<%BANNER%>

The Use of 320 Detector Computed Tomography Coronary Angiography to Diagnose Coronary Artery Disease in Emergency Depart...

Permanent Link: http://ufdc.ufl.edu/UFE0042975/00001

Material Information

Title: The Use of 320 Detector Computed Tomography Coronary Angiography to Diagnose Coronary Artery Disease in Emergency Department Patients with Chest Pain
Physical Description: 1 online resource (36 p.)
Language: english
Creator: WINCHESTER,DAVID E
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2011

Subjects

Subjects / Keywords: Clinical Investigation (IDP) -- Dissertations, Academic -- UF
Genre: Medical Sciences thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Chest pain is a common problem with over 7 million emergency department (ED) visits in the U.S. annually. ED physicians are charged with establishing the absence of potentially serious conditions and with accurately diagnosing the source of chest pain without unduly burdening the patient with an extended duration of stay or unnecessary admission to the hospital. Two crucial diagnoses in the cardiac differential diagnosis of chest pain include acute coronary syndrome (ACS) and obstructive coronary artery disease (CAD). The likelihood of ACS can be minimized with normal findings using a thorough history and physical examination, serial measurements of cardiac serum biomarkers, and serial electrocardiograms. Typically, however, the diagnosis of obstructive CAD requires additional testing. This testing might include electrocardiographic treadmill testing (ETT), myocardial perfusion imaging (MPI), or stress echocardiography and frequently these tests are not available in an ED setting. A newer technology, computed tomography coronary angiography (CTCA), has sensitivity and specificity for CAD superior to ETT and similar to MPI for establishing the diagnosis of CAD. CTCA can be reliably performed on a 64-detector computed tomography (CT) scanner which is a tool available in most EDs throughout the day and on every day of the week. At the University of Florida, the ED faculty was concerned about poor follow-up for patients discharged after chest pain evaluation. To address this, the ED recently switched from a strategy of ordering outpatient stress tests for patients with chest pain, to ordering CTCA in the ED and prior to discharge for these patients. We hypothesized that this change in strategy would reduce the ED duration of stay and increase the detection of CAD. Using two cohorts of patients (n = 50 in each, total n = 100) we compared the duration of stay in the ED and the detection of CAD in patients before and after this change in clinical care to determine the impact of CTCA. The duration of stay was not significantly different between the cohorts (417.5 minutes for the CT cohort, 400.0 for the control cohort, p = 0.53). Substantially more patients in the CT cohort completed the test ordered for them (96% versus 36% for control cohort, p < 0.0001) resulting in more patients being diagnosed with CAD (28% versus 2% in control cohort, p = 0.0004). More patients in the CT cohort were diagnosed with obstructive CAD, (12% versus 2%, p = 0.11) although this difference was not statistically significant. Within 3 months of the index ED visit, recidivism was the same in both cohorts (n = 4, 8%) and no patients in either cohort suffered myocardial infarction (MI) or death. In conclusion, for patients who present to the ED with chest pain who need additional testing for CAD, a strategy of using CTCA prior to ED discharge is more effective than a strategy of outpatient follow-up testing. The CTCA based strategy detected more CAD, primarily due to low likelihood of follow-up in the stress testing cohort. Using CTCA did not significantly change the duration of stay in the ED or reduce ED recidivism. No patients suffered MI or death within 3 months of their ED visit.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by DAVID E WINCHESTER.
Thesis: Thesis (M.S.)--University of Florida, 2011.
Local: Adviser: Limacher, Marian C.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2011-10-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2011
System ID: UFE0042975:00001

Permanent Link: http://ufdc.ufl.edu/UFE0042975/00001

Material Information

Title: The Use of 320 Detector Computed Tomography Coronary Angiography to Diagnose Coronary Artery Disease in Emergency Department Patients with Chest Pain
Physical Description: 1 online resource (36 p.)
Language: english
Creator: WINCHESTER,DAVID E
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2011

Subjects

Subjects / Keywords: Clinical Investigation (IDP) -- Dissertations, Academic -- UF
Genre: Medical Sciences thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Chest pain is a common problem with over 7 million emergency department (ED) visits in the U.S. annually. ED physicians are charged with establishing the absence of potentially serious conditions and with accurately diagnosing the source of chest pain without unduly burdening the patient with an extended duration of stay or unnecessary admission to the hospital. Two crucial diagnoses in the cardiac differential diagnosis of chest pain include acute coronary syndrome (ACS) and obstructive coronary artery disease (CAD). The likelihood of ACS can be minimized with normal findings using a thorough history and physical examination, serial measurements of cardiac serum biomarkers, and serial electrocardiograms. Typically, however, the diagnosis of obstructive CAD requires additional testing. This testing might include electrocardiographic treadmill testing (ETT), myocardial perfusion imaging (MPI), or stress echocardiography and frequently these tests are not available in an ED setting. A newer technology, computed tomography coronary angiography (CTCA), has sensitivity and specificity for CAD superior to ETT and similar to MPI for establishing the diagnosis of CAD. CTCA can be reliably performed on a 64-detector computed tomography (CT) scanner which is a tool available in most EDs throughout the day and on every day of the week. At the University of Florida, the ED faculty was concerned about poor follow-up for patients discharged after chest pain evaluation. To address this, the ED recently switched from a strategy of ordering outpatient stress tests for patients with chest pain, to ordering CTCA in the ED and prior to discharge for these patients. We hypothesized that this change in strategy would reduce the ED duration of stay and increase the detection of CAD. Using two cohorts of patients (n = 50 in each, total n = 100) we compared the duration of stay in the ED and the detection of CAD in patients before and after this change in clinical care to determine the impact of CTCA. The duration of stay was not significantly different between the cohorts (417.5 minutes for the CT cohort, 400.0 for the control cohort, p = 0.53). Substantially more patients in the CT cohort completed the test ordered for them (96% versus 36% for control cohort, p < 0.0001) resulting in more patients being diagnosed with CAD (28% versus 2% in control cohort, p = 0.0004). More patients in the CT cohort were diagnosed with obstructive CAD, (12% versus 2%, p = 0.11) although this difference was not statistically significant. Within 3 months of the index ED visit, recidivism was the same in both cohorts (n = 4, 8%) and no patients in either cohort suffered myocardial infarction (MI) or death. In conclusion, for patients who present to the ED with chest pain who need additional testing for CAD, a strategy of using CTCA prior to ED discharge is more effective than a strategy of outpatient follow-up testing. The CTCA based strategy detected more CAD, primarily due to low likelihood of follow-up in the stress testing cohort. Using CTCA did not significantly change the duration of stay in the ED or reduce ED recidivism. No patients suffered MI or death within 3 months of their ED visit.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by DAVID E WINCHESTER.
Thesis: Thesis (M.S.)--University of Florida, 2011.
Local: Adviser: Limacher, Marian C.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2011-10-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2011
System ID: UFE0042975:00001


