability decreased from 6712 to 3716 (p < 0.001) while normalized low frequency variability increased from 3312 to 6316 (p < 0.001). Additionally, norepinephrine increased from 837 618 to 1666 954 pg/ml (p < 0.001) and epinephrine increased from 9235 to 174 103 pg/ml (p < 0.01)]. Minute ventilation increased from 8.072.8 to 9.23 L/min (p < 0.05) and peak inspiratory flow increased
13 from 33.17 to 36.78 L/min (p < 0.05)]. ABG values were not different between MV support and at SBT failure. HRV changes at the point of SBT failure suggest a high level of sympathoadrenal stimul ation, which was confirmed by the elevated catecholamines. Thus, SBT failure is associated with high levels of sympathetic stimulation and respiratory drive, but not necessarily ABG alterations. We believe that in PMV patients the high levels of physiologi cal stress might be responsible for making spontaneous breathing unsustainable, leading to the eventual failure in the SBT. HRV can be used in PMV patients as a non
14 CHAPTER 1 SPECIFIC AIMS Diff iculty weaning patients from mechanical ventilation (MV) is a growing clinical and economic problem in the United States health care system (1) The vast majority of patients supported by MV are quickly weaned, but a minority (~ 10%) of these patients experience difficult weaning and require prolonged mechanical ventilation (PMV) support, often for months (2) Furthermore, PMV is associated with increased morbidity and mortality. As a consequence, PMV patients incur substantial health care costs (1) Therefore, the process of weaning is instituted as soon as the precipitating disease process is significantly improved or is resolved (3) One common method for weaning patients from MV is having the patient perform daily spontaneous breathing trials (SBT) of progressive duration until weaning is accomplished (4 ) However, during SBT, the abrupt switch in the intrathoracic pressure from positive (MV) to negative (spontaneous breathing) significantly affects intrathoracic hemodynamics leading to cardiovascular stress (5, 6 ) Additionally the underlying these alterations to maintain homeostasis (5 7) Previous studies report the occurrence of tachycardia, myocardial ischemia, pulmonary edema and gut ischemia during transition from MV to SBT, indicative of cardiovascular compromise (5, 6) Furthermore, weaning associated ECG and thallium cardiac bloo d flow scan related signs of ischemia have been reported in both subjects with known coronary artery disease (8) and in otherwise normal patients (9) Moreover, inspiratory muscle load capacity imbalance has been identified as a crucial contributor to ventilator dependence. P atients who fail weaning trials may
15 experience ins piratory pressure loads that approximate up to 40% of maximal trans diaphragmatic pressure (10) W orkloads of this magnitude are unsustainable in healthy adu lts who undergo breathing or extremity loading tasks (10 12) Furthermore, the role played by psychological factors in the outcome of SBT is not very well understood. A of weaning from MV concluded that the (13) The fear of loss of the life support system may be responsible for the stress response. Psychological stress is difficult to measure objectively in critically ill patients and even more so in mechanically ventilated patients (13) Few studies have evaluated the psychological state of critically ill patients and i ts ef fect on physiological response. The pathophysiology of MV weaning failure is multifactorial (4) Additionally, there is no consensus on which physiological variable to monitor in PMV patients during the SBT to decide whether to continue a SBT for an initially planned duration, prolong it, or curtail it (3) In this case, the heart rate variability (HRV) analysis offers a simple, noninvasive bedside measure to detect the fluctuations in the autonomic control mechanisms that compensate for environmental and physiological changes (14, 15) In a recent study, Frazier et al. (16) compared heart rate variability measures and plasma catecholamine levels during MV support and continuous positive airway pressure (CPAP) trials in patients on MV support for short durations ( 11.7 + 11.3 days) The study showed that two thirds of the patients demonstrated abnormal autonomic nervous system (ANS) function and this dysfunction was more severe in patients who failed the C PAP trial (16) However, a possible limitation to studies comparing HRV in two groups of patients is the confounding influence of concurrent factors like age,
16 gender (17) and diseases such as diabetes mellitus (14, 18) congestive heart failure and vario us neurological diseases which constitute major co morbidities in ICU patients (14, 18) Additionally, medications like beta blockers acting directly or indirectly on the ANS potentially influence HRV (18) Therefore in these studies the difference found could be the result of intrinsic differences between groups, rather than the difference between outcomes (success or failure i n the SBT) within a subject. However, there is no consensus on which physiological variable to monitor in PMV patients during the SBT to decide whether to prolong or curtail a SBT trial. The objective of this research study is to quantify the physiologic al stress during failed SBT in PMV patients using a within subject design. The study was designed to achieve the following specific aims. Specific Aim # 1: To compare the physiological stress level during mechanical ventilation and at the point of failure during spontaneous breathing trial in prolonged mechanically ventilated patients using heart rate variability analysis Hypothesis # 1: We hypothesize that in prolonged mechanically ventilated patients during failed spontaneous breathing trials heart rate variability analysis will indicate higher physiological stress level at the point of failure as compared to mechanical ventilation support. Specific Aim # 2: To compare plasma catecholamine levels during mechanical ventilation and at the point of failure d uring spontaneous breathing trial in prolonged mechanically ventilated patients. Hypothesis # 2: We hypothesize that in prolonged mechanically ventilated patients during failed spontaneous breathing trials plasma catecholamine analysis will indicate
17 higher physiological stress level at the point of failure as compared to mechanical ventilation support. Specific Aim # 3: To compare the breathing pattern variables at the first and last five minutes of the spontaneous breathing trial in prolonged mechanically ventilated patients. Hypothesis # 3: We hypothesize that in prolonged mechanically ventilated patients during failed spontaneous breathing trials breathing pattern variables will be significantly different comparing the start and the end of the spontaneous breathing trial. Rationale: This will be the first study to quantify the physiological stress during spontaneous breathing trials in prolonged mechanically ventilated patient. Using a within subject design this study will also help validate the use of he art rate variability analysis as a non invasive bedside tool to evaluate the physiological stress during weaning trials.
18 CHAPTER 2 REVIEW OF LITERATURE Prolonged Mechanical Ventilation and Weaning Failure Prolonged Mechanical Ventilation Healthcare Imp lications Mechanical ventilation (MV) is clinically used to maintain adequate alveolar ventilation in patients who are unable of maintaining it on their own. The indications for mechanical ventilation, as derived from a study (19) of 1638 patients in eight countries are acute respiratory failure (66 percent of patients), coma (15 percent), acute chronic obstructive pulmonary disease exacerbation ( 13 percent), and neuromuscular disorders (5 percent). The disorders in the first group include acute respiratory distress syndrome, heart failure, pneumonia, sepsis, complications of surgery, and trauma (with each subgroup accounting for about 8 to 11 percent of the overall group). The objectives of mechanical ventilation are primarily to decrease the work of breathing and reverse life threatening hypoxemia or acute progressive respiratory acidosis. (20) As the conditions that warranted placing the patient on the ventilator stabilize and begin to resolve the time comes to consider the discontinuation of mechanical ventilation; a process commonly referred to as weaning (21, 22) At any given time, 30 70% of patients in the intensive care unit (ICU) are receiving mechanical ventilatory support; 70 80% of them are rapidly weaned off this support, often within a few days. (2) However, w eaning is more problematic in the remaining 20 30 % of patients leading to prolong mechanical ventilation (PMV) support. (2) A recent inte rnational consensus conference recommended that PMV should be defined as need for at least 21 consecutive days of MV for at least 6 hours/day (3) Approximately 10% of all critically ill patients and up to 34% of th ose ventilated for more
19 than two days require PMV support (23 25) Importantly, ~ 45% of the time the patient spends on mechanical ventilation is dedicated to the weaning process (2) Annually in the US, approximately 250,000 patients experience difficult weaning and the estimated annual cost of providing care during these PMV support episodes is 16 billion dollars. (1) Early s urvival from acute respiratory failure in the ICU has increased during the past two decades and the number of patients experiencing PMV is growing 5 times as rapidly as the number of hospital admissions (26) Additionally, persons aged 65 and older presently account for over half of all intensive care unit days in the US (27) This age group, whose members also have the highest basel ine risk of respiratory failure approach the age of 65 years (28, 29) However, this increase is accompanied by significantly fewer d ischarges to home, more discharges to nursing homes, with a greater burden of comorbidit ies (24) Thus compared with other ICU patients, those on long term MV consume a disproportionate amount of critical care reso urces, in view of the small fraction of the ICU population that they represent (30 32) D espite receiving such a high level of care fewer than 50% of PMV hospital survivors survive more than one year (23, 33, 34) Furthermore, most PMV patients who survive 1 year report significant deficits in cognitive functioning, physical functioning, energy and sle ep (33) Consequently, the survivors often suffer significant disability in performing basic daily functions, experience reduced quality of life, and possess significant long term care giving needs (23, 33, 35)
20 Pathophysiology of Mechanical Ventilation Weaning Failure The pathophysiology of weaning failure in PMV patients is complex and multifactorial The m ain reasons are respiratory pump failure, hemodynamic ins tability and psychological dependence on the ventilator (4, 36 38) Respiratory l oad c apacity i mbalance The vast majority of patients who fail a spontaneous breathing trial do so because of an imbalance between resp iratory muscle capacity and the load placed on the respiratory system (37, 38) The increase in work of breathing may be due to an increase in elastic or resistive loads, or both. Elastic workload increases when the re is a reduction in compliance of the lungs and/or a reduction in the compliance of the chest wall. Additionally, n umerous studies indicate that MV induced diaphragmatic weakness, due to both atrophy and contractile dysfunction, is an important contributo r to weaning difficulties. Baseline passive respiratory mechanics are unable to reliably differentiate patients who fail a weaning trial from those who pass (39) However, patients with respiratory muscle weakness can exhibit det erioration of pulmonary mechanics during periods of unassisted breathing. A number of investigations reported dynamic hyperinflation during failed SBT The presence of dynamic hyperinflation implies that alveolar pressure remains positive throughout expir ation. At the end of the expiration, this positive pressure is termed auto positive end expiratory pressure (auto PEEP) or intrinsic positive end expiratory pressure (PEEPi) (40) During SBT most notably PEEPi increases, which may occur due to active expiratory muscle contractions and early termination of exhalation (41, 42) Progressive hyperinflation is accompanied by increased airway resistance and decreased pulmonary compliance (12, 43) In the presence of dynamic hyperinflation,
21 tidal breathing oc curs over a less compliant region of the pressure volume curve as end expiratory lung volumes expand. In result, increased pressure is required to generate a tidal inhalation (43) Excessive resistive ventilatory loads may occur due to airway obstruction by edema, bronchoconstriction, or mucus plugging. Increased elastic loading occurs with pulmonary congestion, effusion, ascites (excess fluid in the peri toneal cavity) or skeletal injury. Chronic comorbid diseases such as chronic obstructive pulmonary disease may exacerbate acute resistive and elastic ventilatory loads. Patients who repeatedly fail weaning trials may experience inspiratory pressure loads that approximate up to 40% of maximal trans diaphragmatic pressure (10) W orkloads of this magnitude are unsustainable in healthy adults who undergo breathin g or extremity loading tasks (10 12) Thus, high airway resistance (bronchospasm and excessive airway secretions) (44, 45) and low respiratory system compliance (stiff chest wall, stiff lungs, edematous or atelectatic alveoli) (46, 47) contribute to the increased work of breathing and can make spontaneous breathing unsustainable. Inspiratory weakness has been identified as a crucial con tributor to ventilator dependence (10, 48, 49) Numerous animal models have confirmed that periods of controlled MV between six and 48 hours results in diaphragmatic atrophy and contractile dysfunction referred to as ventilator induced diaphragm dysfunction (VIDD) (50 53) Atrophy of the inactive diaphragm occurs in conjunction with rapidly down regulated protein synthesis (54, 55) followed shortly thereafter by a heightened, sustained state of proteolysis (54, 56, 57) Controlled MV is thought to initiate atrophy signaling cascades in the diaphragm up to eight times faster than in the limb muscles (55, 58) suggesting that this chronically active muscle may be more susceptible to
22 disuse atrophy (59) Recent research by Levine (60) illustrated that passively ventilated adults, free from active pulmonary or infectious diseases, exhibited rapid and profound diaphragmatic atrophy. In this study, organ donors with terminal brain injuries experienced 57% atrophy of type I fibers and 53% atrophy in type II fibers with a median 34 hours of controlled MV, compared to the diaphragms of adults who underwent thoracic surgeries for 4 6 h our s. Additional factors in critical care practice may influence the development of VIDD. Medications such as neuromuscular blocking agents and corticosteroids may impair excitation contraction coupling and accelerate the development of critical illness myopa thy (61) Hyperglycemia, systemic inflammatory response syndrome, and multiple syste m organ failure each place patients at greater risk for intensive care unit ( ICU ) acquired weakness of the diaphragm (62) I nspiratory muscle weakness is associated with delayed weaning (63) Thus, it is likely that several factors (e.g., underlying disease state, infection, drug therapy, etc.) can converge with VIDD to exacerbate diaphragmatic weakness in critically ill patien ts leading to reduced capacity of the respiratory muscles (64) The factors that lead to weaning failure due to respiratory load capacity imbalance are summarized in Table 2 1 (adopted with permission from (65) Hemodynamic i mbalance The heart and lungs interact during each ventilation cycle because of their anatomic position in th e closed thoracic cavity. Ventilation can profoundly alter cardiovascular function via complex, conflicting, and often opposi ng processes (66) Figure 2 1 summarizes the potential cardiopulmonary interactio ns with changes in intrathoracic pressure and lung volume [adopted with permission from (67) ]. Positive
23 pressure ventilation generates positive intrathoracic pressure on inspiration. This is in contrast to spontaneous inspiration, whereby a sub atmospheric intrathoracic pressure is produced by diaphragm contr action and a pressure gradient is formed between the atmosphere and the alveoli, and gas flows into the alveoli along the gradient. The transition from mechanical ventilation to independent spontaneous ventilation induces alterations in intrathoracic pres sure that influence thoracic blood volume and flow (68 71) Abrupt removal of mechanical ventilation and reinstitution of spontaneous ventilation typically increases the venous return. An increase in the venous ret urn may produce right ventricular dilation. Right ventricular dilation will shift the int ra ventricular septum toward the left ventricle, impede left ventricular filling, and decrease subsequent cardiac output (72) In addition, right ventricular dilation may augment right ventricular intra chamber pressure and influence the pressure gradient for coronary blood flow. These responses may be even greater in individuals who exhibit increased breathing work because of the significantly greater change in intrathoracic pressure necessary to produce gas flow into the lungs (73) Thus, a pplication and discontinuation o f mechanical ventilation can alter both myocardial oxygen supply and demand (73) Most published criteria (4, 74, 75) require stable hemodynamic status to initiate the spontaneous breathing trial without further definition or descri ption of specific criteria. In addition, many investigators who have suggested that cardiac dysfunction may prevent successful discontinuation of mechanical ventilation studied patients with known cardiac disease (6 66, 72, 73, 76, 77) However, many critically ill patients may have undetected cardiac dysfunction. The underlying pathophysiological processes inherent
24 abili ty to compensate. Thus, many critically ill patients may be unable to respond to hemodynamic changes produced by ventilator discontinuation making the weaning from mechanical ventilatory support a cardiovascular stress. Cardiovascular instability during di scontinuation of mechanical ventilation was first described more than 30 years ago by Beach et al. (1973) in postoperative cardiac surgery patients (78) Patients who had decreased cardiac output in response to ventilator discontinuation had a concurrent increase in central venous pressure, pulmonary vascular resistance, and systemic vascular resistance. Fifteen years later, Demling et al. (79) found that 32% of surgical and burn ICU patients (n=22) required reintubation because of unsta ble hemodynamic status and pulmonary edema. In a similar study, nearly one fourth of all medical ICU (MICU) patients who did not achieve spontaneous ventilation (n = 18) required reinstitution of mechanical ventilation beca use of congestive heart failure (80) Other investigators have described the need for significantly longer periods of mechanical ventilation in patients wi th left ventricul ar dysfunction (81, 82) In ventilator dependent patients with chronic cardiopulmonary disease (n=15), left ventricular responses to the discontinuation of mechanical ventilation included the development of acute h eart failure concurrently with significant elevations in plasma levels of catecholamines (83) In another study, patients with chronic obstructive pulmonary disease (COPD) without diagnosed coronary artery disease had a significant decrease in left ventricular ejection fraction during T piece breathing (84) Additionally, myocardial dysfunction (85 87) and myocardial ischemia (73, 88) were identified as mechanism causing failure of weaning from mechanical v entilation.
25 Frazier et al. (16) recommended that clinicians must be aware of the potential for silent myocardial ischemia during the stress of liberation from mechanical ventilation. Moreover previous studies rep ort occurrence of pulmonary edema, and gut ischemia, during the transition from MV to SBT, indicative of cardiovascular compromise (5, 6) Furthermore, weaning associated ECG and thallium cardiac blood flow scan r elated signs of ischemia have been reported in both subjects with known coronary artery disease (8) and in otherwise normal patients (9) This indicates that the failure in the weaning process may be secondary to cardiovascular decompensation. Therefore analysis of cardiovascular variables, before and during weaning has been proposed as an important determinant of weaning outcome (36) Autonomic tone influences thoracic hemodynamics because of its effects on heart rate, ventricular filling time, vascular tone, and degree of ventricular contrac tility. Psychological f actors The psychological factors may be among the important non respiratory factors contributing to unsuccessful liberation from mechanical ventilation and leading to ventilator dependence (4, 89 91) Psychological stress is difficult to quantify objectively in critically ill patients and even more so in mechanically ventilated patients. ing was generalized stress (13) The fear of loss of the life support system may be responsible for the stress response. In one observational study (92) the psychological status of 43 con secutive patients who had undergone successful weaning 48 to 96 h ours earlier was recorded using an 32 item questionnaire. Several difficult experiences were recorded, including an inability to communicate, sleep disorders, diffuse anxiety, depression, and fear of abandonment by staff. Although
26 patients received no sedation for 48 h ours many could not recall distinguishing between night and day, and they reported being confused during weaning (92) In another investigation (93) 10 alert patients who were receiving me chanical ventilation, and were judged ready to wean, and who had undergone two to five failed weaning attempts underwent extensive psychometric testing. Several instruments were used, including the multidimensional health locus of control scales form, the Hope scale, the Norbeck social support questionnaire, and a scale measuring fear and other responses to mechanical ventilation (93) Mechanical ventilation was reported as a moderately fearful experience. Patients felt as though their locus of control was external to themselves, reflecting the intense dependence they have on the ICU team and on family members (93) As patients were weaned from mechanical ventilation, the locus of control was internalized. Hope increased as time passed following successful weaning, and hopelessness predominated for patients who continued to require mechanical ventilation (93) Wunderlich et al. (94) measured the patient uncertainty and stress during weaning to determine levels of stre ss and to determine the helpfulness of information from panel and pilot interviewing, eight open ended questions were asked of 19 extubated patients. Qualitative data were analyzed for content and were coded into themes. The study reported that most patients experienced extreme uncertainty and stress during weaning. Patients with underlying pulmonary disease (compared to those without underlying disease) and women had worse experiences than men. Patients were afraid because they did not know what to expect and did not understand what was going on,
27 including whether they would be on the ventilator for the rest of their lives (94) The dominant feeling that patients described was discomfort while weaning from mechanical ventilation (94) The second prominent theme was frustration at the inability to communicate. Patients were very appreciative of information provided by ICU nurses during weaning that promoted patient empowerment. This study highlights the stress and uncertainty of patients undergoing mechanical ventilator weaning (94) Perceptions of dyspnea during mechanical ventilation and weaning were examined in a small number of studies In interviews with patients after extubation Lo gan et al. (95) found that dyspnea was a primary subjective experience during weaning. In studies by Powers et al. and Knebel et al. patients had moderate to high levels of dyspnea during mechanical ventilation (96, 97) Connelly et al. (98) and Bouley et al. (99) found low to moderate levels of dyspnea in patient s receiving mechanical ventilation. No differences in dyspnea were noted between patients who were weaned completely from mechanical ventilation and those who were not (98) Knebel et al. (97) and Bouley et al. (99) examined the occurrence of dyspnea during differen t methods of weaning and found no differences between the methods. Perceptions of fatigue during mechanical ventilation and weaning were examined in 4 studies (95, 98, 100, 101) In an investigation by Logan and J enny, patients who were interviewed after extubation reported a lack of energy, extreme fatigue, and exhaustion during weaning that decreased breathing effectiveness and caused discomfort and frustration. Weaning self efficacy is defined as confidence in o to breathe without ventilatory support (95) However, research that measures perceptions of self efficacy during weaning is scarce. Moody et al. (102) found that
28 sense of mastery related t o weaning from mechanical ventilation was a significant predictor of complete weaning in a sample of long term ventilator dependent patients. Moreover, m any patients suffer significant anxiety during their ICU stay and the process of weaning from mechanica l ventilation and these memories of distress may remain for years (103) The prevalence of anxiety during ICU i s reported to be 30 75%. (92, 104) The anxiety was secondary to dyspnea (105) ; inability to communicate (106) ; and sleep disruption (103) Additionally, Otte et al. (107) found that depressive symptoms were associated with elevated nor epinephrine ( NE ) levels in patients with coronary artery disease Few studies have evaluated the psychological state of critically ill patients and the effect on physiological response. Furthermore, i n a recent study Jubran et al. (108) evaluated the prev a lence of d epressive disorders in PMV patients and found that depressive disorder is diagnosed in 42% of patients who are being weaned from prolon ged ventilation. Additionally, the study showed that patients with depressive disorders were more likely to experience weaning failure and death (108) Despite the qualitative evidence p sychological stress is difficult to quantify in critically ill patients and even more so in mechanically ventilated patients Therefore, heart rate variability measure may be useful in non invasive monitoring of the patients. Weaning Predictors in Prolonged Mechanical Ventilation Patients In an attempt to identify mechanisms of weaning failure and predict i t s likelihood of occurrence, previous studies contrasted the ventilatory characteristics of patients who were successful from those who failed weaning (10, 36, 43, 49, 109 113) Early weaning readiness trials establ ished the use of the spontaneous breathing trial, a short period of unassisted breathing, to test readiness for extubation (81, 114) However, the
29 research highlighted that many causes of early extubation failure do not necessarily predict weaning failure in patients who require prolonged MV and weaning failure cannot be explained by weaning predictors based exclusively upon respiratory mechanics (3) A number of breathing p attern parameters have been reported to be associated with the success or failure of ventilator discontinuation (4, 113, 115, 116) These including vital capacity, tidal volume, respiratory rate, minute ventilation, rapid shallow breathing index (RSBI), calculated by dividing the tidal volume by the respiratory rate and maximal inspiratory pressure (PImax) Moreover, integrated factors also have been employed (4) for example, CROP index [ratio of dynamic compliance maximum negative inspiratory pressure PaO2/PAO2) to respiratory rate ] ). The receiver operating characteristic (ROC) curve is a plot of the sensitivity of a test versus its false positive rate for all possible cu t points. A nalyses of ROC have shown none of these indices are sufficiently sensitive and specific to be useful in predicting the success of ventilation discontinuation, especially in the elderly and/or in the PMV patients (4) Studies examining the breathing pattern, maximal inspiratory pressure, and lung mechanics in patients being weaned from MV have reported inconsistent findings (38, 82) Del Rosario et al. reported that p atients who failed to wean had a higher respiratory rate and RSBI by comparing with successful to wean groups. But, the P i max and dynamic intrinsic positive airway pressure (PEEP i ) measured from the oesophageal pressure were similar in both groups (38) Jubran et al. (82) found that in the early phase of the weaning trial, the failure group developed rapid shallow breathing and a higher value of PEEP i than the success group. Over the weaning course, the
30 respiratory resistance increas ed in the failure group whereas it remains unchanged in the success group. At the end of weaning trials, they found that 13 of 17 failure to wean patients increased in PaCO 2 whereas 4 showed a decrease in PaCO 2 They concluded that the patients who fail to wean developed rapid shallow breathing at the onset of the weaning trial and progressively increased in respiratory resistance and PEEPi, representing an excessive load to the respiratory muscles. This combination of increased mechanical load with rapid s hallow breathing led to inefficient CO 2 clearance, which was the dominant determinant of weaning failure in the overall group. However, the observation that a rapid shallow breathing pattern developed at the onset of weaning trials in the failure group is not a universal phenomenon. Capdevia investigated 17 patients receiving PMV (an averaged MV staying > 20 days) and found that at the onset of weaning trials, high respiratory rate and low tidal volume values were observed in both success and failure groups without significant inter group differences (49) But, they agreed that PEEPi increased in response to the increased respiratory rate in the failure group throughout the weaning period (49) It seems that an excessive inspiratory load imposed on the respiratory muscles is an essential determinant of weaning failure. This excessive load leads to increase in the required breathing energy expenditure with a concomitant breath ing pattern alteration (82) Additionally, it is accepted that a high ne ural drive persist s over the weaning period in failure to wean patients (37) The presence of a high neural drive indicates that the respiratory muscles continue to generate large inspiratory pressure to cope with this excessive load rather than a decrease in respiratory motor output. I f the mechanical
31 loads excessive to the capacity that respiratory muscle can generate, this imbalance will lead to respiratory distress and sooner or later weaning failure will ensue. The importance of the load capacity balance on the weaning outcome of PMV patients has been highlighted in a study by Purro et al. (10) They showed that in the presence of a high neural drive to breathe, the patients with a high load/capacity index (Pdi/Pdimax > 0.4) were unweanable (where Pdi is the pressure required for tidal breath ing and Pdimax is maximal pressure that the respiratory muscles can generate) They also found that a positive linear relationship between the load/capacity index and the effective inspiratory impedance (P 0.1 /tidal volume/inspiratory time and P 0.1 is the va lue of airway pressure exactly 100ms after the beginning of the occluded inspiration) (r = 0.61). Th erefore, they suggested that non invasive methods such as breathing pattern and P 0.1 might help to identify the patients who fail to wean. However, it has b een shown that the value of P 0.1 may be underestimated in the presence of hypercapnia or in the patients with abnormal lung mechanics (117) Additionally, the ratio of Pdi/Pdimax obtained during the patients receiv ing on MV support might underestimate the values that would be obtained during spontaneous respiration since it is reported that a progressive deterioration in respiratory mechanics during SBT in the patients who fail to wean and Pdimax probably decreased by the end of the weaning trials (118) Moreover, in clinical settings, it is non possible to measure the ratio of Pdi/Pdimax on a breath by breath basis during the weaning trials. Thus, an ac cessible and alternate index to represent the relationship of the load capacity balance is needed. In PMV patients the switch from positive pressure mechanical ventilation to negative pressure spontaneous breathing is a stressful experience. This stress c ould be
32 physiological (hemodynamic instability, respiratory load capacity imbalance), psychological or both. Moreover, the underlying pathophysiological processes inherent ing this stressful experience. Furthermore, in PMV patients weaning failure cannot be explained by weaning predictors based exclusively upon respiratory mechanics. Therefore the measurement of physiological stress during SBT would be helpful in monitorin Autonomic Nervous System and Maintenance of Homeostasis Autonomic Nervous System Basic Physiology The autonomic nervous system (ANS) is a part of the peripheral nervous system that functions to regulate the basic visc eral (organ) processes needed for the maintenance of the normal internal environment of the body in an equilibrium state called as homeostasis. (119) The ANS is responsible for extrinsic regulation of cardiac muscle, smooth muscles (e.g. vascular smooth muscles) and all glandular secretions (e.g. hormones). The autonomic nervous system is traditionally d escribed as a motor system that provides control over visceral functions critical for homeostasis. However, it is not strictly an efferent (motor) nervous system. Almost all visceral nerve bundles have sensory fibers intermixed with motor fibers (approxima tely 50% of all axons in the splanchnic nerves and 20% of all axons in the vagus nerves) (119) These sensory fibers carry information from receptors to the central nervous system. This information is, in turn, integrated and relayed by multi neuronal pathways to the brain and/or spinal cord and eventually modulates the autonomic motor outflow. Thus, the ANS provides all the pathways for negative feedback control systems (119)
33 The ANS is composed of two anatomically and functionally distinct divisions, the sympathetic system and the parasympathetic system. Both systems are tonically active. In other words, they provide some degree of nervous input to a given tissue at all times. Therefore, the frequency of discharge of neurons in both systems can either increase or decrease. As a result, tissue activity may be either enhanced or inhibited. This characteristic of the ANS improves its ability to more precisely regulate a tissue's function. Parasympathetic d ivision The preganglionic neurons of the parasympathetic system arise from several nuclei of the brainstem and from the sacral region of the spinal cord (segments S 2 S 4 ). The axons of the preganglionic neurons are quite long compared to those of the sympa thetic system and synapse with postganglionic neurons within terminal ganglia which are close to or embedded within the effector tissues. The axons of the postganglionic neurons, which are very short, then provide input to the cells of that effector tissue Parasympathetic pre ganglia fibers run from the brain stem with the cranial nerves to muscles and glands in the head (cranial nerves III, VII, IX) and to the organs in thorax and abdomen (vagus nerve). The preganglionic neurons that arise from the sacra l region of the spinal cord exit the CNS and join together to form the pelvic nerves. Because the terminal ganglia are located within the innervated tissue, there is typically little divergence in the parasympathetic system compared to the sympathetic syst em. In many organs, there is a 1:1 ratio of preganglionic fibers to postganglionic fibers. Therefore, the effects of the parasympathetic system tend to be more discrete and localized, with only specific tissues being stimulated at any given
34 moment, compare d to the sympathetic system where a more diffuse discharge is possible. Sympathetic d ivision The preganglionic neurons of the sympathetic system arise from the thoracic and lumbar regions of the spinal cord (segments T 1 through L 2 ). Most of these pregangli onic axons are short and synapse with postganglionic neurons within ganglia found in the sympathetic ganglion chains. These ganglion chains, which run parallel immediately along either side of the spinal cord, each consist of 22 ganglia. The preganglionic neuron may exit the spinal cord and synapse with a postganglionic neuron in a ganglion at the same spinal cord level from which it arises. The preganglionic neuron may also travel more rostrally or caudally in the ganglion chain to synapse with postganglio nic neurons in ganglia at other levels. In fact, a single preganglionic neuron may synapse with several postganglionic neurons in many different ganglia. Overall, the ratio of preganglionic fibers to postganglionic fibers is about 1:20. The long postgangli onic neurons originating in the ganglion chain then travel outward and terminate on the effector tissues. This divergence of the preganglionic neuron results in coordinated sympathetic stimulation to tissues throughout the body. The concurrent stimulation of many organs and tissues in the body is referred to as a mass sympathetic discharge. Other preganglionic neurons exit the spinal cord and pass through the ganglion chain without synapsing with a postganglionic neuron. Instead, the axons of these neurons travel more peripherally and synapse with postganglionic neurons in one of the sympathetic collateral ganglia. These ganglia are located about halfway between the CNS and the effector tissue. Finally, the preganglionic neuron may travel to the adrenal