This item has the following downloads:


Full Text

PAGE 1

1 THE USE OF 320 DETECTOR COMPUTED TOMOGRAPHY CORONARY ANGIOGRAPHY TO DIAGNOSE CORONARY ARTERY DISEASE IN EMERGENCY DEPARTMENT PATIENTS WITH CHEST PAIN By DAVID E. WINCHESTER A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNI VERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2011

PAGE 2

2 2011 David E. Winchester

PAGE 3

3 To Mom and Dad, for their love and support

PAGE 4

4 ACKNOWLEDGMENTS My achievements would not have been possible without the loving support of my mother, father, and especially my wife Erin, who is my advocate, mentor, and best friend. I appreciate the time and resources provided for me by the Division of Cardiovascular Medicine to seek this Master of Science degree. Further, I would like to extend my gratitude and thanks to my many mentors and colleagues for this and other research endeavors including Dr. James Hill, Dr. Anthony Bavry, Dr. Carl Pepine, Dr. Steven Kraft, Dr. Marian Limacher, Dr. Nabih Asal, Dr. David Wymer, Dr. Preeti Jois, Dr. John Petersen, Dr. Rhonda Cooper DeHoff, Dr. Eileen Handberg, Dr. William Brearley, and Dr. Ki Park.

PAGE 5

5 TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................. 4 LIST OF TABLES ............................................................................................................ 6 LIST OF FIGURES .......................................................................................................... 7 LIST OF ABBREVIATIONS ............................................................................................. 8 ABSTRACT ..................................................................................................................... 9 CHAPTER 1 INTRODUCTION .................................................................................................... 12 2 METHODS .............................................................................................................. 16 Study Design and Setting ....................................................................................... 16 Patient Selection ..................................................................................................... 16 Data Collection ....................................................................................................... 17 Outcomes ............................................................................................................... 17 CTCA Acquisition .................................................................................................... 18 Statistical Methods and Data Analysis .................................................................... 19 3 RESULTS ............................................................................................................... 21 Baseline Characteristics ......................................................................................... 21 Duration of Stay ...................................................................................................... 21 Detection of CAD and Clinical Outcomes ............................................................... 22 4 DISCUSSION AND CONCLUSIONS ...................................................................... 28 Discussion .............................................................................................................. 28 Conclusions ............................................................................................................ 32 LIST OF REFERENCES ............................................................................................... 33 BIOGRAPHICAL SKETCH ............................................................................................ 36

PAGE 6

6 LIST OF TABLES Table page 3 1 Baseline Characteristics ..................................................................................... 25 3 2 Outcomes ........................................................................................................... 26 3 3 Recidivism Patients ............................................................................................ 27

PAGE 7

7 LIST OF FIGURES Figure page 2 1 Cohort Selection Process ................................................................................... 20 3 1 Emergency department duration of stay ............................................................. 23 3 2 Results of CTCA ................................................................................................. 24

PAGE 8

8 LIST OF ABBREVIATION S ACS acute coronary syndrome CA C coronary artery calcium CAD coronary artery disease CT computed tomography CTCA computed tomography coronary angiography CVD cardiovascular disease ED emergency department ETT exercise treadmill test HR heart rate IQR interquartile range MI myocardial in farction MPI myocardial perfusion imaging

PAGE 9

9 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science THE USE OF 320 DETECTOR COMPUTED TOM OGRAPHY CORONARY ANGIOGRAPHY TO DIAGNOSE CORONARY ARTERY DISEASE IN EMERGENCY DEPARTMENT PATIENTS WITH CHEST PAIN By David E. Winchester May 2011 Chair: Marian Limacher Major: Medical Sciences Clinical and Translational Science Chest pain is a common problem with over 7 million emergency department (ED) visits in the U. S annually. ED physicians are charged with establishing the absence of potentially serious conditions and with accurately diagnosing the source of chest pain without unduly burdening the patient with an extended duration of stay or unnecessary admission to the hospital. Two crucial diagnoses in the cardiac differential diagnosis of chest pain include acute coronary syndrome (ACS) and obstructive coronary artery disease (CAD). The likelih ood of ACS can be minimized with normal findings using a thorough history and physi cal examination, serial measurements of cardiac serum biomarkers, and serial electrocardiograms. Typically, however, the diagnosis of obstructive CAD requires additional tes ting. This testing might include electrocardiographic treadmill testing (ETT), myocardial perfusion imaging (MPI), or stress echocardiography and frequently these tests are not available in an ED setting. A newer technology, computed tomography coronary angiography (CTCA), has sensitivity and specificity for CAD superior to ETT and similar to MPI for establishing the

PAGE 10

10 diagnosis of CAD. CTCA can be reliably performed on a 64detector computed tomography ( CT ) scanner which is a tool available in most EDs thro ughout the day and on every day of the week. At the University of Florida the ED faculty was concerned about poor follow up for patients discharged after chest pain evaluation. To address this, the ED recently switched from a strategy of ordering outpatie nt stress tests for patients with chest pain, to ordering CTCA in the ED and prior to discharge for these patients. We hypothesized that this change in strategy would reduce the ED duration of stay and increase the detection of CAD. Using two cohorts of patients (n = 50 in each, total n = 100) we compared the duration of stay in the ED and the detection of CAD in patients before and after this change in clinical care to determine the impact of CTCA. The duration of stay was not significantly different betw een the cohorts (417.5 minutes for the CT cohort, 400.0 for the control cohort, p = 0.53). Substantially m ore patients in the CT cohort completed the test ordered for them (96% versus 36% for control cohort, p < 0.0001) resulting in more patients being diagnosed with CAD (28% versus 2% in control cohort, p = 0.0004). More patients in the CT cohort were diagnosed with obstructive CAD, (12% versus 2%, p = 0.11) although this difference was not statistically significant. Within 3 months of the index ED visit, recidivism was the same in both cohorts (n = 4, 8%) and no patients in either cohort suffered myocardial infarction (MI) or death. In conclusion, for patients who present to the ED with chest pain who need additional testing for CAD, a strategy of using C TCA prior to ED discharge is more effective than a strategy of outpatient follow up testing. The CTCA based strategy

PAGE 11

11 detected more CAD, primarily due to low likelihood of follow up in the stress testing cohort. Using CTCA did not significantly change the duration of stay in the ED or reduce ED recidivism. No patients suffered MI or death within 3 months of their ED visit.

PAGE 12

12 CHAPTER 1 INTRODUCTION Cardiovascular disease (CVD) is the leading cause of mortality in the United States for both men and women.1 The best estimate is that over 82 million Americans (over one in three) suffers from some form of CVD. Fortunately, the rate of death from CVD has decreased 27.8% from 1997 to 2007.2 Nearly half of this decrease has been attributed to increased use of evidenc e based medical therapies.3 An important technological component of evidence based medical therapies includes advanced techniques for diagnosing CVD. Several modalities of functional and anatomic testing for CVD are available for physicians to apply in patient care. Of course, no test is completely accurate and each method has unique limitations and levels of precision. One of the biggest challenges, therefore, lies in selecting the right test for the right patient at the right time, ideally based on the patients pretest likelihood of CVD.4 For example, in evaluating a patient who complains of chest pain, considering the pretest likelihood that the patient has CVD is helpful in selecting the optimal test. Young patients without significant CVD risk factors are unlikely to have CVD. Ordering a test with a low positive predictive value increases the chance of a false positive test, potentially subjecting the patient to un necessary testing. On the opposite end of the spectrum, older patients with many CVD ri sk factors are likely to have CVD. In these patients, a test with a low negative predictive value increases the chance of a false negative test, potentially delaying an accurate diagnosis of CVD. Patients with intermediate pretest likelihood of CVD are the most likely to receive valuable diagnostic information from noninvasive testing and are therefore the ideal population for these tests .5 7

PAGE 13

13 While the symptoms of CVD are legion, the best known to both physicians and the public is chest pain. Because this symptom is well known to be associated with CVD, patients frequently consider chest pain to be an emergency and seek medical attention in a nearby emergency department (ED). In fact, over 7 million ED visits annually result from a complaint of chest pain.8 While ED physicians are primarily responsible for identifying lifethreatening conditions they also find themselves in an increasing role as the front line interface between the public and the medical community. Therefore, they bear some responsibility t o help patients become established within the healthcare system and must also offer appropriate follow up. Making accurate diagnoses facilitates better follow up, and the diagnosis of CVD is important to make. Not only does CVD carry a high burden of morta lity, as previously discussed, but advances in evidence based medical therapies provide excellent potential to reduce the burden of morbidity and mortality associated with CVD. For patients with chest pain presenting to an ED, physicians are encumbered to establish the presence or absence of two important diagnoses. The first is an acute coronary syndrome (ACS). The second is obstructive coronary artery disease (CAD) resulting in angina pectoris. ACS, such as acute myocardial infarction or unstable angina, can be reliably ruled out using serial assessments of the electrocardiogram and cardiac biomarkers, such as serum troponin.9 D iagnosi ng obstructive CAD typically requires additional noninvasive testing, and such testing provides the best diagnostic yield in patients with intermediate pretest likelihood of CAD. ED physicians order tests and noninvasive imaging they consider to be best for the patient, however most imaging tests are only available during business hours and