35 medu lla and synapse directly with this glandular tissue. The cells of the adrenal medulla have the same embryonic origin as neural tissue and, in fact, function as modified postganglionic neurons. An important feature of this system, which is quite distinct fr om the parasympathetic system, is that the postganglionic neurons of the sympathetic system travel within each of the 31 pairs of spinal nerves. Interestingly, 8% of the fibers that constitute a spinal nerve are sympathetic fibers. The response of the two types of fibers may be either antagonistic (as in the heart) or almost parallel (in salivary glands). Functionally, both divisions act synergically on the controlled organ, i.e. the desired response is brought by simultaneous stimulation of one division a nd stimulation reduction of the other division, and vice versa. The actions of both divisions of the ANS must be balanced to maintain homeostasis. Table 2 1: summarizes the comparison between sympathetic parasympathetic divisions. Neurotransmitters The two most common neurotransmitters released by neurons of the ANS are acetylcholine and norepinephrine. Neurotransmitters are synthesized in the axon varicosities and stored in vesicles for subsequent release. Nerve fibers that release acetylcholine are referr ed to as cholinergic fibers. These include all preganglionic fibers of the ANS, both sympathetic and parasympathetic systems; all postganglionic fibers of the parasympathetic system; and sympathetic postganglionic fibers innervating sweat glands. Nerve fib ers that release norepinephrine are referred to as adrenergic fibers. Most sympathetic postganglionic fibers release norepinephrine. The cells of the adrenal medulla are considered modified sympathetic postganglionic neurons. Instead of a neurotransmitter, these cells release hormones
36 into the blood. Approximately 20% of the hormonal output of the adrenal medulla is norepinephrine. The remaining 80% is epinephrine. Unlike true postganglionic neurons in the sympathetic system, the adrenal medulla contains an enzyme that methylates norepinephrine to form epinephrine. The synthesis of epinephrine, also known as adrenaline, is enhanced under conditions of stress. These 2 hormones released by the adrenal medulla are collectively referred to as the catecholamines. Receptors The effect caused by any of these neurotransmitters is determined by the receptor distribution in a particular tissue and the biochemical properties of the cells in that tissue, specifically, the second messenger and enzyme systems present with in the cell. The neurotransmitters of the ANS and the circulating catecholamines bind to specific receptors on the cell membranes of the effector tissue. All adrenergic receptors and muscarinic receptors are coupled to G proteins which are also embedded wi thin the plasma membrane. Receptor stimulation causes activation of the G protein and the formation of an intracellular chemical, the second messenger. The function of the intracellular second messenger molecules is to elicit tissue specific biochemical ev ents within the cell which alter the cell's activity. In this way, a given neurotransmitter may stimulate the same type of receptor on 2 different types of tissue and cause 2 different responses due to the presence of different biochemical pathways within each tissue. Acetylcholine binds to 2 types of cholinergic receptors. Nicotinic receptors are found on the cell bodies of all postganglionic neurons, both sympathetic and parasympathetic, in the ganglia of the ANS. Acetylcholine released from the pregangli onic neurons binds to these nicotinic receptors and causes a rapid increase in
37 the cellular permeability to Na + ions and Ca ++ ions. The resulting influx of these 2 cations causes depolarization and excitation of the postganglionic neurons the ANS pathways. Muscarinic receptors are found on the cell membranes of the effector tissues and are linked to G proteins and second messenger systems which carry out the intracellular effects. Acetylcholine released from all parasympathetic postganglionic neurons and s ome sympathetic postganglionic neurons traveling to sweat glands binds to these receptors. Muscarinic receptors may be either inhibitory or excitatory, depending on the tissue upon which they are found. For example, muscarinic receptor stimulation in the m yocardium is inhibitory and decreases heart rate while stimulation of these receptors in the lungs is excitatory, causing contraction of airway smooth muscle and bronchoconstriction. There are 2 classes of adrenergic receptors for norepinephrine and epine phrine, 1 2 1 2 All of these receptors are linked to G proteins and second messenger systems which carry out the intracellular effects. Alpha receptor s are the 1 receptors are more widely distributed on the effector tissues. Alpha one receptor stimulation leads to an increase in intracellular calcium. As a result, these receptors tend to be excitatory. For 1 receptors causes contraction of vascular smooth muscle resulting in vasoconstriction and increased glandular secretion by way of exocytosis. Adrenal m edulla A mass sympathetic discharge, which typically occurs dur or response and during exercise, involves the simultaneous stimulation of organs and
38 tissues throughout the body. Included among these tissues are the adrenal medullae which release epinephrine and norepinephrine into the blood. In l arge part, the indirect effects of these catecholamines are similar to and, therefore, reinforce those of direct sympathetic stimulation However, there are some important differences in the effects of the circulating catecholamines and those of norepineph rine released from sympathetic nerves. The duration of activity of the catecholamines is significantly longer than that of neuronally released norepinephrine. Therefore, the effects on the tissues are more prolonged. This difference has to do with the mech anism of inactivation of these substances. Norepinephrine is immediately removed from the neuro effector synapse by way of reuptake into the postganglionic neuron. This rapid removal limits the duration of the effect of this neurotransmitter. In contrast, there are no enzymes in the blood to degrade the catecholamines. Instead, the catecholamines are inactivated by COMT in the liver. As one might expect, the hepatic clearance of these hormones from the blood would require several passes through the circulat ion. Therefore, the catecholamines are available to cause their effects for a comparatively longer period of time (up to 1 2 minutes as opposed to milliseconds). Because they travel in the blood, organs and tissues throughout the body are exposed to the ca techolamines. Therefore, they are capable of stimulating tissues that are not directly innervated by sympathetic nerve fibers: airway smooth muscle, hepatocytes, and adipose tissue, in particular. As a result, the catecholamines have a much wider breadth o f activity compared to norepinephrine released from sympathetic nerves. The third important feature that distinguishes th e catecholamines from
39 2 receptors. Norepinephrine has a very limited affinity for these receptors. Therefore, circulating epinephrine causes effects that differ from those of direct sy mpathetic innervation including a greater stimulatory effect on the heart and relaxation of smooth muscle (vascular, bronchial, gastrointestinal, and genitourinary). 1 receptors, the predominant adre nergic receptor on the heart. However, the human heart also contains 2 1 receptors are excitatory. Therefore, epinephrine is capable of stimulating a greater number of receptors and of causing a greater stimula tory effect on the myocardium. It is well known that vagal nerve stimulation and acetylcholine infusion can result in significant changes in cardiac electrophysiology, including nonuniform effects on atrial refractory periods (120) pacemaker activity and atrioventricular (AV) conduction, (121) and induction of AF (122) Cervical vagal stimulation shortens the atrial effective refra ctory period primarily in the high right atrium and facilitates induction of AF by a single premature extra stimulus (123) Autonomic Control of the Heart The sinus node has an intrinsic rate of spontaneous depolarization, known as the intrinsic HR ( 10 ) The intrinsic HR is the HR measured in the absence of sympathetic and parasympathetic inputs (achieved by denervation or pharmacologic blockade). In healthy human s ubjects, this is approximately 100 beats/min and is age and gender dependent endurance exercise trained individuals may have a lower intrinsic HR (124) Other non autonomic contributions to changes in HR are hypoxia, circadian rhythm and temperature (125, 126) Thus, sympathetic an d parasympathetic effects on the intrinsic
40 HR predominantly determine the actual HR. The heart is innervated by the sympathetic and the parasympathetic nervous systems; their influence on ion channels is manifested as changes in the heart rate, refractorin ess, and contractility. The ventrolateral medulla (VLM) is a functionally identified region within the medulla oblongata that has been shown to be involved in regulation of cardiovascular activity. Anatomically, the VLM has been divided into rostral (RV LM ) and caudal (CVLM) divisions (127, 128) The RVLM comprises the nucleus reticularis paragigantocellularis, nucleus reticularis gigantocellularis, nucleus reticularis parvocellularis, the C1 area, and the rostral po rtion of the nucleus ambiguus (128) The CVLM comprises the A1 region, the caudal portion of the nucleus reticularis gigantocellularis, nucleus reticularis ventralis, lateral reticular nucleus, and the caudal portion of the nucleus ambiguous (127) Electrical or chemical stimulation of the RVLM neurons elicits a pressor response associated with an increase in heart rate and sympathetic activity, RVLM being referred to (129) In contrast, similar stimulation of the CVLM neurons evokes a decrease in blood pressure, bradycardia, and a reduc tion in sympathetic (127, 128) The HR control is mainly determined by the outflow from the cardiovagal motoneurons that are located in the nucleu s ambiguus and the dorsal vagal nucleus (130, 131) The cardiovagal motoneurons in the nucleus ambiguus are excited by afferent inputs from the peripheral baroreceptors (131) arterial chemoreceptors and unmyelinated cardiac afferents. This excitatory effect is mediated via a direct monosynaptic projection from the nucleus tractus solitarius, which relays ba roreceptor afferent inputs, and a supramedullary pathway that may involve the parabrachial
41 nucleus and the anterior hypothalamus (131) Stimulati on of the anterior hypothalamus inhibits the activity of cardiovagal motoneurons in the nucleus ambiguus via direct short latency inhibition mediated by the gamma aminobutyric acid A receptors, disfacilitation due to inhibition of the neurons of the nucleu s tractus solitarius activated by baroreceptor afferents, and an increase in inspiratory drive (131) Respiration affects the basic discharge of cardiovagal motoneurons and their sensitivity to central and reflex inputs (132) causing hyperpolarization during inspiration. It is the main determinant of respiratory sinus arrhythmia, which is an important clinical index of vagal innervation to the heart (133) Individual neurons of the nucleus ambiguus and the dorsal vagal nucleus innervate either the sinoatrial or the atri oventricular node, but not both. Therefo re, the CNS may selectively influence the sinoatrial or atrioventricular node together or independently. The nucleus tractus solitarius integrates the inputs from peripheral visceral receptors with those from higher control centers like the prefrontal cort ex, the central nucleus of the amygdala, the hypothalamus and the periaqueductal gray matter, and modifies the gain of baroreflexes and other cardiorespiratory responses during exercise and other adaptive conditions (134) Most cardiac branches of the vagal nerve separate in the thorax and innervate several cardiac ganglion cells, using acetylcholine as transmitter (135) The vagal inputs produce mainly fast excitatory postsynaptic potentials via nicot inic receptors and to a lesser extent slow inhibitory potentials via muscarinic receptors (136) Acetylcholine, activating the M 2 subtype of muscarinic receptors, mediates the parasympathetic influence on the heart. The activation of these receptors leads to an increase in potassium conductance and a
42 decrease in cyclic adenosine monophosphate via G protein mediated mechanisms (136) Parasympathetic stimu lation Stimulation of the parasympathetic nerve to the heart, the vagus nerve causes the hormone acetylcholine to be released at the vagal endings. This hormone has two major affects on the heart. First it decreases the rate or rhythm of the sinus node a nd second, it decreases the excitability of the A V junctional fibers between the arterial musculature and the A V node, thus slowing transmission of the cardiac impulse into the ventricles. Moderate stimulation can slow the rate of the heart pumping to as little as one half of the normal rate. Strong vagus stimulation can stop the rhythmical excitation of the sinus node or block transmission of the cardiac impulse through the A V junction. In either case, rhythmical impulses are no longer transmitted into the ventricles. The ventricles usually stop beating for 5 20 seconds, where after the Purkinje fibres develop a rhythm of their own and cause ventricular contraction at a rate of 15 40 beats per minute. This phenomenon is called ventricular escape (137) During rest, the cardio motor centre continuously discharges impulses via the vagus to the heart. The resultant cardio Effective physical training increases vagal tone, and fit athletes have therefore a slower stroke rate but a greater stroke volume than unfit persons (137 139) The acetylcholine released at the vagal nerve ending s binds to muscarine (N2) receptors and greatly increases the permeability of the fiber membranes to potassium, which allows rapid leakage of potassium out of the conductive fibers. This causes an increased negative potential inside the fibers. This effect is called hyper polarization, which makes the tissue much less excitable (137,
43 140, 141) membrane potential of the sinus nodal fibers to a level more negative ( 65 to 75 millivolts), than the normal level of 55 to 60 millivolts. Therefore the drift of the resting membrane potential caused by sodium leakage takes longer to reach the threshold potential for excitation. This greatly slows th e rate of rhythmicity of these nodal fibers. If the vagal stimulation is strong enough, it is possible to stop the rhythmical self excitation of this node. In the A V node, the state of hyper polarization makes it difficult for the minute junctional fibers which can generate only small quantities of current during the action potential, to excite the nodal fibers. Therefore, the safety factor for transmission of the cardiac impulses through the junctional fibers and into the nodal fibers decreases. A modera te decrease simply delays conduction of the impulse, but a decrease in safety factor below unity (so low that the action potential of a fiber cannot cause an action potential in the successive portion of the fiber), blocks conduction (137, 140, 141) Sympathetic stimulation Sympathetic stimulation causes essentially the opposite effects on the heart to those caused by vagal stimulation. First it increases the rate of sinus nodal discharge. Secondly, it increases the rate of conduction as well as the level of excitability in all portions of the heart. Thirdly, it greatly increases the force of contraction of all the cardiac musculature, both arterial and ventricle. In short: sympathetic stimulation increases the streng th of heart contraction up to two fold. In contrast to the parasympathetic fibers, the sympathetic discharge occurs at a low level during rest and increases sharply during stress (physical, mental, and traumatic stress) (137, 138) The permeability of the fiber membrane to sodium and calcium increases upon sympathetic stimulation. In the sinus node, an increase of sodium permeability causes a
44 more positive resting potential and an increased rate or upward drift of th e membrane potential to the threshold level for self excitation. This accelerates the onset of self excitation and therefore the heart rate. In the A V node, increased sodium permeability makes it easier for the action potential to excite each succeeding p ortion of the conducting fiber, thereby decreasing the conduction time from the atria to the ventricles. The increase in permeability to calcium ions is at least partially responsible for the increase in contractile strength of the cardiac muscle under the influence of sympathetic stimulation because calcium ions play a powerful role in exiting the contractile process of the myofibrils (137 139, 142, 143) Reflex control of heart rate The reciprocal association betw een sympathetic and vagal nerve control forms the basis for several cardiac reflexes. Baroreceptor reflex Baroreceptors are pressure sensors comprising of pressure sensitive nerve endings They are located in the elastic segments of arterial walls and re spond to stretching. Baroreceptors detect vessel stretch caused by pressure increases, codifying this information into bursts of action potentials (proportional to pressure changes), which are then sent to the nucleus tractus solitarii (NTS) in the dorsal brainstem, the primary termination site for the cardiovascular afferents. Second order NTS glutamatergic neurons (as well as higher order NTS neurons) excite both parasympathetic preganglionic cell bodies (in the dorsal motor nucleus of the vagus and nucle us ambiguus) and the sympathetic cell groups in the caudal ventrolateral medulla (CVLM; GABAergic inhibitory neurons) that project to and inhibit rostral ventrolateral medulla (RVLM) glutamatergic neurons, thus decreasing sympathetic preganglionic neuronal outflow. During unloading of baroreceptors, increased sympathetic and