PAGE 14

14 require travel to facilities outsi de the ED setting This reality requires that the ED physician discharge the patient with instructions to follow up at another time and location for further testing. This strategy frequently fails with up to half of patients not completing scheduled follow up testing.10 Failure to follow up could be due to financial constraints, misunderstandings leading patients to believe that they do not have a medical problem requiring testing, or other reasons. As opposed to other testing modalities, computed tomograp hy coronary angiography (CTCA) is a noninvasive test for CAD potentially available to ED physicians at any time of the day or night. CTCA is a recently adopted imaging modality that can be performed on most modern computed tomography (CT) scanners. The diagnostic accuracy of CTCA has been shown to be similar to other noninvasive imaging tests for CAD including stress echocardiography,11 single photon emission tomography,12 and rubidium based positron emission tomography.13 Prognostic information can be gl eaned from CTCA, and a normal exam is associated with an exceedingly low risk of future cardiovascular events with a 10year survival of 99.4% .14 This prognostic information can readily be obtained in the ED setting.15 Other research in the ED setting has demonstrated that CTCA can reduce duration of ED stay and reduce costs.16 In the past, ED physicians at the University of Florida typically evaluated chest pain by first ruling out ACS and then discharging patients for further CAD evaluation in the outpatient setting. Out of concern that few patients were completing follow up, this strategy was altered to incorporate CTCA during the ED visit as the primary strategy for diagnosing CAD in intermediate risk patients. We designed t his investigation to test th e hypothesis that a strategy of CAD testing based on CTCA would be superior to an

PAGE 15

15 outpatient follow up strategy as measured by the success rate for completion of CAD testing, by the percentage of patients diagnosed with CAD, and by the duration of ED stay

PAGE 16

16 CHAPTER 2 METHODS Study Design and Setting This investigation was conducted in the ED of a large tertiary care medical center. The design is a retrospective cohort study using a historical control group. Patients were considered for inclusion if they presented to the ED with a chief complaint of chest pain, or of other symptoms suggestive of CAD. Based on the patients history and clinical presentation, the attending ED physician was responsible for determining which patients were at low risk of ACS. Thes e patients underwent serial testing with ECGs and cardiac biomarkers. Once the diagnosis of ACS had been reliably excluded to the satisfaction of the attending ED physician, and further CAD testing was determined to be warranted, patients were nonrandomly assigned either to follow up outpatient stress testing or CTCA during their index ED visit as described below (Figure 2 1) Two cohorts were thus established, the CT cohort of patients tested for CAD by CTCA, and the control cohort of patients tested for C AD using outpatient follow up stress testing referral. The I nstitutional R eview B oard at the University of Florida approved this research protocol and waived the requirement to obtain consent for access to existing medical records. Patient Selection The ED routinely documented all patients referred for outpatient stress testing as a method of quality assurance. This quality assurance logbook was us ed to identify patients for the control cohort. On June 1, 2009, the ED began the routine use of CTCA for all c hest pain patients without ACS who needed further testing for CAD. After this date, all patients considered for CTCA were documented and the logbook was used to

PAGE 17

17 identify patients for the CT cohort. Patients in each cohort were identified sequentially and a ll patients were included, even if they failed to complete the assigned test ing methodology The first 50 patients documented after June 1, 2009 comprised the CT cohort and the last 50 prior to June 1, 2009 comprised the control cohort. Patients were exclu ded from the study in either cohort if they had any contraindications for CTCA including: acute or chronic kidney disease with glomerular filtration rate less than 60 mL/minute or allergy to iodinated contrast. Data Collection Patient information was collected regarding age, gender, height and weight, chief complaint, medical history, history of tobacco and recreational drug use, prescription medication use, ECGs, and laboratory tests. ED duration of stay was determined using the time of ED arrival and dis charge as documented in the medical record. In the control cohort, adherence to referral for follow up outpatient stress testing within 3 months of ED discharge was determined. Outcomes The primary aim of this study was to determine the effect of a CTCA based strategy on the duration of stay in the ED. S econdary outcomes included, the rate of detection of CAD the success of each strategy at completing testing, and recidivism (the rate of return ED visit for chest pain). Detection of CAD for the control co hort was defined as patients who both completed follow up testing as ordered and had a positive test for CAD. Detection of CAD in the CT cohort was defined as discovery of any coronary artery stenotic lesion. Patients with only coronary calcium and without stenosis were not included in the definition of CAD. Obstructive CAD was defined by the detection of any lesion of greater than or equal to 50% luminal stenosis. This definition

PAGE 18

18 was used to maximize the sensitivity for patients who would be suitable candi dates for further testing, including invasive angiography.17 Recidivism was defined as a return visit to the ED within 3 months with chest pain or symptoms suggestive of cardiac ischemia. As a safety outcome, we determined the rate of myocardial infarction (MI) or death within 3 months. CTCA Acquisition CTCA studies were acquired using the 320 detector Aquilion One CT Scanner (Toshiba, Nasu, Japan). Betablocker use was encouraged for all patients with a heart rate (HR) over 70 beats per minute; however us e was not required and was done at the discretion of the ED physician. A weight based protocol was used to determine the dose of iodinated contrast (VisipaqueTM [ iodixanol ] 60 90 mL ; Amersham Health, Princeton, NJ), tube current (400580 mA) and tube voltage (120135 kV). After coronary artery calcium (CAC) scoring was completed, contrast bolus tracking was used and the scan was triggered when contrast density in the descending aorta reached 180 Hounsfield units. Scans were performed with retrospective gati ng, prospective gating, or dose modulation based on patient suitability. CTCA studies were reconstructed at 70%, 75%, and 80% of the R R interval with additional reconstructions performed if necessary and interpreted using a Vitrea workstation (Vital Imag es, Minn esota ) All studies were read in a preliminary fashion by r adiology housestaff with r adiology faculty available for oversight. Within 12 hours of any study, final interpretation was provided by both cardiology and r adiology faculty who are board ce rtified in cardiovascular CT. Results were communicated to ED faculty immediately upon reading. Abnormal findings were communicated to the patient by the responsible ED faculty. All stenoses were classified

PAGE 19

19 as < 50%, 5075%, or > 75% stenotic by the consensus of the interpreting facu lty physicians, some of whom were investigators in this study. Statistical Methods and Data Analysis Using an estimated duration of stay of 480 minutes in the ED we considered a reduction or increase in length of stay by 60 minutes would be clinically relevant. We set a beta level of 0.8 and determined that a sample size of 50 patients would be adequate to detect a 60 minute change in the duration of stay. We selected two time frames for secondary analysis of our duration of stay data. First we examined duration of stay if the patient arrived during peak ancillary staff availability (8 AM to 5 PM) or not (5 PM to 8 AM). Second, we examined duration of stay if the patient arrived during peak ED patient volume (4 PM to 12 AM) or not (12 AM to 4 PM). Power calculations were performed using G Power 3.1.18 Continuous variables were compared using the S tudents t test and Wilcoxon rank sum test as appropriate for normal and skewed distributions. Categorical data were compared by Fisher s exact test and chi square as appropriate. Calculations were completed using MyStat version 12 (Systat Software; Chicago, IL) We defined a p value < 0.05 to be statistically significant.

PAGE 20

20 Figure 21 Cohort Selection Process ACS = acute coronary s yndrome, CAD = coronary artery disease, CT = computed tomography, ECG = electrocardiogram, ED = emergency department, MI = myocardial infarction

PAGE 21

21 CHAPTER 3 RESULTS Baseline Characteristics The mean age of patients in the CT cohort was 47.0 years compared t o 41.3 in the control group (p = 0.009). Male patients comprised 50% of the CT cohort versus 44% of controls (p = 0.55) Patients in the two cohorts did not have any significant differences in their mean body mass index, medication use, medical history, or social history (Table 31) Family history of CAD was inconsistently recorded and therefore excluded from the investigation. Median duration of chest pain prior to presentation was 12 hours or less for both cohorts (p = 0.35) Duration of Stay The m edian duration of stay in the ED was 417.5 minutes (359.0 581.0 interquartile range [IQR]) for the CT cohort and 400.0 minutes (338.0 471.0 IQR) for the control cohort (p = 0.53) (Figure 31, Table 32) When patients arrived during peak ancillary staff avai lability (8 AM to 5 PM), duration of stay was 384.0 minutes versus 382.0 minutes (p = 0.72), while arrival from 5 PM to 8 AM duration of stay was 453.0 minutes versus 432.0 minutes (p = 0.49). When patients arrived during peak ED patient volume (4 PM to 12 AM), duration of stay was 551 .0 minutes versus 421 .0 minutes (p = 0.07), while arrival from 12 AM to 4 PM duration of stay was 393.5 versus 393.0 ) (p = 0.93). Fewer patients in the CT cohort (n = 35, 70%) had three sets of cardiac biomarkers checked during the ED visit as compared to the control cohort (n = 47, 94%).

PAGE 22

22 Detection of CAD and Clinical Outcomes In the control cohort, only 18 patients (36%) completed outpatient stress testing while all but two patients in the CT cohort completed CTCA (96%, p < 0. 0001) (Table 32) One patient assigned to the CT cohort was not scanned due to inability to establish IV access and the second patient was unable to be scanned due to a scanner malfunction. Neither of these patients (a 39 year old woman and a 58 year old man) underwent further CAD testing over the following 3 months. Of the 48 patients from the CT cohort who successfully completed CTCA, 31 had CAC scores of zero, with median CAC for the cohort of zero. CTCA for three patients was not evaluable due to inco rrect bolus timing ( n = 2) and arrhythmia ( n = 1), however all three patients had CAC of zero. Of 42 patients with data available for HR, the median was 53.5 beats per minute. Radiation dose data were not available in the radiology reports. CAD (defined as the presence of a stenotic lesion) was detected in 14 CT cohort patients compared to 1 patient in the control cohort (p = 0.0004). Obstructive CAD was detected in 6 CT cohort patients compared to 1 control patient (p = 0.11) (Figure 3 2) During three months of follow up, 4 patients in each cohort sought repeat evaluation in the ED (p > 0.99) (Table 33) No patients suffered death or MI during the subsequent three months.

PAGE 23

23 Figure 31 Emergency department duration of stay This figure is a box and whisker plot of the distribution of duration of stay for each patient. The central vertical line represents the median duration of stay while the values within one standard deviation (SD) of the median are included in the boxes. Values inside the whisker s are within two SDs of the median. Asterisks represent values within 3 SDs of the median and circles are values beyond 3 SDs CT = computed tomography, mins = minutes .

PAGE 24

24 Figure 32 Results of CTCA This pie chart demonstrates the distribution of fi ndings on CTCA with the largest proportion (56%) of patients having a normal exam Patients with only coronary calcium and without any stenotic lesions are denoted in this chart as CAC. CAC = coronary artery calcium, NonDx = nondiagnostic .

PAGE 25

25 Table 31 Base line Characteristics CT Cohort Control Cohort p value n=50 n=50 Age, yrs (SD) 47.0 (10.7) 41.3 (10.5) 0.009 BMI, kg/m 2 (SD) 31.5 (7.6) 31.6 (11.2) 0.94 Pulse, bpm (SD) 79 (11) 87 (16) 0.007 Creatinine, mg/dL (SD) 0.85 (0.2) 0.9 (0.6) 0.59 Ma le, n (%) 25 (50) 22 (44) 0.55 Diabetes Mellitus 6 (12) 6 (12) > 0.99 Current Smoker 14 (28) 18 (36) 0.39 Former Smoker 2 (4) 0 (0) 0.50 Hypertension 20 (40) 19 (38) 0.84 Hyperlipidemia 9 (18) 6 (12) 0.40 Anxiety 11 (22) 11 (22) > 0.99 Acute Cocaine Use 3 (6) 2 (4) > 0.99 Days of CP, median* 0.5 0 0.35 Medications on presentation Aspirin 9 (18) 4 (8) 0.24 RAS i nhibitor 6 (12) 8 (16) 0.56 Beta blocker 9 (18) 2 (4) 0.06 Statin 3 (6) 3 (6) > 0.99 BMI = body mass index, bpm = beats per min ute, CP = chest pain, CT = computed tomography, dL = deciliter, kg = kilogram, mg = milligram, m2 = meter squared, RAS = renin/angiotensin system, SD = standard deviation, yrs = years *Median duration of chest pain prior to admission. Chest pain that star ted on the date of admission was coded as zero days.