45 decreased parasympathetic outflows (regulated by this simple reflex loop integrated within the brainstem), cause a marked bradycardic response, diminished cardiac output, increased veno us capacitance and decreased total peripheral resistance (144, 145) Opposite autonomic effects, i.e. reduced parasympathetic and increased sympathetic drive, are observed during loading of the baroreceptors (145, 146) Oscillations in blood pressure accompany self oscillations in the vasomotor part of the baroreflex loop and are termed Mayer waves. These are mediated by the interaction between the sympathetic and parasympathe tic nervous system. Mayer waves are oscillations of arterial pressure occurring spontaneously in conscious subjects at a frequency lower than respiration ( 0.1 Hz in humans) (137, 138, 147) Mayer waves are tightly coupled with synchronous oscillations of efferent sympathetic nervous activity and are almost invariably enhanced during states of sympathetic activation. For this reason, the amplitude of these oscillations has been proposed as a surrogate measure of symp athetic activity (148 150) Bainbridge reflex High pressure sensitive receptors in the left ventricle and low pressure respon sive elements in the atria and right ventricle consist of stretch induced mechanoreceptor s that respond to pressure or volume changes. These receptors activate myelinated vagal afferent fibers that project to the nucleus solitarius and increase sympathetic nerve activity to the SA node but not to the ventricles, thereby increasing heart rate b ut not contractility (151 153) Distention of these mechanoreceptors also increases renal excretion of free water by inhibition of antidiuretic hormone secretion from the posterior lobe of the pituitary gland (137, 138, 147, 154, 155) It appears highly likely that the Bainbridge reflex may be mediated by
46 distention of these mechanoreceptors. Second, a diffuse receptor network is distributed throughout the cardiac chambers th at projects via unmyelinated vagal afferent neurons to the nucleus tractus solitarius. These receptors behave like the carotid and aortic mechanoreceptors and produce a vasodepressor response consisting of vagus activation concomitant with a simultaneous increase in venous capacitance (151 153) Respiratory centre reflex of the medulla A third reflex occurs during excitation of re into the vasomotor centre, with effects on the sympathetic and parasympathetic nervous systems activity (138) Res piratory sinus arrhythmia (RSA) RSA causes rhythmical variations in the heart at the respiration frequency. The RSA is based on the simultaneous influence of the three above mentioned physiological reflexes on the heart rate. Stimulation of the Bainbridge reflex results in a corresponding stimulation of the baroreceptor reflex aimed at decreasing the heart rate. The combined action of the Bainbridge and baroreceptor reflexes, plus the third reflex that occurs in the respiratory centre of the medulla, has the effect that normal respiration may increase and decrease heart rate by approximately 5% during inspiration and expiration respect ively (137, 138, 147) Heart rate fluctuation is thus a result of various factors, which are often difficult to discern from total behavior, which combine different wave forms. Thus, by studying heart rate variabili ty, we have an opportunity to study the cardiac dynamic behavior influenced by a variety of endogenous and exogenous factors. It is possible to obtain information about the nature of the perturbations to which the cardiovascular system is
47 exposed as well a s the regulatory responses to these perturbations. Figure 2 1 summarizes the influences on the heart rate. Techniques that are available for the study of autonomic nerve activity in humans do not allow any direct exploration of vagal efferent activity. Ear lier research suggests the use of heart rate variability as a surrogate measure of vagal control of t he sinoatrial node (156) With regard to sympathetic nerve activity, several studies have indicated the interesting capabilities of two of the most widely used techniques plasma catecholamine levels and muscle sympathetic neur al activity (157) Heart R ate V ariability A nalysis Measure of Autonomic Tone Heart rate variability (HRV), the variation over time of the period between consecutive heartbeats, is predominantly dependent on the extrinsic regulation of the heart rate. H RV is thought to reflect the heart s ability to adapt to changing circumstances by detecting and quickly responding to unpredictable stimuli. HRV analysis is the ability to assess overall cardiac health and the state of the autonomic nervous system (ANS) r esponsible for regulating cardiac activity. It is known that the vagus nerve is primarily responsible for momentary short term changes in heart rate. It follows that quantification of the beat to beat, high frequency variability of heart rate is an index o f vagal/parasympathetic influence on the heart. Parasympathetic control is related to central vagal outflow to the heart, mean level of vagal effect on the heart (cardiac vagal tone), phasic variation of vagal influence on the heart associated with respira tion, and dynamic vagal responses that influence RR interval, including the parasympathetic baroreflex response. In a normal, healthy heart the rate is restrained by parasympathetic tone. This means that the heart rate can rise
48 by 40 50% when the vagal sup ply is compromised. That is from average 70 to 100 beats per minute (158) A lower frequency heart rate variation is considered to be influenced by both sympathetic and parasympathetic (vagal) nervous system (159) High frequency and low frequency (HF and LF) variation is thus derived from at least partly distinct, although overlapping physiologic mechanisms. Very low and ultra low frequencies have been reported for circadian rhythms, changes in activity, posture, periodic breathing, autonomic outflow, state of arousal, thermoregulatory cyc les and fluctuations in plasma renin activity (159) The mechanisms are, however still somewhat unclear. During this study only high and low frequencies variations were studied. The timing of dynamic and ste ady state effects differ between vagal and sympathetic heart rate control. The parasympathetic nervous system is able to modulate heart rate at all frequencies, while the sympathetic system modulates heart rate at lower frequencies (160 163) Cardiovascular health in general has been associated with higher variability at all frequencies. It is this ever changing rhythm that acts as a buffer against internal and external stresses to maintain homeostasis. The sympathet ic and parasympathetic autonomic branches are tonically active to maintain c division (164 166) The autonomic branches can, depending on the external and internal demands, be controlled reciprocally, independently, or be co activated or co inhibited (167) Heart Rate Variability Autonomic Nervous System Tes ting HRV analysis has been used for the assessment of ANS responses during standard autonomic tests, in which a selective stimulus elicits sympathetic (rest to tilting,
49 cold pressure test, etc.) or parasympathetic (deep breathing, valsalva maneuver) respo nses (168, 169) The pronounced, acute changes after the stimulus are important for grading the autonomic performances and for evaluating neuroregulatory disorders. Early responses to tilt have shown both vagal and sympathetic changes: the almost instantaneous disappearance of the HF component was accompanied by a slower, progressive increase in the LF components (170, 171) The response was dependent on the amplitude of the s timulus: a faster (and larger) sympathetic response was observed for more pronounced tilt angels (172) When the tilt was prolonged, oscillations and non stationarity c haracterized the trend of the LF components, being more e vident in patients with syncope (173) Autonomic unbalance before syncope has als o been assessed using the time varying method (172, 173) documenting a sympathetic withdrawal preceding syncope, which may be either sudden or progressive. This withdrawal has also been confirmed by the analys is of MSNA variability analysis (174) Heart Rate Variability Frequency Domain Analysis The time intervals between consecutive heart beats are customarily measured in the electrocardiogram from the beginning of a QRS co mplex to the beginning of the next QRS complex, so these intervals might be called QQ intervals, but they are conventionally named RR intervals. Although custom dictates using the beginning of the QRS complex as the reference (fiducial) point, it should be noted that this point can be difficult to locate in noisy or low amplitude ECGs, leading to measurement error. Many investigators prefer to measure inter beat intervals using the R wave peak as the reference point, reasoning that this measurement can be m ade with smaller errors. If the measurements are being made for the purpose of studying RR or heart rate
5 0 variability, it is appropriate to make such a choice in order to obtain more accurate measurements of intrinsic variability. Definition: Physiological data collected as a series in time, as with any time series, may be considered a sum of sinusoidal oscillations with distinct frequencies. Conversion from a time domain to frequency domain analysis is made possible with a mathematical transformation develo ped almost two centuries ago (1807) by the French mathematician Jean Babtiste Joseph Fourier (1768 1830). Other transforms exist (e.g. wavelet, Hilbert), but Fourier was first and his transformation is used most commonly. The amplitude of each sine and cos ine wave determines its contribution to the biological signal; frequency domain analysis displays the contributions of each sine wave as a function of its frequency. Facilitated by computerized data harvest and computation, the result of converting data fr om time series to frequency analysis is termed spectral analysis because it provides an evaluation of the power (amplitude) of the contributing frequencies to the underlying signal. Frequency domain analysis yields information about the amount of the over all variance in heart rate resulting from periodic oscillations of heart rate at various frequencies. Because heart rate (or, more accurately, heart period) is measured in milliseconds, variance, which l spectrum of frequencies, is measured in milliseconds squared. Some investigators which is the square root of power and is measured in milliseconds. Fig. 2 3 represents a hypothetical analysis in the frequency domain. In this drastically simplified example, total variability is assumed to be a result of only three frequencies, shown of 0.25 Hz (15
51 frequency of 0.016 Hz (1 cycle per minute). Fig. 1 (top right) shows the signal that results when the underlying frequencies in Fig. 1 (top left) are combined. Finally, Fig. 1 (bottom left) shows the result of a Fourier analysis on the signal in Fig. 1 (top right). Calculation: Frequency domain measures use spectral analysis of a sequence of R R intervals and provide information on how power (variance) is distributed as a function of frequency. Short term recordings (5 min) yield up to 3 peaks in very low (0.003 to 0.04 Hz; VLF), low (0.04 to 0.15 Hz; LF), and high (0.15 to 0.4 Hz; HF) frequency ranges. One reason for the association of each limb of the autonomic nervous system with a different frequency range stems from the fact that the timing o f the HR response to autonomic nerve activity is not identical for each limb. Although a burst of vagal nerve activity has a maximal effect at 0.6 s with a return to baseline within 1 s, a sympathetic burst has no effect for 1 s, a maximal effect at 4 s, a nd a return to baseline within 20 s (175, 176) Both cardiac and peripheral sympathetic responses have a similar time delay (175, 176) The short delay of the vagal cardiac r esponses allows the parasympathetic nervous system to modulate HR at all frequencies between 0 and 0.5 Hz, although the sympathetic system has significant gain only below 0.15 Hz (177) Muscle sympathetic nerve activity has been shown to fluctuate every 10 s (178) a period long enough for vascular smooth muscle and sinus node effectors to respond to relea sed norepinephrine and modulate blood pressure and HR (179) This period corresponds to the LF range observed in HRV. The absolute and normalized LF powers have therefore been used as an index of sympathetic modulation of the heart rate, and the ratio of absolute LF to HF power has been us ed as an i
52 (179, 180) The third main spectral component in the frequency domain is the and the existence of its physiological background might even be questioned. Total (181) The measurement of VLF, LF, and HF is usually made in absolute values, but LF and HF can also be calculated in normalized units, which represent the relative value of each power component in proportion to the total power minus the VLF component (181) The low frequency power (LFP) (0.04 to 0.15 Hz) and high frequency power (HFP) (0.15 to 0.4 Hz) were derived from the sum of area within specific frequency range under the power spectrum density curve and expressed in absolute units (ms2) and normalized units (n.u.) (181) Table 2 1 summarizes the description and normal values of frequency domain measures of heart rate variability. Figure 2 2 [adopted with permission from (18) ] represents the interval tachogram in a normal subject at supine rest (a) and after head up tilt (b). The HRV spectra are shown calculated by parametric autoregressive modeling (c and d) and by a fast Fourier transform based nonparametric algorithm (e and f). For c and d, VLF, LF, and HF central frequency, power in absolute value and power in normalized units (n.u.) are also indicated. In e and f, the peak frequency and the power of VLF, LF, and HF were calculated by integrating the power spectral density (PSD) in the defined frequency bands. Summary and Significance In summary, PMV is associated with a high risk of mortality, morbidity and healthcare cost. Weaning trials are recommended for the patients who are ready to wean. There is growing evidence that transition from mechanical ventilation support to
53 spontaneous breathing causes hemodynamic instability. Moreover, the underlying to compensate making the weaning from mechanical ventilatory support a cardiovascular stress. Furthermore, psychological factors secondary to the apparent loss of the life support may also contribute to the overall physiological stress. Failing a spontaneous breathing trial is an extreme ly stressful experience for the patients and monitoring the stress level during the spontaneous breathing trial can help to stop the trial at an early stage. There are no data examining the physiological stress level during SBT in PMV patients. This will b e the first study to quantify the physiological stress during SBT in PMV patient. Using a within subject design this study will also help validate the use of heart rate variability analysis as a bedside tool to evaluate the physiological stress during wean ing trials.
54 Table 2 1 R espiratory load capacity imbalance factors causing weaning failure Factors that r esult in d ecreased n euromuscular c ompetence Decreased drive Muscle weakness Impaired neuromuscular transmission Drug overdose Electrolyte deran gement Critical illness polyneuropathy Brain stem lesion Malnutrition Neuromuscular blockers Sleep deprivation Myopathy Aminoglycosides Hypothyroidism Hyperinflation Guillain Barr syndrome Starvation/malnutrition Drugs, corticosteroids Mysthenia gravi s Metabolic alkalosis Sepsis Phrenic nerve injury Myotonic dystrophy Spinal cord lesion Factors that result in increase d respiratory load Increased resistive loads Increased chest wall elastic loads Increased lung elastic loads Bronchospasm Pleural e ffusion Hyperinflation (intrinsic positive end expiratory pressure) Airway edema, secretions Pneumothorax Alveolar oedema Upper airway obstruction Flail chest Infection Obstructive sleep apnea Obesity Atelectasis Endotracheal tube kinking Ascites Inter stitial inflammation and/or oedema Secretions encrustation Abdominal distension Ventilatory circuit resistance Adopted with permission from Ala and Esteban Critical Care 2000 4 :72 doi:10.1186/cc660 (65)
55 Table 2 2 Comparison sympathetic parasympathetic division Sympathetic System Parasympathetic Systems Originates in thoracic and lumbar regions of the spinal cord (T1 L2) Originates in brainstem (crani al nerves III, VII, IX, and X) and sacral region of spinal cord (S2 S4) Ganglia located in paravertebral sympathetic ganglion chain or collateral ganglia Terminal ganglia located near or embedded within target tissue Short cholinergic preganglionic fiber s; long adrenergic postganglionic fibers Long cholinergic preganglionic fibers; short cholinergic postganglionic fibers Ratio of preganglionic fibers to postganglionic fibers is 1:20 Ratio of preganglionic fibers to postganglionic fibers is 1:3 Divergenc e coordinates activity of neurons at multiple levels of spinal cord Limited divergence Activity often involves mass discharge of the entire system Activity normally to discrete organs Primary neurotransmitter of postganglionic neurons is norepinephrine P rimary neurotransmitter of postganglionic neurons is acetylcholine or Predominates during quiet resting conditions
56 Table 2 3 Frequency domain analysis of Heart rate variabilit y Variable (Unit) Description Normal Values Total power (ms2/Hz) The total area under the curve in a power spectrum plot. The ms2/Hz unit is considered an absolute unit of measure. 3466 1018 ms2/Hz ULF (ultra low frequency) The peak frequency found in this defined range; obtained from 24 h recordings and may be a graphical representation of direct current (DC). 0.00 0.003 Hz VLF (very low frequency) The peak frequency found in this defined range. The physiological significance is unknown but may corres pond to thermoregulation. VLF power affected by mathematical algorithms of trend (baseline) removal. 0.003 0.04 Hz LF (low frequency) The peak frequency found in this defined range. Both parasympathetic and sympathetic activity influences this component, which may reflect baroreflex mediated modulatory activity. 0.04 0.15 Hz LF power (ms2/Hz) The area under the spectral curve within this frequency range. 1170 416 ms2/Hz LF power (nu) Measure represents relative proportional value of LF power to total power; calculated as (LF power/(total power VLF power)) 100. 54 4 nu HF (high frequency) The peak frequency found in this defined range, which is influenced by both respiratory and parasympathetic activity. 0.15 0.4 Hz HF power (ms2/Hz) The area u nder the spectral curve within this frequency range. 975 203 ms2/Hz HF power (nu) Measure represents relative proportional value of HF power to total power; calculated as (HF power/(total power VLF power)) 100 29 3 nu LF/HF ratio Calculated as LF power/HF power. This controversial measure is considered an assessment of sympathovagal balance. 1.5 2.0
57 Figure 2 1 Schematic representation c ardiopulmonary interactions Adopted from Luecke and Pelosi Clinical review: Positive end expiratory pressur e and cardiac output Critical Care 2005 9 :607 (67)
58 Figure 2 2 A simplified model of heart rate regulation Additional factors influencing considerably the HR are shown within the dashed boxes. [ ad o pted with permission from (182) ].