PAGE 26

26 Table 32 Outcomes CT Cohort Control Cohort p value n=50 n=50 Duration of stay (minutes), median (IQR) 417.5 (359 .0 581 .0 ) 400 .0 (338 .0 471 .0 ) 0.53 Subgroup Analysis Arrival between 5p 8a n=23 n=25 0.49 453 .0 (388 .0 678. 8 ) 432 .0 (366.5 546.5) Arrival between 8a 5p n=27 n=25 0.72 384 .0 (323. 3 542 .0 ) 382 .0 (334.5 426.5) Arrival between 4p 12a n=12 n=21 0.07 551 .0 (422 .0 712 .0 ) 421 .0 (366.5 486.5) Arrival between 12a 4p n=38 n= 29 0.93 393.5 (320 .0 545 .0 ) 393 .0 (337. 3 452.5) Additional ED outcomes 3rd troponin checked 35 (70%) 47 (94%) 0.003 3rd ECG checked 30 (60%) 47 (94%) < 0.0001 3 month follow up outcomes Completed noninvasive testing 48 (96%) 18 (36 %) < 0.0001 Any CAD Diagnosed 14 (28%) 1 (2%) 0.0004 Obstructive CAD (>50% stenosis) 6 (12%) 1 (2%) 0.11 Return ED visit 4 (8%) 4 (8%) > 0.99 CAD = coronary artery disease, CT = computed tomography, ECG = electrocardiogram, ED = emergency department, IQR = interquartile range

PAGE 27

27 Table 33. Reci d i v ism Patients Age Gender DM HTN Tobacco Anxiety CT Cohort Patient #9 60 M Yes Yes No No Patient #34 43 F No Yes Yes No Patient #44 43 F No No No No Patient #45 51 F No Yes No Yes Control Coh ort Patient #19 42 F No Yes Yes No Patient #31 58 F No Yes Yes Yes Patient #34 56 M No Yes Yes No Patient #40 21 F No No Yes No CT = computed tomography, DM = diabetes mellitus, F = female, HTN = hypertension, M = male

PAGE 28

28 CHAPTER 4 DISCUSSION AND CONCLUSIONS Discussion Testing for CAD using a CTCA based strategy for ED patients with chest pain was more effective than a strategy of outpatient stress testing. As compared to outpatient stress testing, a CTCA based strategy had no significant effect on ED duration of stay and detected a greater number of patients with both nonobstructive and obstructive CAD. No patients in either cohort suffered MI or death and the same number in each cohort returned to the ED for evaluation of chest pain during 3 months of follow up. Our investigation has demonstrated that for ED patients with chest pain and without ACS who warrant further testing for CAD, a CTCA based strategy detected both nonobstructive and obstructive CAD in more patients as compared with a strat egy of outpatient stress testing. Prior studies have documented this phenomenon in stable outpatients.19, 20 We recognize that several factors could contribute to these differences including the greater ability of CTCA to diagnose nonobstructive CAD, low f ollow up rates in the control cohort, and the nonrandomized design of our investigation. Because CTCA can detect nonobstructive lesions while ETT, MPI, and stress echocardiography detect myocardial ischemia, greater detection of nonobstructive CAD is an expected finding. A CTCA based strategy, therefore, is an opportunity to provide unique and robust prognostic information. For patients without CAD, the prognostic value of a zero calcium score has been well established and is a valuable tool in reassuring patients about their risk of cardiovascular events.14, 21 Three patients had nondiagnostic CTCA studies, however their CAC scores were zero and therefore they

PAGE 29

29 could still be reassured of low cardiovascular risk. Patients with nonobstructive CAD can be reas sured of a similarly low cardiovascular event risk over the next 12 months .22 These two groups accounted for 84% of the patients in our CT cohort. When patients are diagnosed with CAD, that knowledge provides physicians an opportunity to intervene and potentially reduce the burden of cardiovascular events. Further study is needed to establish if earlier diagnosis could alter future clinical outcomes.23 In addition, future studies should address new strategies to effectively communicate low risk results to p atients to reduce return visits to the ED for the same complaints The increased detection of CAD in the CT cohort is also expected given the low rate of follow up observed in the control cohort Failure to follow up has been linked to many factors,2426 some of which can be overcome by completing testing prior to ED discharge. Because our investigation is a comparison of patient care strategies, the low follow up rate reinforces the limitations of delayed outpatient stress testing as a patient care strat egy. Because CTCA can be reliably performed on a CT scanner with at least 64 detectors,27 the strategy we have described could be used at many EDs. Few hospitals have 24 hour, immediate reading of CTCA studies, but we have demonstrated that a strategy of r outine CTCA with prompt preliminary reading is safe. Because our diagnostic strategy was not conducted by randomized assignment, the true prevalence of CAD may not be similar between the cohorts. I f we assume, however, that the CT cohort is an accurate re flection of CAD prevalence, the disparity in coronary findings compared to the control cohort is worrisome. Despite the fact that the same population was used to construct the CT and control cohorts, the routine use of CTCA detected obstructive CAD in 12% of patients as compared to 2% detected by