59 Figure 2 3 Frequency Domain Analysis ( Top left ) Three sinusoidal signals: 1 cycle/min, 6 cycles/min, and 15 cycles/min shown superimposed on the same scale. ( Top right ) Same three signal s combined into one signal. ( Bottom left ) Power spectral analysis of signal shown top right. [ad o pted with permission from (18 3) ].
60 Figure 2 4 Heart Rate Variability Frequency Domain Analysis [ adopted with permission From (18) ]
61 CHAPTER 3 MATERIALS AND METHOD S Rese arch Design This prospective, observational study was conducted in the Surgical and Intermediate Care Unit at Shands Hospital at the University of Florida. The study protocol was approved by the University of Florida Institutional Review Board and informe d consent was obtained from each subject prior to participation in the study. Power Analysis & Sample Size Estimation A power analysis was conducted to determine a sufficient sample size. Because the experimental model was novel, we applied existing data from previous studies. In the specific aim # 1, we stud ied the change in the stress level in PMV patients using heart rate variability parameters using a within subject design. A previous study by Shen et al. (184) compared the heart rate variability measures during assist control mechanical ventilation support (ACMV) to pre ssure support ventilation (PSV) and SBT in patients who failed and patients who were successful. In the patients who failed the weaning trial the low frequency power to the high frequency power ratio was sig nificantly different comparing ACMV to PSV and SB T. The LF/ HF ratio decreased from 1.46 + 0.03 to 1.42 + 0.0 3 comparing ACMV to SBT in patients who failed the weaning trial. The power analysis (185) for this work indicated that a sample size of 10 patients was sufficient to yield statistical significance for LF/ HF ratio with a power (1 error probability) =0.85 [Figure 3 1]. In the specific aim # 2, we compare d the change in the stress level in PMV patients using plasma catecholamine levels using a within subject design. A previous study by Frazier et al. (16) compared the changes in plasma catecholamine during MV support
62 and at 1 hr after initiation of a CPAP trial in patients who failed with successful patients. The change within subjects in plasma catecholamines over time was compared using a paired t tests (baseline, weaning) in failed SBT found a sig nificant increase in the plasma epinephrine level. Those patients who failed the CPAP trial had lower concentrations of catecholamines than the successful group while receiving baseline MV and increased plasma epinephrine from 68 + 43 to CPAP 119 + 100 ( pg/ml) A power analysis (185) of this work indicated that a sample size of 10 patients was suff icient to yield statistical significance for plasma epinephrine with a power (1 error probability) =0.85 [Figure 3 2]. An important difference between this study and the current protocol is that this protocol will compare the catecholamines during MV support and during SBT failure. However, we expect the stress levels to be higher during completely unassisted SBT as compared to CPAP trials. Collectively, the power analysis showed that a sample size of 10 patients should be sufficient to yield statistic al significance. Additionally, we decided to drop any selected patients if any unforeseen morbidities occurs during the study. However, we suspected that a drop out rate would be very low since this is a one time visit observational only study.
63 Metho ds and Measurements Patients Training in Ventilator Dependent Patients (NIH R01 HD042705). The patients were selected from a pool of candidates recovering from acute respiratory f ailure of various etiologies in the surgical intensive care unit and the intermediate respiratory Care Unit at Shands hospital. All patients were tracheostomized during their illness and have categorized to prolong mechanically ventilated patients (at leas t three weaning attempts or require > 21 days of weaning). Informed consent was obtained from the patient or an appropriate surrogate for those patients who met inclusion criteria. Inclusion criteria Patient demonstrating an improvement or resolution of the underlying cause of respiratory failure and adequate gas exchange (e. breathing with a FiO 2 2 O; while receiving assist control or SIMV/pressure support MV. Patient is medically stable and ready to be weaned from the ventilator as determined by the attending physicians. Patient h as a cardiac rhythm originating from the sinus node. Patient demonstrating stable cardiovascular system (eg. HR<140; stable BP) Patient demonstrating stable metabolic status (e.g. acceptable electrolytes) adequate mental status (arousal, Glasgow Coma Sc ale score of >13, and no continuous sedative infusions) sinus rhythm with only rare episodes of ectopy.
64 Exclusion criteria hemodynamically significant valvular or congenital heart disease, severe hypertension, atrial fibrillation or flutter presence o f a cardiac pacemaker history of a myocardial infarction or cerebrovascular accident within the past 6 months adrenergic antagonist drugs (Task Force, 1996) (18) history of a spinal cord injury or any progressive neuromuscular disease, such as ALS, muscular dystrophy, multiple sclerosis that will interfere with neurologic breathing controller. history of diabetes or chronic obstructive pulmonary disease patients requiring continuous analgesic agents that would depress respiratory drive were excluded. Patients with frequent dysrhythmias were excluded from study. Spontaneous Breathing Trials SBT were started between 8:00 am to 9:00 am and lasted until failure or the predetermined duration was reached. During SBT, the patient was disconnected from the ventilator and required to breathe spontaneously while receiving supplemental oxygen to keep SpO2 > 90%. Patients were maintained in a semi recumbe nt position (keeping head end of the bed 30 elevated). During SBT, all patients received routine nursing care, but no rehabilitation services. A failed SBT was defined as inability to sustain spontaneous breathing effort for the predetermined duration o f the trial followed by reinstitution of MV Criteria for terminating a SBT included:
65 oxygen saturation (SPO2) < 85 90% respiratory rate > 35 breaths/min respiratory rate change > 50% heart rate > 140 beats/min, blood pressure change > 20% change in me ntal status (e.g. agitation, anxiety) signs of increased work of breathing (e.g. use of accessory respiratory muscles, paradoxical breathing movements) onset or worsening of discomfort, diaphoresis. Data Collection Demographic data and selected clinical da ta were collected from the medical records. The clinical features included age, gender, weight, BMI, reasons for initiation of ventilator support, duration of MV use prior to SBT and Acute Physiology and Chronic Health Evaluation (APACHE II) Score. The da ta were collected at two points, first when the patient was receiving MV support and last at the point of failure during the SBT. On both points the measured parameters included R R interval tachogram, plasma catecholamines and arterial blood gases. Breath ing parameters were measured on MV and during SBT till failure. Heart rate variability The Heart Rhythm Scanner was connected to the subject through Biocom Active ECG unit through 3 small electrodes. The ECG electrodes were attached to the left arm, right arm, and left leg.
66 All intervals between adjacent QRS complexes resulting from sinus node depolarization were recorded for five minute epochs in a continuous EKG record with the Biocom Heart Rhythm Scanner (Active ECG, Biocom Technologies, Seattle, Washi ngton). T he Heart Rhythm Scanner conforms to standards set forth by the North American Society of Paci ng and Electrophysiology (1996) (186) For each epoch, noise artifa ct and irregular heartbeats were manually edited by visual inspection. This included checking each ECG tracing to make sure that accurate ECG R R intervals are recorded for HRV analysis. Only the beats that had normal morphological characteristics were use d for analysis We excluded complete measurement epochs where events such as extra systolic heartbeats, skipped beats, and other arrhythmias comprised greater than 10% of the total epoch. The power spectral density then was calculated using a Fast Fourier t ransform ( FFT ). Breathing variables analysis A computerized pulmonary monitoring system (CO 2 SMO Plus, Novametrix Medical System Inc. Wallingford, Connecticut, USA), incorporating an adult flow sensor placed between the tracheal canula and the T piece of th e breathing circuit, was used to measure the breathing variables. The monitor was calibrated at the beginning of each testing sequence. Respiratory variables were computed during steady state breathing with a moving average over the last 8 breaths. These variables, included minute ventilation (V E ), respiratory rate (RR), inspired tidal volume (Vt i ), peak inspiratory flow (PIF), inspiration time (Ti), expiration time (Te), the duty cycle [Ti/(Ti+Te)], and mean inspiratory flow rate (Vt i /Ti) were recorded el ectronically with Analysis Plus software (Novametrix Medical System Inc. Wallingford, Connecticut, USA) on a laptop computer.
67 Blood gas analysis An arterial whole blood specimen was obtained from each patient by his/her ICU nurse. The blood samples for blo od gas analysis were collected anaerobically into 5 ml heparinized cooled glass syringes. The ABG syringe was transported on ice to the hospital core laboratory. Samples were immediately processed within a calibrated Chiron 855 ABG analyzer (Chiron Diagnos tics, Medfield, MA, USA) which is calibrated automatically with known standards every 2 hr and with manual controls run twice daily. All blood gas values were corrected to 37C body temperature. The following parameters were determined: pH, partial press ure of carbon dioxide (PaCO 2 mmHg), partial pressure of oxygen (PaO 2 mmHg), actual bicarbonate contents (HCO 3 mmol/l), total carbon dioxide (TCO 2 mmol/l) and oxygen saturation of hemoglobin (SAT, %). Physiological dead space ratio Dead space is define d as the portion of the respiratory system not involved in gas exchange and includes both alveolar and airway dead space. Dead space is often expressed as a ratio of dead space to tidal volume, also known as physiologic dead space ratio (V d /V t ), and is a c linical measure of the efficiency of ventilation. Recent advances in capnography technology have provided a simplified method for calculating V d /V t from single breath carbon dioxide wave forms. The CO 2 SMO Plus is a capnograph, pulse oximeter, and gas flow monitor. An infrared beam splitter continuously detects real time mixed expired carbon dioxide. It is for single patient use with minimal dead space. The CO 2 SMO Plus uses the method originally described by Fowler (187) and validated by Arnold et al. (188) in 1996. The CO 2 SMO Plus provides a standard, expired single breath carbon dioxide (CO 2 ) wave
68 form that can be divided into three phases [Figure 3 3]. Phase I represents CO 2 free gas expired from large airway and endotracheal tube dead space, phase II represents a mixture of gas from both large airway dead space and alveolar dead space, and phase III (or alveolar plateau) represents alveolar ventilation (188) To calculate V d /V t using a single breath CO 2 wave form, the slope of the phase III capnogra ph must first be determined [Figure3 4]. A line is then drawn perpendicular to the x axis so that the intercept between this vertical line and the slope of phase III creates two equal areas, labeled a and b, around the carbon dioxide wave form of phase II. When a concurrently drawn Paco 2 is plotted on the same capnograph, X, large airway dead space (V d aw ), and alveolar dead space (V d alv ) can be identified (189) The sum of these three areas equals the theoretical volume of CO 2 exhaled from a lung with no dead space. Area X depicts the elimination of CO 2 during an exhaled breath, whereas areas V d aw and V d alv depict ventilation that does not eliminate CO 2 The CO 2 SMO Plus computes the V d /V t for each breath during a 1 minute interval using an accompanying arterial Paco 2 and th en averages the V d /V t values to produce the 2 obtained separately from an arterial blood gas, was manually various VD components. Plasma catech olamine levels analysis Approximately, 5 mL blood was drawn through an indwelling antecubital venous catheter into a green top Vacutainer (TM). The whole blood sample was kept on wet ice until centrifuge. Centrifuge was used to separate the plasma within 2 hours of venipuncture. After centrifugation, the plasma was transferred to a plastic, leak proof vial and was immediately refrigerated. Catecholamines were analyzed by high
69 performance liquid chromatography, at Quest Diagnostics Nichols Institute San Juan Capistrano, CA, using the standard procedure (190 192) Three or five milliliter blood samples were added to prechilled tubes containing antioxidant solution (20 l/ml blood). The antioxidant solution consisted o f 225 mM glutathione, 93 M EDTA, 1,660 U/ml heparin, and 250 pmol/ml isoproterenol, as an internal standard, in saline. Blood collection tubes were immediately centrifuged at 4C for 2 min at 15,000 rpm, and the plasma was removed and stored in a covered ice container. Plasma samples were analyzed on the day of the experiment or frozen at 70C for later analysis. Plasma catecholamines were adsorbed on powdered alu mina (25 mg/ml plasma) after addition of 1 M Tris buffer with 2% EDTA (pH 8.6; 400 l/ml plasma). The tubes were agitated for 5 min andcentrifuged; the plasma was aspirated; and the alumina pellet was washed twice with 1 ml of distilled water. Catecholamin es were eluted from the alumina under acid conditions with 150 l 0.1 N HClO 4 by vortexing the tubes for 2 min. One hundred microliters of the supernatant were analyzed on a Hewlett Packard 1100 HPLC system and electrochemical detector (HP 1049A). Catechol amines were eluted isocratically at a flow of 0.75 1.0 ml/min using a 125 4 mm LiCrospher 100 column. Elution is a term used to describe the emergence of chemicals from the column of a chromatograph. As they elute, the chemicals typically flow into a de tector. Predicting and controlling the order of elution is a key aspect of column chromatographic methods. The mobile phase consisted of 20 mM citric acid, 100 mg/l octanesulfonic acid, 0.2 mM EDTA, and 8 10% methanol, and pH was adjusted to 5.0 with NaOH. The electrochemical detector used a glassy carbon electrode at a
70 potential of 0.6 V. Epinephrine and norepinephrine peaks were identified and quantified by comparison of retention times and peak areas to those of known standards. The detection limit is 0. 2 pmol for both catecholamines, which is equivalent to a plasma concentration of ~0.2 nM. Concentrations in each sample were corrected for recovery using the isoproterenol internal standard. Statistical A nalysis All statistical analysis was performed usi ng SPSS statistical software (release 9.0, SPSS Inc., Chicago, IL). Heart rate variability indices [Total power, High Frequency power (normalized units), and Low Frequency power (normalized units)], Plasma catecholamine levels (epinephrine and norepinephri ne), breathing variables, blood gases and respiratory dead space data were analyzed using paired Student's t Test. A p value < 0.05 was considered to be significant.