PAGE 30

30 outpatient follow up testing in the control cohort. This observation suggests that patients with obstructive CAD may go undiagnosed when delayed outpatient stress testing is employed. Prior reports have documented a similar magnitude of missed diagnoses.28 The rapid adoption of new CT imaging techniques and the theoretical risks associated with medical radiation has raised appropriate concerns.29 We share concerns about the potential overuse of diagnostic imaging s tudies ; however all patients in our study were determined to warrant further CAD testing based on the judgment of the treating physician. Previous work documents that CTCA is more sensitive and specific at detecting CAD tha n ETT and a direct comparison of the se two test ing modalities may not be a fair comparison. W e have endeavored, however, to compare two strategies: immediate CTCA versus delayed stress testing. While outpatient stress testing is commonly used by EDs, we have demonstrated that this strate gy is not only incapable of detecting nonobstructive CAD, but may frequently fail to detect obstructive CAD. We observed no significant change in duration of stay in the ED. Because many forces affect the duration of stay, our investigation may not have altered clinical care enough to detect a difference. In the CT cohort, ED physicians less frequently ordered three sets of cardiac biomarkers. This suggests that they found the CTCA clinically useful in accelerating decisions about disposition and therefore CTCA has potential to reduce ED duration of stay. Mixed results have been found with prior investigations on how CTCA affects the duration of stay.16, 30 Because our investigation was conducted using the first 50 patients in the ED evaluated using a CTCA strategy, the test may not have been optimally used by technologists and physicians. The duration of stay in the

PAGE 31

31 CT cohort was nonsignificantly higher than the control cohort, and waiting for a CTCA scan and the results could be causing an increase that this investigation was not powered to detect. We could not account for the time savings garnered by avoiding outpatient stress testing and this could potentially confer benefit in a formal cost benefit analysis. Based on 3 months of follow up data, a CTCA based strategy appears to be safe, given a cardiovascular event rate of 0%. Prior studies on CTCA have described similar event rates with both short and long term follow up.3133 We suspect that the low event rate is likely related to the purposeful select ion of patients with low to intermediate pretest likelihood of cardiovascular events. Our analysis was not powered to detect a difference in recidivism, however we observed 4 patients in each cohort return to the ED with chest pain within 3 months. Further study will be necessary to determine if comprehensive evaluation of chest pain with CTCA is reassuring enough to convince patients to not return to the ED with similar chest pain, but instead pursue less costly care for their chest discomfort. Our study h as several limitations. As a retrospective cohort study, our study does not have the benefit s of a randomized trial which would have minimized differences between the two patient populations, yet f ew differences were observed in the baseline characteristic s. The difference in pulse may be related to the nearly significant difference in baseline beta blocker use. Age difference may reflect the nonrandom selection of patients with the ED staff ordering tests on older patients they considered to be at higher r isk of CAD and could lead to a higher prevalence of CAD in the CT cohort. Our study is limited by the fact that we only reviewed records for our own institution.

PAGE 32

32 Conclusions For symptomatic ED patients who warrant noninvasive testing for CAD, a strategy of immediate CTCA is superior to delayed outpatient stress testing for detecting CAD. A delayed outpatient stress testing strategy may fail to diagnose obstructive CAD and such a strategy is limited by low follow up rates A CTCA based strategy does not sign ificantly affect on the ED duration of stay. Patients with chest pain and no evidence of ACS can safely be discharged with an expectation of low cardiovascular event risk in the ensuing 3 months.

PAGE 33

33 LIST OF REFERENCES 1. Roger VL, Go AS, LloydJones DM, et al Heart Disease and Stroke Statistics -2011 Update: A Report From the American Heart Association. Circulation. 2011;123:e18e209 2. Xu J, Kochanek KD, Murphy S, TejadaVera B. Deaths: Final Data for 2007. Natl Vital Stat Rep. 2010;58:1 135. 3. Ford ES, Aj ani UA, Croft JB, et al. Explaining the decrease in U.S. deaths from coronary disease, 19802000. N Engl J Med. 2007;356:23882398. 4. Diamond GA, Forrester JS. Analysis of probability as an aid in the clinical diagnosis of coronary artery disease. N Engl J Med. 1979;300:1350 1358. 5. Taylor AJ, Cerqueira M, Hodgson JM, et al. ACCF/SCCT/ACR/AHA/ASE/ASNC/NASCI/SCAI/SCMR 2010 Appropriate Use Criteria for Cardiac Computed Tomography. J Am Coll Cardiol. 2010;56:18641894. 6. Douglas PS, Khandheria B, Stainback RF, et al. ACCF/ASE/ACEP/AHA/ASNC/SCAI/SCCT/SCMR 2008 Appropriateness Criteria for Stress Echocardiography. Catheter Cardiovasc Interv 2008;71:E1 19. 7. Hendel RC, Berman DS, Di Carli MF, et al. ACCF/ASNC/ACR/AHA/ASE/SCCT/SCMR/SNM 2009 Appropriate Use Criteria for Cardiac Radionuclide Imaging. Circulation. 2009;119:e561587. 8. Nawar EW, Niska RW, Xu J. National Hospital Ambulatory Medical Care Survey: 2005 emergency department summary. Advance Data. 2007;386:132. 9. Farkouh ME, Aneja A, Reeder GS, et al. Clinical risk stratification in the emergency department predicts long term cardiovascular outcomes in a populationbased cohort presenting with acute chest pain: primary results of the Olmsted county chest pain study. Medicine. 2009;88:307313. 10. Richa rds D, Meshkat N, Chu J, Eva K, Worster A. Emergency department patient compliance with follow up for outpatient exercise stress testing: a randomized controlled trial. CJEM. 2007;9:435440. 11. Nixdorff U, Kufner C, Achenbach S, et al. Headto head compar ison of dobutamine stress echocardiography and cardiac computed tomography for the detection of significant coronary artery disease. Cardiology. 2008;110:8186. 12. Budoff MJ, Rasouli ML, Shavelle DM, et al. Cardiac CT angiography (CTA) and nuclear myocardial perfusion imaging (MPI) a comparison in detecting significant coronary artery disease. Academic Radiology. 2007;14:252257.