71 Figure 3 1 Power analysis and sample size estimation (Specific Aim # 1)
72 Figure 3 2 Power analysis & sample size estimation (Specific Aim #2)
73 Figure 3 3 Single breath CO 2 waveform Phase I represents dead space CO 2 expired from large airways. Phase II represents CO 2 mixing from both large airways and alveo lar gas. Phase III represents alveolar ventilation alone. Figure adopted from (189)
74 Figure 3 4 Calculation of dead space from single breath CO 2 waveform. Triangles a and b are created by drawing perpendicular lines. Large airway dead space (V d aw ) is from t he start of expiration to the intersection of the perpendicular lines. Area X is the volume of CO 2 in an exhaled breath. Alveolar dead space is represented by V d alv The physiologic V d /V t = (V d alv + V d aw )/(X + V d alv + V d aw ). Figure adopted from (189)
75 CHAPTER 4 R ESULTS Demographic Data The demographic data for these patients is shown in Table 4 1. Ten patients who had been receiving long term MV support secondary to respiratory failure were recruited. 3 patients were male while 7 patients were female. Patients exh ibited a high severity of illness indicated by an APACHE II score of 19 + 9 indicating that on average patients had a 33% chance of mortality during the ICU stay (193) All the patients experienced respiratory failure following surgical procedures. The average duration of MV before SBT was 50 21 days. Thus all the patients satisfied t he minimum criteria of PMV of > 21 days of MV support. Typical ventilator setting included intermittent mandatory ventilation rates of 2 to 4 breaths / minute, pressure support of 5 to 15 cm H 2 O, continuous positive airway pressure of 3 to 8 cm H 2 O, with a FiO 2 of 0.35 to 0.5. All the patients had a tracheostomy performed (tracheal canula size 8 + 1 mm ID). SBT were started between 8:00 am to 9:00 am and lasted until failure. Among the 10 failed trials 8 were terminated when the patients requested to be returned to be MV, and two trials were terminated by staff due to the development of respiratory distress. Average duration of SBT was 67 65 minutes. Vital signs including heart rate and blood pressure during MV support and at the point of SBT failure are shown in Table 4 2. Although the mean heart rate increased over the duration of the SBT, this increase was not statistically or clinically significant. Additionally, blood pressure did not show a statistically significant difference. Both mean HR and BP w ere within the SBT
76 termination criteria. Furthermore, blood chemistry was measured within 24 hrs before SBT start and the values are reported in Table 4 3. Arterial Blood Gas Analysis Arterial blood gas values during MV support and at the point of SBT fai lure are shown in Table 4 4. At the point of SBT failure the mean PCO 2 was higher while the mean PO 2 and mean PiO 2 /FiO 2 B were lower as compared to MV support. However, these differences were not statistically significant. Heart Rate Variability Frequen cy Domain Analysis HRV frequency domain indices are shown in Table 4 5. At the point of failure HFnu decreased from 6712 to 3716 (p<0.001). Additionally, LFnu increased from 3312 to 6316 (p<0.001). Low HF variability and high LF variability at the poi nt of failure indicates relatively high levels of physiological stress. Plasma Levels of Catecholamine Plasma levels of catecholamines during MV support and at the point of SBT failure are shown in Table 4 7. W e found NE increased significantly from 837 6 18 while the subjects received full MV support to 1666 954 pg/ml (p<0.001) at the time of failure, while EP increased from 9235 to 174 103 pg/ml (p<0.01)]. Elevated catecholamines indicate high levels of stress. Breathing Pattern Analysis Breathing pattern variables during MV support and at the point of SBT failure are shown in Table 4 7. Breathing pattern variables indicated higher respiratory drive at the point of failure during the SBT evident by an increase in V E from 8.072.75 to 9.233.08 L/min (p<0.05) along with the increase in PIF from 33.17.4 to 36.78.36 L/min
77 (p<0.05)]. Other variables respiratory rate, inspired tidal volume, inspiration and expiration time and mean inspiratory flow rate were not different. Physiological D ead S pace Addi tionally, dead space ventilation was compared between MV support and SBT failure. Dead space ventilation was high when the patients were on MV ( 0.56 + 0.09 ) and it increased to 0.62 + 0.12 however the increase was not significant.
78 Table 4 1 Demographic Data Variable (Unit) Value Age (years) 73 + 11 Weight (kg) 66 + 22 BMI 25.7 + 4.7 Gender (male/female) 3:7 Acute Physiology and Chronic Health Evaluation (APACHE II) Score 19 + 6 Mechanical Ventilation (Days) 50 + 21 Spontaneous Breathing Trial Dura tion (mins) 67 + 65 *Data expressed as mean + SD
79 Table 4 2 Blood Chemistry Values Variable Unit Reference Range Result Serum sodium mEq/L 135 148 141.9 + 4.5 Serum potassium mEq/L 3.5 5 4.24 + .38 Serum Chloride mEq/L 98 106 106.30 + 5.91 Bicarbonate total mmol/L 23 30 26.21 + 2.09 Blood urea nitrogen mg/dL 7 18 42.02 + 19.05 Serum creatinine mg/dL 0.6 1.2 1.42 + 1.2 White b lood c ell c ount (*10 3 )mm 3 3.9 10 10.71 + 5.64 Hemoglobin gm/dL 13.2 16.9 9.89 + 0.95 Hematocrit % 38.5 49.0 29.62 + 2.92 Bilirubin mg/dL 0.2 1.0 0.81 + 0.52 Serum pre albumin mg/dl 20 to 40 10.21 + 4.09 Total Protein gm/dL 6.0 8.4 5.45 + 0.4 Serum albumin gm/dL 3.5 5.0 2.81 + 0.5 *Data expressed as mean + SD
80 Table 4 3 Vital Signs On MV SBT Failure t Test (p value) Heart Rate 91 + 12.63 97.33 + 14.95 0.16 Blood Pressure Systolic 126.33 + 15.44 131.33 + 24.40 0.41 Diastolic 58.50 + 11.60 63.30 + 11.76 0.44 Data expressed as mean + SD *MV: Mechanical ventilation, SBT: Spontaneous breathing trial,
81 Ta ble 4 4 Arterial Blood Gas Data Normal Value On MV AT Failure t Test (p value) pH 7.35 7.45 7.4 + 0.05 7.36 + 0.07 0.10 PaCO 2 ( mmHg) 35 45 46.88 + 5.30 50.20 + 12.19 0.24 PaO 2 ( mmHg) 80 95 93.39 + 14.76 81.06 + 22.72 0.33 HCO 3 ( mmol/l) 22 26 28.68 + 1.75 27.78 + 2.72 0.73 SaO 2 ( %) 95 99% 97.25 + 3.15 95.26 + 3.26 0.59 PaO 2 /FiO 2 > 200 241.33 + 53.56 201.71 + 60.30 0.26 Data expressed as mean + SD pH: power of Hydrogen, PaCO 2 : partial pressure of carbon dioxide, PaO 2 : partial pre ssure of oxygen, HCO 3 : actual bicarbonate contents, SaO 2 : oxygen saturation of hemoglobin, PaO 2 /FiO 2 : ratio of arterial oxygen partial pressure to fractional inspired oxygen concentration.
82 Table 4 5 Heart Rate Variability Analysis: Frequency Domain M easures On MV AT Failure t Test (p value) HF ln (ms2) 6.362.3 6.111.2 0.22 LF ln (ms2) 7.10.3 7.87 0.9 0.16 HF (n.u.) 6712 3716 LF (n.u) 3312 6316 LF/HF 0.60.3 2.31.8 Data expressed as mean + SD. HF ln: High Frequen cy variability, LF ln: Low Frequency variability, HF (n.u.): High Frequency variability normalized units, LF (n.u.): Low Frequency variability normalized units. p < 0.05 between MV support and SBT failure. Table 4 6 Plasma Catecholamine On MV AT Failu re t Test (p value) NE (pg/ml) 837 618 1666 954 Ep (pg/ml) 9235 174 103 NE: Norepinephrine, EP: Epinephrine. Data expressed as mean + SD. p < 0.05 between MV support and SBT failure.
83 Table 4 7 Breathing Pattern Variables E arly SBT Late SBT t Test (p value) VE 8.07 + 2.8 9.23 + 3.0 RR 27.18 + 8.9 29.03 + 8.4 0.37 Vti 316 + 84 324 + 102 0.83 PIF 33.11 + 7.4 36.69 + 8.4 PEF 32.34 + 7.7 33.56 + 8.34 0.55 RSBI 90.25 + 30.8 97.44 + 32.2 0.52 Ti 0.83 + 0.19 0. 78 + 0.21 0.36 Te 1.63 + 0.7 1.51 + 0.62 0.37 VCO2 169.9 + 62.1 187.5 + 74.3 0.17 (Vd/ Vt) 0.56 + 0.09 0.62 + 0.12 0.14 Data expressed as mean + SD *(Ve) minute ventilation, (RR) respiratory rate, (VT) tidal volume, (PIF) peak inspiratory flow, (PEF ) peak expiratory flow, (RSBI) rapid shallow breathing index, (Ti) inspiratory time, (Te) expiratory time, (VCO2) carbon dioxide production rate & (Vd/Vt) dead space ventilation., p<0.05 between early SBT and late SBT
84 CHAPTER 5 DISCUSSION Principal Findings Heart rate variability analysis is a novel method of quantification of overall stress. This is the first study that analyzed the overall stress level in PMV patients during MV and at the point of failure during the subsequent spontaneous breathin g trial using a within subject design. Mechanical Ventilator Weaning HRV Changes In Aim 1, we hypothesized that in PMV patients during failed SBT heart rate variability analysis will indicate higher overall stress level at the point of failure compared to MV support. T he frequency domain analysis showed that at the point of failure HFnu which is regarded as the as an index of the level of parasympathetic activity decreased significantly. Moreover, LFnu reflects both sympathetic and parasympathetic activity increased significantly. Additionally the LF/HF ratio is considered to mirror sympathovagal balance and we found a significant increase in the LF/HF ratio at the point of failure in SBT as compared to full MV support Collectively, these changes indicate r elatively high levels of physiological stress when the patients fail the SBT. There are a number of potential explanations for these changes HRV may be influenced by a variety of confounding variables. The m ain factors that influence HRV are age, gender (17) and diseases such as diabetes mellitus, congestive heart failure and various neurological diseases which constitute major co morbidities in ICU patients (14, 18) Additionally, medications acting directly or indirectly on the ANS potentially influence HRV (18) Therefore in these studies the difference found could be
85 the result of intrinsic differences between groups, rather than the difference between outcomes (success or failure in the SBT) within a subj ect. In our study, as all subjects acted as their own controls, thus the effects of age, gender, and disease were controlled. Additionally, no medication changes occurred during data recording so that medications cannot account for the considerable variab ility found in our study. HRV is also influenced by circadian rhythms. All SBT were started between 8:00 and 9:00 am; therefore the circadian rhythm variation of HRV was controlled. Other possible causes of change in HF component are respiratory rate and tidal volume. The HF component of HRV decreases with increased respiratory rate and decreased VT (194, 195) We found no significant changes in RR and tidal volume during MV support and at the point of failure dur ing SBT. Thus, it is unlikely that the lower HRV in the failure group was because of significant differences in respiratory rate and tidal volume. The only difference s we found during MV support and at the point of failure during SBT were the PIF and V E in creased significantly at failure. The concept of LF (n.u.) as a marker of cardiac sympathetic modulation is debatable and the change in LF (n.u.) during SBT may be due to respiratory autonomic interactions, the pathologic processes of sympathetic modulatio n of heart beat fluctuations in patients recovering from respiratory failure, or the influence of unde rlying diseases and medications (196 201) The critical care environment may also produce significant and chroni c sympathetic activation in critically ill patients. Psychological stress is difficult to measure in critically ill patients and even more so in mechanically ventilated patients. However,
86 Yu et al. (1999) (202) found that anxiety was highly associated w ith downregulation of adrenergic receptors and a blunted ability to respond to further elevation in catecholamines in healthy individuals; and Otte et al. (2005) (107) found that depressive symptoms were associated with elevated NE levels in patients with coronary artery d isease. In current study the patients were left undisturbed, and every effort was made to keep the environmental conditions stable throughout data acquisition, suggesting a limited role for environmental factors. T he change of HRV during different ventilat or settings was investigated in an animal study by Frazier et al. (203) They found that there were significant increases in very LF power (sympathetic tone) with a concomitant significant reduction in HF power (parasympathetic tone) with exposure to a combination of pressure support and continuous positive airway pressure (203) These changes in HRV were associated with significantly increased heart rate and reduced right ventricular end diastolic volume. Additionally, Shen et al. investigated the change of autonomic nervous activity during ventilator weaning by HRV analysis (184) They found t hat patients who failed a spontaneous breathing trial exhibited a shift to predominant sympathetic control of heart rate during spontaneous breathing in comparison with those who were successfully weaned (184) Furthermore, in a recent study, Frazier et al. (16) evaluated the autonomic responses of critically ill patients during a 24 hr period of mechanical ventilatory support which included their initial spontaneous breathing trial using continuous positive airway pressure. The autonomic tone was quantified using plasma catecholamine and
87 heart rate variability indices. The study reported that nearly two thirds of the patients demonstrated abnormal autonomic function and this dysfunction was more severe in those patients who were unable to sustain spontaneous ventilation as illustrated by reductions in time domain and geometric measures of HRV. Plasma catecholamine levels were also elevated at both data points (16) However, patients in the success group exhibited reduced plasma catecholamines in response to the CPAP weaning trial, whereas those in the failure group exhibited increased plasma catecholamines in response to the weaning trial (16) Prior research has established a substantial link between red uced HRV and poorer outcomes in a variety of critically ill patient populations. Winchell et al. (204) found that reduced total autonomic power was associated with increased mortality in a group of general surgical ICU patients, and in a later study (205) they found that reduced HRV was associated with altered cerebral perfusion and increased mortality in patients with severe h ead injury. In other critically ill populations, reduced HRV on postoperative Day 1 was an independent predictor of complicated recovery from abdominal aortic surgery (206) and an independent predictor of mortality in patients with multiple organ dysfunctio n syndrome (207) Additionally, in patients with acute myocardial infarction and heart failure, decreased HRV has been well established as an independent predictor of life threatening dysrhythmias like ventricular t achycardia and of mortality (208, 209) To date, the association between autonomic tone and the success of ventilator weaning has not been a prominent focus of study. There is currently interest in identifying quant ifiable, rapidly attainable measures
88 Measurements of HRV have shown promise as such a tool. In the clinical setting of critical illness, methods of collection and in terpretation of autonomic nervous system activity with potential utility in real time have been undertaken with some success (210) (204) Several studies have even implied the use of HRV as an additional vital sign in the assessment and care of critically ill patients with the hopes of earlier intervention for those patients deemed at higher risk ba sed on HRV derived parameter(s) (210) (204, 211) Mechanical Ventilator weaning Endocrine Stress Response In aim 2 we hypothesized that in PMV patients during failed SBT plasma catecho lamine analysis will indicate higher physiological stress level at the point of failure as compared to MV support. We found that the catecholamine concentrations were significantly elevated from normal values in these patients at both sampling times (labor atory normal range for Epi = supine < 50 pg/ml, NE = supine 110 to 410 pg/ml). These levels increased significantly at the point of failure indicating very high levels of stress during failure. The most well known physiological response to stress concerns the hypothalamus pituitary adrenal (HPA) axis (212) Emotional respons es to perceived threat are generated in the limbic system, and signals are sent to subcortical brain centers and the hypothalamus. The hypothalamus, in turn, activates the posterior pituitary to secrete vasopressin and oxytocin, and the adrenal medulla to secrete epinephrine and norepinephrine (212) Catecholamines have a shor t half life of 2 minutes and, therefore, provide an immediate measure of stress (213) Thus the hormonal stress response may provide an objective method to measure patient comfort during MV
89 However, Brinkmann et al. found that catecholamine and stress hormone blood concentrations did not i ncrease following withdrawal of sedation and cessation of MV after abdominal surgery (214) Additionally, Rathgeber et al. used biphasic positive airway pressure, controlled mandatory ventilation, or intermittent m andatory ventilation for weaning after cardiac surgery (215) The hormonal response was not affected by the discomfort of breathing. Calzia et al. (216) compared oxygen consumption (VO 2 ) work of breathing (WOB), cardiovascular effects, and the plasma concentrations of catecholamines and other hormones involved in the stress response during weaning using different ventilatory modes, in patients who had aorto coronary bypass surgery. The study found that during the early stages of weaning from MV after cardiac surgery, switching from passive ventilation to partial spontaneous breathing and interruption of continuous sedation did not alter the postoperative hormonal stress response and VO 2 (216) Furthermore, Quinn et al. (217) compared the effects of synchronized i ntermittent mandatory ventilation and biphasic positive airway pressure on the stress response, during weaning after cardiac surgery. Neither mode affected postoperative plasma cortisol, epinephrine, or norepinephrine concentrations. In patients who underw ent cardiac surgery, Brinkmann et al. (214) and Calzia et al. (216) foun d no significant differences in plasma epinephrine and norepinephrine levels during weaning. On the other hand, hormonal stress response has been used successfully in preterm infants to demonstrate the advantage of mechanically supported spontaneous breat hing over controlled MV in terms of reduced stress response (217) Additionall y, Oh et al. (1991) measured plasma catecholamines in 20 short term ventilated patients during weaning by synchronized intermittent mandatory ventilation and SIMV and
90 continuous positive airway pressure (CPAP) (218) The study demonstrated that during the weaning trial plasma epinephrine and non epinephrine increased significantly as the ventilator assistance was reduced (218) Additionally, studies that evaluated the effects of MV on oxygen consumption in ICU patients during weaning trials have found increased oxygen requirement associated with the ris e in catecholamine levels (7, 77) Furthermore, Koksal et al. (219) compared changes in plasma concentrations of insulin, cortisol and glucose, and in urine vanilmandelic acid (VMA), the end product of catecholamine metabolism during weaning and after extubation, using the three different mo des of pressure support (PS) ventilation, CPAP and T piece, in intensive care patients. The study found the greatest changes in measured variables during the 2 hours of weaning occurred in T piece trial concluding that the weaning via the T piece caused a greater stress response compared to the PS and CPAP modes (219) Mechanical V entilator Weaning: Breathing Pattern analysis In aim 3 we hypothesized that in PMV patients during failed SBT the breathing pattern will be significantly different between the start and the point of failure. We found a significant increase in V E and PIF at the point of failure during indicating a higher respiratory drive. In patients who were ventilated for shorter periods of time a number of breathing pattern parameters have been reported to be associated with the success or failure of ventilator disconti nuation (4) Previously, Sahn et al. (115) reported that a V E < 10 l/minute is associated with weaning success. Subsequent studies showed that V E values > 15 20 l/minute are helpful in identifying patients who are unlikely to be liberated from MV but lower values were not helpful i n predicting successful liberation (5,
91 220 222) Moreover, Martinez et al. (223) showed that the time of recovery of V E from the end of a 2 hour spontaneous breathing trial to return to baseline after reinstitution of MV is a good predictor of liberation from MV They concluded that short V E recovery times (3 4 minutes) may h elp in determining respiratory reserve and be valuable in predi cting the success of extubation (223) Reported weaning predictors including vital capacity, tidal volume, respiratory rate, minute ventilation, rapid shallow breathing index (RSBI), and maximal inspiratory pressure (Pi max ) have been developed and applied in clinical settings. Moreover, integrated fact ors also have been employed (4) for example, CROP index (CROP = dynamic compliance multiplies by maximal inspiratory pressure by PaO2/PAO2 and divides this product by the respiratory rate). However, analysis of rec eiver operating characteristics curves (ROC) has shown none of these indices are sufficiently sensitive and specific to be useful in predicting the success of ventilation discontinuation, especially in the elderly and/or in the PMV patients. (4) Yet few investigators have attempted to examine the breathing variability during weaning protocols (110, 221, 224, 225) Bien et al. reported that breathing pattern variability in th e patients who failed to weaning trials was significantly lower than those who passed to weaning trials (110) Accordingly, they also reported that the area under the ROC curves of these breathing variability indic es was within 0.73 0.80. Consistently, Wysocki et al. showed that reduced breathing variability, quantified by using CV, during a 60 min SBT was associated with a high incidence of weaning failure in the ICU patients (224) In contrast, EI Khatib et al. and Engoren found that breathing variability measured by entropy indices was more irregular (higher) in patients who failed
92 extubation compared to patients who passed extubation trials (221, 225) It is hard to explain the inconsistency of these findings because of the nature of the corresponding populations and different experimental conditions. Role of D ead S pace in Prolonged Mechanical Ventilation Patient Dead space is usu ally related to tidal volume and the normal adult dead space to tidal volume ratio is in the range of 0.2 to 0.35 during resting breathing. Dead space is increased in number of disease states associated with abnormalities of gas exchange (226) The patients with a high V D /V T ratios (greater than 0.6) are considered as difficult to wean. However, the exception exists. Earlier studies (227) have documented two successful weaning cases whose V D /V T ratios were repeatedly in excess of 0.65. They found that V D /V T ratios were similar during weaning periods compared with values measured on MV At the time of successful weaning, the V D /V T ratio was still above 0.65. Unfortunately, the explana tion for the persistence increases in V D /V T ratio remains unclear. The role of dead space in predicting the outcome of successful weaning from MV is controversial. For example, Hubble et al. have shown that a significant difference in mean V D /V T ratio (cal culated using a CO2SMO plus) between successful and failed to wean children of MV (0.44+/ 0.17 vs. 0.68+/ 0.16; p=0.0001) (189) On the other hand, Bousso et al. applied a similar analysis strategy reporting different results; there was no significant difference of the V D /V T ratios for patients with succe ssful and failed weaning (0.62+/ 0.17 vs. 0.65+/ 0.21; p=0.472) (228) The difference in results of these two studies may be reflecting the presence of different populations or measurement errors or both. In the Hub ICU, with supposedly normal lungs, while the population of Bousso comprised patients with
93 severe acute respiratory disease such as ARDS. With the lung injury, the dead space is increased and assoc iated with increased ventilation with high V/Q regions and larger anatomic/alveolar dead space. In the Nucton et al. study, they demonstrated that increased V D /V T ratio as a consequence of pulmonary vascular injury was observed in patients with ARDS and in creased V D /V T ratio was an independent risk factor for death among these patients (229) It seems that an increased V D /V T ratio in patients with lung injury results from two different mechanisms. First, dead space r eflects the efficiency of gas exchange; any alteration in the distribution of pulmonary blood flow will change in dead space. For example, a high V D /V T reflects increased ventilation to unperfected areas of lung. Second, dead space reflects the extent of p ulmonary vascular injury. Injury to the microcirculation, which is characteristic features of ARDS, increased pulmonary vascular resistance by causing several mechanisms such as vasoconstriction, micro thromboembolism from platelet or endothelial cell swel ling (230) All of these mechanisms can increase alveolar dead space, as consequence of increased V D /V T ratio. As mentioned, another explanation is the measurement errors; V D /V T ratios in D /V T ratio is usually derived from the Bohr Enghof equation (see as above). In this equation the assumption is made that PaCO2 is equal to alveolar carbon dioxide t ension (P A CO2). This assumption can be violated in the presence of a significant anatomical shunt and imbalance of V A /Q (231) It is stated that if the shunt (Qs) as a proportion of cardiac output (Qt) is greater than 20 percent, this would overestimate V D /V T because of a high portion of blood flow from the right side of the heart to the left side of the heart without participating in gas exchange
94 (231) In turns, carbon dioxide tension in the pulmonary capillaries (PcCO2) must participate in alveolar gas exchange, and P A CO2 would be lowered than PaCO2, thus increasing the calculated V D /V T. More accurate estima tes of V D /V T require the multiple inert gas elimination technique (MIGET) but this technique is complicated and clinically impractical in t he mechanically ventilated patients. Here is an example to demonstrate the measurement errors; one study (232) compared MIGET to the Bohr Enghof equation to calculate V D /V T in ARDS patients and found markedly overestimated V D /V T (0.37+/ 0.04 vs. 0.64+/ 0.03, respectively), which the latter ignored the effect of anatomic shunt. Me chanical Ventilation Weaning Arterial Blood gases Arterial blood gases (ABGs) are used routinely to assess alveolar ventilation during weaning yet surprisingly little is known about their appropriate role during SBTs. Beyond routine bedside monitoring (of heart rate, respiratory rate, blood pressure and subjective parameters), ABGs affect decision making infrequently and may not necessarily lead to a correct decision (233) Additionally, End tidal CO 2 (EtCO 2 ; capnography) has be routinely monitored continuously during SBT. It can also be helpful in monitoring dead space in mechanically ventilated patients. Unfortunately, it may be insufficiently sensitive to detec t episodes of hypercapnia (234) Some data suggest poor sensitivity detecting less than 10 mm Hg increments of PaCO 2 but greater sensit ivity for increases of 10 mm Hg or more (233) But accuracy is reduced in patients with parenchymal lung disease, which comprise a majority of medically ill pat ients (235) False positives (236) (ie,
95 increments of EtCO 2 without significant increments in PaCO 2 ) may also contribute to unnecessary ABGs (234) Limitations of the Current Project The major limitation of this study is the absence of successful SBT to compare. The critically ill mechanically ventilated patients undergo standa rd weaning procedure time on MV i s actually spent during weaning (65) By d efinition PMV patient has undergone > 21 days of MV with the weaning process comp licated by multiple SBT failure (3) These PMV patients were recruited for the inspiratory muscle training study. This makes it very r are for the patient to have a successful trial on the first day. In the course of 1 year that this study was conducted we observed a total of 13 patients 10 of which failed the initial SBT while only 3 were successful. These 3 patients did not fail and bre athed spontaneously for 48 consecutive hours and were weaned on the first SBT entering the study. The data from these trials is summarized in Chapter 6. Whether heart rate variability reflects cardiac sympathetic activity is a topic of much debate (26, 33) Microneurographic recordings of muscle sympathetic nerve activity (MSNA) offer a direct measurement of efferent postganglionic sympathetic nerve activity, and as such are considered the gold standard measurement of global sympathetic outflow to skeletal muscle (237) In the current project although we did measure the plasma catecholamines, we did not measure MSNA recordings during SBT. However, previous stu dies have compared MSNA and low frequency fluctuations of heart rate variability at rest and shown no relationship in healthy individuals, o r in those with chronic disease (238, 239) However, studies employing orth ostatic stress or
96 pharmacologic manipulation of blood pressure have demonstrated significant rel ationships between MSNA and HRV (178, 240) Additionally, in healthy subjects, parallel increases in MSNA and the ratio of low to high frequency heart rate variability (LF/HF) were observed with orthostatic challenge (241) while experim ental changes in blood pressure result in parallel responses in MSNA and LF These results suggest that MSNA and cardiac sympathetic markers of HRV may change in parallel in response to an autonomic challenge. Importantly, due to the invasiveness and tech nical complexity associated with this technique, microneurography is generally not practical for repeated measurements or large clinical studies. Finally, because of the inherited limitation of HRV analysis, (186) the application as a weaning parameter is limited to those without significant arrhythmias. Furthermore, this was a small sample size and needs a larger study to confirm these results.
97 C HAPTER 6 SUCCESSFUL SPONTANEOUS BREATHING TRIALS In the course of 1 year t hat this study was conducted, 13 patients experiencing prolonged mechanical ventilation (PMV) met the inclusion criteria and were studies. 10 of these patients failed the spontaneous breathing trials ( SBT ) while 3 patients were successful in the SBT These 3 patients did not show any objective or subjective signs of failure and breathed spontaneously for 48 consecutive hours These subjects were were classified as successfully weaned Sample data from the successful SBT is presented. SBT were started between 8:00 am to 9:00 am and lasted until failure or the predetermined duration was reached. During SBT, the patient was disconnected from the ventilator and required to breathe spont aneously while receiving supplemental oxygen to keep SpO2 > 90%. Patients were maintained in a semi recumbent position (keeping head end of the bed 30 elevated). During SBT, all patients received routine nursing care, but no rehabilitation services. De mographic Data 3 (M/F: 2/1) patients did not fail the trial and breathed on their own for 48 hours and were subsequently weaned. The data was obtained at 380 + 86.6 minutes during the trial. The average duration of mechanical ventilation ( MV ) support (54 16 days). Thus all the patients satisfied the minimum criteria of PMV of > 21 days of MV support. Typical ventilator setting included intermittent mandatory ventilation rates of 2 to 4 breaths / minute, pressure support of 5 to 15 cm H 2 O, continuous pos itive airway pressure of 3 to 8 cm H 2 O, with a FiO 2 of 0.35 to 0.5. The relevant clinical features are summarized in Table 6 1. The blood chemistry on the day of SBT is shown in Table 6 2.
98 Vital signs including heart rate and blood pressure during MV suppo rt and late SBT are shown in Table 6 3. The Heart rate and blood pressure did not show statistically significant difference. Additionally, arterial blood gas values during MV support and during late SBT are shown in Table 6 4. ABG values were not different between MV support and during late SBT. Heart Rate Variability Frequency Domain Analysis HRV indices are shown in Table 6 5. High frequency normalized units [ HF (nu) ] Low frequency normalized units LF(nu) as well as LF/HF ratio were not significant ly d ifferent. Plasma Catecholamine Levels at SBT Failure Plasma levels of catecholamines during MV support and late SBT are shown in Table 6 6. NE as well as EP were not different between MV support and late SBT. Breathing Pattern Change between Early and Late SBT Breathing pattern variables during MV support and late SBT are shown in Table 4. Breathing pattern variables including minute ventilation, respiratory rate, inspired tidal volume, inspiratory time, expiratory time as well as peak inspiratory flow rate were not different. Additionally, the dead space ventilation was not different during MV support and during late SBT. Conclusion Although HRV indices were low and plasma catecholamine levels were high at both sampling times compared to the healthy norms the values did not change during the successful SBT trial. There is substantive evidence that positive pressure MV itself
99 generates a complex neurohormonal response because of altered intrathoracic pressure and changes in thoracic hemodynamics and may b e responsible for these changes (242) The c ritical care environment may also produce significant and chronic sympathetic activation in critically ill patients. (16) Previously, Shen et al. investigated the change of autonomic nervous activity during ventilat or weaning by HRV analysis (184) They found that in the success group, the changes of HR, BP, and HRV components were insignificant among the three phases. (184) Furthermore, in a recent study, Frazier et al. (16) evaluated the autonomic responses of critically ill patients during a 24 hr period of mechanical ventilatory support and during the 24 hr th at included their initial spontaneous breathing trial using continuous positive airway pressure. Patients in the success group exhibited reduced plasma catecholamines in response to the CPAP weaning trial, whereas those in the failure group exhibited incre ased plasma catecholamines in response to the weaning trial (16) Thus, these data from successful SBT demonstrates that the physiological stress did not change during the SBT and the patients could tolerate the SB T well.
100 Table 6 1 Demographic Data Variable (Unit) Value Age (years) 68 + 9 Weight (kg) 66 + 7 BMI 24.3 + 1.2 Gender (male/female) 2:1 Acute Physiology and Chronic Health Evaluation (APACHE II) Score 20 + 6 Mechanical Ventilation (Days) 54 + 16 Spontaneous Breathing Trial Duration (mins) 380 + 86 *Data expressed as mean + SD
101 Table 6 2 Blood Chemistry Values Variable Unit Result Serum sodium mEq/L 1 53. 1 + 1 .5 Serum potassium mEq/L 4 11 + 1 .38 Serum Chloride mEq/L 1 1 6. 87 + 0 .91 Bicarbonate total mmol/L 2 4 .21 + 1 .09 Blood urea nitrogen mg/dL 4 4 .02 + 7 .0 8 Serum creatinine mg/dL 1.4 4 + 1. 1 White b lood c ell c ount (*10 3 )mm 3 11 .71 + 5. 4 Hemoglobin gm/dL 10 .89 + 1 0 5 Hematocrit % 2 7 .62 + 2. 45 Bilirubin mg/dL 0. 9 1 + 0. 3 2 Serum pre albumin mg/ dl 12 0 1 + 2 .09 Total Protein gm/dL 6 .45 + 1.2 Serum albumin gm/dL 1 .8 5 + 0. 3 *Data expressed as mean + SD Na= Sodium, K = Potassium, CL= Cloride, CO2 = Carbondioxide,BUN = B lood Urea Nitrogen Cr = Creatinin, WBC= White blood cells, HGB= hemoglobin, HCT = Hematocrit, Billirub = Billirubin, Pre alb = prealbumin, TP = total protein, Alb = Albumin.