PAGE 34

34 13. Chow BJ, Dennie C, Hoffmann U, et al. Comparison of computed tomographic angiography versus rubidium 82 positron emission to mography for the detection of patients with anatomical coronary artery disease. Can J Cardiol 2007;23:801807. 14. Budoff MJ, Shaw LJ, Liu ST, et al. Long term prognosis associated with coronary calcification: observations from a registry of 25,253 patien ts. J Am Coll Cardiol. 2007;49:18601870. 15. Gallagher MJ, Ross MA, Raff GL, Goldstein JA, O'Neill WW, O'Neil B. The diagnostic accuracy of 64slice computed tomography coronary angiography compared with stress nuclear imaging in emergency department low risk chest pain patients. Ann Emerg Med. 2007;49:125136. 16. Goldstein JA, Gallagher MJ, O'Neill WW, Ross MA, O'Neil BJ, Raff GL. A randomized controlled trial of multi slice coronary computed tomography for evaluation of acute chest pain. J Am Coll Cardiol. 2007;49:863871. 17. Meijboom WB, Meijs MF, Schuijf JD, et al. Diagnostic accuracy of 64 slice computed tomography coronary angiography: a prospective, multicenter, multivendor study. J Am Coll Cardiol. 2008;52:21352144. 18. Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39:175191. 19. Ovrehus KA, Jensen JK, Mickley HF, et al. Comparison of usefulness of exercise testing vers us coronary computed tomographic angiography for evaluation of patients suspected of having coronary artery disease. Am J Cardiol. 2010;105:773779. 20. Weustink AC, Mollet NR, Neefjes LA, et al. Diagnostic accuracy and clinical utility of noninvasive test ing for coronary artery disease. Ann Intern Med. 2010;152:630639. 21. Nabi F, Chang SM, Pratt CM, et al. Coronary Artery Calcium Scoring in the Emergency Department: Identifying Which Patients With Chest Pain Can Be Safely Discharged Home. Ann Emerg Med. 2010;56:2209. 22. Hollander JE, Chang AM, Shofer FS, et al. Oneyear outcomes following coronary computerized tomographic angiography for evaluation of emergency department patients with potential acute coronary syndrome. Acad E merg M ed. 2009;16:693698 23. Arad Y, Spadaro LA, Roth M, Newstein D, Guerci AD. Treatment of asymptomatic adults with elevated coronary calcium scores with atorvastatin, vitamin C, and vitamin E: the St. Francis Heart Study randomized clinical trial. J Am Coll Cardiol. 2005;46:1 66172.

PAGE 35

35 24. Engel KG, Heisler M, Smith DM, Robinson CH, Forman JH, Ubel PA. Patient comprehension of emergency department care and instructions: are patients aware of when they do not understand? Ann Emerg Med. 2009;53:454461 25. Wang NE, Gisondi MA, Gol zari M, van der Vlugt TM, Tuuli M. Socioeconomic disparities are negatively associated with pediatric emergency department aftercare compliance. Acad Emerg Med. 2003;10:12781284. 26. Clarke C, Friedman SM, Shi K, Arenovich A, Culligan C. Emergency departm ent discharge instructions comprehension and compliance study. CJEM. 2005;7:511. 27. Rubinshtein R, Halon DA, Gaspar T, et al. Usefulness of 64slice cardiac computed tomographic angiography for diagnosing acute coronary syndromes and predicting clinical outcome in emergency department patients with chest pain of uncertain origin. Circulation. 2007;115:17621768. 28. Madsen T, Mallin M, Bledsoe J, et al. Utility of the emergency department observation unit in ensuring stress testing in low risk chest pain patients. Crit Pathw Cardiol. 2009;8:122124. 29. Einstein AJ, Henzlova MJ, Rajagopalan S. Estimating risk of cancer associated with radiation exposure from 64slice computed tomography coronary angiography. JAMA. 2007;298:317323. 30. Chang SA, Choi SI, C hoi EK, et al. Usefulness of 64slice multidetector computed tomography as an initial diagnostic approach in patients with acute chest pain. Am Heart J. 2008;156:375383. 31. Gopal A, Nasir K, Ahmadi N, et al. Cardiac computed tomographic angiography in an outpatient setting: an analysis of clinical outcomes over a 40month period. J Cardiovasc Comput Tomogr 2009;3:9095. 32. Beigel R, Oieru D, Goitein O, et al. Usefulness of routine use of multidetector coronary computed tomography in the "fast track" evaluation of patients with acute chest pain. Am J Cardiol. 2009;103:1481 1486. 33. Laudon DA, Behrenbeck TR, Wood CM, et al. Computed tomographic coronary artery calcium assessment for evaluating chest pain in the emergency department: long term outcome of a prospective blind study. Mayo Clin Proc. 2010;85:314322.

PAGE 36

36 BIOGRAPHICAL SKETCH David E. Winchester is a physician originally from Tallahassee, FL. He holds a B achelor of S cience in m icrobiology and a B achelor of A rts in s ociology both from the Universi ty of Florida. He completed his medical degree at the University of South Florida and training in internal medicine at the University of Virginia. Work on the M aster of S cience degree was completed concurrent with fellowship training in cardiovascular m edi cine