102 Table 6 3 Vital Signs On MV During SBT t Test (p value) Heart Rate 91 + 6 92 + 9 0.89 Blood Pressure Systolic 119 + 15 130 + 18 0.47 Diastolic 62 + 23 53 + 8 0.44 *MV: Mechanical ventilation, SBT: Spontaneous breathing trial, Data expressed as mean + SD
103 Table 6 4 : Arterial Blood Gas Data On MV During SBT t Test (p value) pH 7.41 + 0.02 7.4 + 0.03 0.70 PCO 2 ( mmHg) 44.7 + 0.3 42.80 + 3.45 0.71 PO 2 ( mmHg) 101.4 + 1.7 93.6 + 12.4 0.60 HCO 3 ( mmol/l) 27.45 + 1.05 26.05 + 4.35 0.74 SaO 2 ( %) 99 + 1.41 97.5 + 0.71 0.50 PaO 2 /FiO 2 296.3 + 66.5 278.2 + 106.30 0.64 pH: power of Hydrogen, PaCO 2 : partial pressure of carbon dioxide, PaO 2 : partial pressure of oxygen, HCO 3 : actual bicarbonate contents, SaO 2 : oxygen saturation of hemoglobin, PaO 2 /FiO 2 : ratio of arterial oxygen partial pressure to fractional inspired oxygen concentration. Data expressed as mean + SD
104 Table 6 5 Breathing Pattern Vari ables Early SBT Late SBT t Test (p value) VE 8.07 + 2.8 8.23 + 3.0 0.6 RR 27.18 + 8.9 28.03 + 8.4 0.37 Vti 316 + 84 324 + 102 0.83 PIF 33.11 + 7.4 34.69 + 8.4 0.51 PEF 32.34 + 7.7 33.56 + 8.34 0.65 RSBI 80.25 + 30.8 87.44 + 32.2 0.52 Ti 0.81 + 0 .19 0.78 + 0.21 0.56 Te 1.66 + 0.7 1.54 + 0.62 0.47 VCO2 179.9 + 62.1 177.5 + 74.3 0.54 (Vd/ Vt) 0.55 + 0.09 0.60 + 0.12 0.34 *(Ve) minute ventilation, (RR) respiratory rate, (VT) tidal volume, (PIF) peak inspiratory flow, (PEF) peak expiratory flow, (RSBI) rapid shallow breathing index, (Ti) inspiratory time, (Te) expiratory time, (VCO2) carbon dioxide production rate & (Vd/Vt) dead space ventilation. Data expressed as mean + SD, p<0.05 between early SBT and late SBT
105 Table 6 6 : Plasma Catecholami ne On MV During SBT t Test (p value) NE (pg/ml) 742 574 340 202 0.12 Ep (pg/ml) 60.757.9 59.3 19 0.5 NE: Norepinephrine, EP: Epinephrine. Data expressed as mean + SD. p < 0.05 between MV support and SBT failure.
106 Table 6 7 Heart Rate Varia bility Analysis: Frequency Domain Mea s ures On MV AT Failure t Test (p value) HF ln (ms2) 6.362.3 6.111.2 0.22 LF ln (ms2) 7.10.3 7.87 0.9 0.16 HF (n.u.) 6612 5616 0.2 LF (n.u) 3312 4316 0.12 LF/HF 2.60.3 2.31.8 0.34 HF ln: High Frequency variability, LF ln: Low Frequency variability, HF (n.u.): High Frequency variability normalized units, LF (n.u.): Low Frequency variability normalized units. Data expressed as mean + SD. p < 0.05 between MV support and SBT failure.
107 CHAPTER 7 CONCLUSION A ND FUTURE DIRECTIONS This study is clinically important. Currently, there is no consensus on which physiological variable to monitor in PMV patients during the SBT to decide whether to prolong or curtail a SBT trial. A f ailed SBT is an extremely distressf ul experience for the patient, however, it is difficult to quantify physiological stress level during SBT in critically ill patients and more so in PMV patients. There is currently interest in identifying quantifiable, rapidly attainable measures that may be utilized to monitor patient tolerance of SBT. Evaluation of HRV parameters provides an indicator of physiologic status and may yield an earlier indication of impending deterioration or response SBT. Currently the standard measures of physiological stres s are circulating stress hormones and muscle sympathetic nerve activity analysis. However, plasma catecholamine analysis requires blood samples and laboratory analyses and is therefore not suitable for bedside monitoring of intraoperative stress. Whereas, due to the invasiveness and technical complexity associated with this technique, microneurography is generally not practical for repeated measurements or in clinical protocols. This project demonstrates the feasibility of using heart rate variability ana lysis as a novel to quantify and monitor in real time the physiological stress associated with a SBT respond to normal regulatory impulses that influence cardiac rate and rhy thm. HRV is a sensitive, tool which can be used bedside to monitor the physiological stress real time. Additionally, HRV analysis is technically straightforward and an automatically derived
108 weaning predictor in a busy intensive care setting would be an at tractive one. Commercial equipment designed to measure HRV is available which makes this technique far more suitable for studies that involve large samples and/or repeated measures in clinical settings. Specific suggestions for further study include, To study the use of HRV analysis through regular screening during MV support as predictive tool for weaning failure. To study the tolerance of different IMST loads in critically ill patients using HRV changes To study the tolerance to regular rehabilitation i nterventions (occupational and physical therapy) in critically ill patients
109 APPENDIX A BASIC ELECTROPHYSIOL OGY OF HEART Cells within the sinoatrial (SA) node are the primary pacemaker site within the heart. These cells are characterized as hav ing no true resting potential, but instead generate regular, spontaneous action potentials. Unlike non pacemaker action potentials in the heart, and most other cells that elicit action potentials (e.g., nerve cells, muscle cells), the depolarizing current is carried into the cell primarily by relatively slow Ca++ currents instead of by fast Na+ currents. There are, in fact, no fast Na+ channels and currents operating in SA nodal cells. This results in slower action potentials in terms of how rapidly they de polarize. Therefore, these pacemaker action potentials are sometimes referred to as "slow response" action potentials. SA nodal action potentials are divided into three phases. Phase 4 is the spontaneous depolarization (pacemaker potential) that triggers t he action potential once the membrane potential reaches threshold between 40 and 30 mV). Phase 0 is the depolarization phase of the action potential. This is followed by phase 3 repolarization. Once the cell is completely repolarized at about 60 mV, the cycle is spontaneously repeated. The changes in membrane potential during the different phases are brought about by changes in the movement of ions (principally Ca++ and K+, and to a lesser extent Na+) across the membrane through ion channels that open an d close at different times during the action potential. When a channel is opened, there is increased electrical conductance (g) of specific ions through that ion channel. Closure of ion channels causes ion conductance to decrease. As ions flow through open channels, they generate electrical currents (i or I) that change the membrane potential.
110 In the SA node, three ions are particularly important in generating the pacemaker action potential. At the end of repolarization, when the membrane potential is very negative (about 60 mV), ion channels open that conduct slow, inward (depolarizing) Na+ currents. These currents are called "funny" currents and abbreviated as "If". These depolarizing currents cause the membrane potential to begin to spontaneously depola rize, thereby initiating Phase 4. As the membrane potential reaches about 50 mV, another type of channel opens. This channel is called transient or T type Ca++ channel. As Ca++ enters the cell through these channels down its electrochemical gradient, the inward directed Ca++ currents further depolarize the cell. As the membrane continues to depolarize to about 40 mV, a second Ca++ channel opens. These are the so called long lasting, or L type Ca++ channels. Opening of these channels causes more Ca++ to en ter the cell and to further depolarize the cell until an action potential threshold is reached (usually between 40 and 30 mV). During Phase 4 there is also a slow decline in the outward movement of K+ as the K+ channels responsible for Phase 3 continue t o close. This fall in K+ conductance (gK+) contributes to the depolarizing pacemaker potential. Phase 0 depolarization is primarily caused by increased Ca++ conductance (gCa++) through the L type Ca++ channels that began to open toward the end of Phase 4. The "funny" currents, and Ca++ currents through the T type Ca++ channels, decline during this phase as their respective channels close. Because the movement of Ca++ through these channels into the cell is not rapid, the rate of depolarization (slope of Ph ase 0) is much slower than found in other cardiac cells (e.g., Purkinje cells).
111 Repolarization occurs (Phase 3) as K+ channels open (increased gK+) thereby increasing the outward directed, hyperpolarizing K+ currents. At the same time, the L type Ca++ chan nels become inactivated and close, which decreases gCa++ and the inward depolarizing Ca++ currents. During depolarization, the membrane potential (Em) moves toward the equilibrium potential for Ca++, which is about +134 mV. During conductance) increases, which brings Em closer toward the equilibrium potential for K+, which is about 96 mV). Although pacemaker activity is spontaneously generated by SA nodal cells, the rate of this activity can be modified significantly by external factors such as by autonomic nerves, hormones, drugs, ions, and ischemia/hypoxia. It is important to note that action potentials described for SA nodal cells are very similar to those found in the atr ioventrcular (AV) node. Therefore, action potentials in the AV node, like the SA node, are determined primarily by changes in slow inward Ca++ and K+ currents, and do not involve fast Na+ currents. AV nodal action potentials also have intrinsic pacemaker a ctivity produced by the same ion currents as described above for SA nodal cells. Figure A 1 summarizes the automaticity of pacemaker cells of heart. The cardiac musculature consists of two types of muscle cells (or fibers): (i) cells that initiate and co nduct impulses, and (ii) cells that, besides conducting, respond to stimuli by contracting. The cardiac conduction system is composed of the sinoatrial node (SAN), the atrioventicular node (AVN), the HIS bundle, the right and left bundle branches, the fasc icles and the Purkinje fibers. The conduction system consists of specialized myocytes. Its atrial components, the SAN (subepicardial) and the AVN
112 (subendocardial), are in contact with the atrial myocardium. The His bundle goes through the right fibrous tri gone (central fibrous body) and runs at the junction of the membranous and muscular septum before it divides into the right and left ventricular bundle branches. The right bundle branch is a cord like structure with a 1 mm diameter, which proceeds along th e septal and moderator bands to reach the anterior papillary muscle. In contrast, the left bundle branch forms a broad sheet of conduction fibers that splits along the left side of interventricular septum into three indistinct fascicles . The action pot entials generated by the SA node spread throughout the atria primarily by cell to cell conduction at a velocity of about 0.5 m/sec. There is some functional evidence for the existence of specialized conducting pathways within the atria (termed internodal t racts), although this is controversial. As the wave of action potentials depolarizes the atrial muscle, the cardiomyocytes contract by a process termed excitation contraction coupling. Normally, the only pathway available for action potentials to enter the ventricles is through a specialized region of cells (atrioventricular node, or AV node) located in the inferior posterior region of the interatrial septum. The AV node is a highly specialized conducting tissue (cardiac, not neural in origin) that slows th e impulse conduction considerably (to about 0.05 m/sec) thereby allowing sufficient time for complete atrial depolarization and contraction (systole) prior to ventricular depolarization and contraction. The impulses then enter the base of the ventricle at the Bundle of His and then follow the left and right bundle branches along the interventricular septum. These specialized fibers conduct the impulses at a very rapid velocity (about 2 m/sec). The bundle branches then divide into an extensive system of Pu rkinje fibers that conduct the impulses at high velocity (about 4 m/sec)
113 throughout the ventricles. This results in rapid depolarization of ventricular myocytes throughout both ventricles.
114 Figure A 1 Sinoatrial Node Action Potentials
115 APPENDIX B BASIC ELECTROCARDIOG RAM The electrocardiogram (ECG) is a tool for evaluating the electrical events in the heart. ECG measurements have been used for diagnostic purposes for more than a century. The action potentials of cardiac muscle cells can be viewed as batteries that cause charge to move throughout the body fluids. These moving charges are caused by all the action potentials occurring simultaneously in many individual myocardial cells, and their result can be detected by recording electrodes on the surface of the skin. The ECG does not provide a direct record of the changes in membrane potential across individual muscle cells. Rather, it is a measure of the currents generated in the extracellular fluid by the changes occurring simultaneously in many cardiac cells. A conventional three lead measurement of the ECG is performed by using three leads, placed on the right and left shoulder bones for the first and second leads, and on the left leg or lower left rib bone for the third lead. The result ant ECG signal, recorded in this way, is shown schematically in The P wave is the first deflection and represents the electrical impulse through the atrial musculature (depolarization). The second deflection is the QRS complex and represents the spread of the electrical impulse through the ventricular musculature, which triggers the ventricular contraction. The P R interval is measured from the beginning of the P wave to the beginning of the QRS complex. It reflects the time taken by impulse to travel the e ntire distance from the SA node to the ventricular muscle. The final deflection is the T wave and represents the period of recovery for the ventricles (i.e. repolarization).
116 Figure B 1Normal EKG waveform
117 APPENDIX C THE POINCARE PLOT Introduction: Variability analysis is essentially a collection of various mathematical and computational techniques that characterize biologic time series with respect to their overall fluctuation, spectral composition, scale free variation, and degree of irregularity or complexity. A growing exploration of patterns of variation or fluctuations in physiologic time series, particularly heart rate variability (HRV) analysis, has been shown to about the health of the system producing the dynamics. The Poincare plot is a representation of a time series into a Cartesian plane (or phase space), where the values of each pair of successive elements of the time series define a point in the plot. (1 3) The Poincare plot is a very simplified phase space with dimension two and delay or lag of one beat (i.e. each R R interval is plotted as a function of the previous R R interval). (243) T displayed by the Poincare plot as the HRV has a higher estimated dimension than two. (244) However, the Poincare plot gives a useful visual contact to the R R data by representing both short and long term variations included in the recording. (243) Poincar HRV plot is a graph in which each RR interval is plotted against next RR interval (a type of delay map) Points above the line of identity indicate R R intervals that are longer than the preceding R R interval, and points below the line of identityindicate a shorter R R interval than the previous. The quantitative analysis of the HRV attractor displayed by the Poincare plot can be made by adjusting it to an ellipse. (243) Using this technique, three indexes can be obtained: the standard deviation (SD) of the instantaneous beat
118 to beat R R interval variability (minor axis of the ellipse or SD1), the SD of the long term R R interval variability (major axis of the ellipse or SD2) and the axes ratio (SD1/SD2). (245) The physiological meaning of Poincare plot indexes has been explored in different experimental settings (243, 246) It is known that the sympatho vagal interaction during exercise is reflected by the Poinc are plot indexes and that the SD1 axis reflects vagal activity in certain specific conditions (247) At the point of failure SD1 decreased from 24.12 +4.22 to 19.06+4.28 (p<0.001) while SD2 decreased from 46.42+7.51 to 27.96+9.28(p<0.001) and SD1 /SD2 increased from 0.52+0.56 to 0.68+0.46 (p<0.001). Nonlinear analysis of the HRV using a Poi ncar plot can reflect the impact of stress situations on short duration records based on the SD1 parameter (248, 249) Our results indicate a significant inhibition of the parasympathetic activity at the point of f ailure during SBT as the SD1 parameter is significantly lower than when the patients were receiving mechanical ventilation Moreover, the increased SD1/SD2 ratio indicates increased sympathetic tone at the point of failure during SBT compared to mechanica l ventilation support. Thus, because Poincar plot parameters are easy to compute and because the Poincar plot is a quantitative visual tool, it could be applied to the analysis of R R interval data gathered over relative short time periods during mechani cal ventilation weaning.
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140 BIOGRAPHICAL SKETCH Harshavardhan Deoghare received his bachelor of physical therapy degree from University of Pune in April 2001. He then worked as a consultant physical therapist in National heart Institute, Pune for two years. Deciding to focus his carrier in cardiorespiratory rehabilitation research, Harshavardhan began his doctoral work at the University of Florida in 2004 under the direction of Dr. A.D. Martin. Harshavardhan focused his studies on pulmonary physiology and inspiratory muscle strength training in difficult to wean patients. He received his PhD in August 2010.