Running head: ASSESSING KNEE PAIN AND SLEEP QUALITY 1 Assessing the Temporal Relationship of Clinical Knee Pain and Sleep Quality in Individuals with or at Risk for Knee Osteoarthritis Chase W. Mallory Bachelor of Health Science Primary Investigator: Dr. Roger Fillingim, Ph.D. Department of Community Dentistry, University of Florida Gainesville, FL
ASSESSING KNEE PAIN AND SLEEP QUALITY 2 Table of Contents 3 .. 4 AIMS AND 5 7 12 13 14
ASSESSING KNEE PAIN AND SLEEP QUALITY 3 Abstract While the current literatu re suggests a strong reciprocal relationship between sleep quality and osteoarthritic pain, the direction of the relationship is poorly understood or documented. The purpose of this study is to investigate the temporal relationship of clinical knee pain and sleep quality in individuals with or at risk for chronic knee osteoarthritis Sleep and pain data were analyzed from a sample of more than 150 participants older adults from the ages of 45 85 with or at risk for knee osteoarthritis that participated in the prospective cohort study tit led Understanding Pain and Limitations in Osteoarthritic Disease (UPLOAD II) at the University of Florida We hypothesized that individuals reporting days with increased pain would show significantly poorer sleep quality the day after the peak pain day (PP D) compared to before the PPD The results demonstrate decreased patient reported and objective sleep duration, decreased sleep efficiency and increased sleep onset latency in the day following the PPD compared to the day before the PPD. This conclusion su pports the hypothesis and reinforces that elevated pain drives decreased sleep qua lity. Key terms: osteoarthritis, temporal, peak pain day, actigraphy
ASSESSING KNEE PAIN AND SLEEP QUALITY 4 Introduction Osteoarthritis (OA) represents the leading cause of disability worldwide, while the knee is the most commonly affected joint ( Neogi, 2013 ) There are many biopsychosocial factors which influence osteoarthritic pain which varies considerably across people Among these contributing factors is sleep quality, as abundant evidence demonstrates a strong reciprocal relationship between sleep quality and osteoarthritic related pain (Finan, Goodin, & Smith, 2013) That is, the poorer the sleep quality of an individu al, the higher their average level of osteoarthritic pain. Similarly, the higher the level of osteoarthritic pain, the poorer their sleep outcomes tend to be However, the direction of this relationship and the mechanisms involved are currently poorly und erstood In other words, it is unclear if it is pain that directs poor sleep outcomes or vice versa. It is important to characterize the direction of this relationship in order to develop effective interventions to disrupt the pain sleep cycle. In order to better understand the temporality of clinical pain and sleep quality we collected data on pain and sleep using patient reported diaries and objectively assessed sleep parameters using actigraphy. Further stratifying this relationship, there are well documented ethnic differences in both clinical pain and sleep quality. Among individuals wi th knee OA, average daily pain interacts with race with African Am erican (AA) adult s report significantly greater pain compared to their Non Hispanic White (NHW) co unterparts ( Parm e lee, Cox, Descaro, Keefe, & Smith, 2017) ( Cruz Almeida et al., 2014) Likewise AA individuals compared to NHWs exhibit poorer sleep outcomes such as decreased sleep duration, lower sleep percentage, higher wake after sleep onset (WASO) and higher sleep fragmentation (Carnethon et al., 2016). Therefore, not
ASSESSING KNEE PAIN AND SLEEP QUALITY 5 only are sleep disturbances more common in older adults with knee pain, but this relationship is particularly apparent within AA cohorts (Petrov and Lichstein, 2016). Understanding the directional influence of sleep and osteoarthritic pain is particularly important for several reasons. First, OA is a common disabling condition among older adults with a rising prevalence. Second, poor sleep quality is correlated with osteoarthritic knee p ain Therefore understanding this relationship can aid in providing earlier and improved treatment interventions. Lastly, the prevalence of lower sleep quality and knee OA are greater and produce more adverse effects among AA compared to NHW. Consequently elucidating the relationship between sleep and pain can contribute to improving disparities among AA populations. Aims and Hypothesis The purpose of this study is to investigate the temporal relationship between clinical knee pain and sleep quality. We hypothesized that individuals reporting days with increased pain would show significantly poorer sleep quality the day after the PPD when compared to the sleep quality the day before the PPD. This hypothesis supports the claim that elevated pain drives dec reased sleep quality. Method To assess the temporal relationship of sleep and pain data were analyzed from a sample of more than 150 participants of community dwelling older adults from the ages of 45 85 with or at risk for knee OA that participated in the prospective cohort study titled Understanding Pain and Limitations in Osteoarthritic Disease (UPLOAD II) at the University of Florida In this study each p articipant s elf reported their average daily knee pain on a numerical
ASSESSING KNEE PAIN AND SLEEP QUALITY 6 scale from 0 (no pain) to 100 ( most intense pain imaginable ) for a period of 1 to 2 weeks in a daily sleep d i ary. Then each sleep diary was assessed for a peak pain day (PPD), or a day in which an individual reported substantially greater pain compared to the previous and ensuing d ays. Subsequently sleep quality w as evaluated on the day s prior and following the PPD. By understanding the quality of sleep prior to and after the peak pain day, inferences can be drawn regarding the temporal relationship of sleep and pain. For example, if sleep qua lity was high before the PPD which then significantly decreased after the PPD, then one could infer that pain drives sleep outcomes. However if sleep quality w as low prior to the PPD and then significantly higher after the PPD, then one could infer that it is poor sleep quality that drives pain. Furthermore, three separate and continuous days of consistent pain data was obtained from the same participants to serve as a within subject group co ntrol. The control days did not have a PPD but rather three days of similar pain ratings. It was hypothesized that sleep quality would not vary significantly across these controls day during which pain remained consistent. Sleep quality was measured from two data sources: the patient reported sleep diary and Philips Actiwatch Technology. The patient reported sleep diary utilized three variables to assess sleep quality on a nightly basis which consisted of sleep duration, sleep quality and sleep refreshment Sleep duration was measured in hours, based on participants reported sleep duration, while sleep quality and sleep refreshment were measured using a Li kert Scale quantified from 1 to 5 (with 5 representing the highest quality of sleep or feeling of
ASSESSING KNEE PAIN AND SLEEP QUALITY 7 refre shment after sleep). In addition, in order to obtain a more objective measure of sleep quality participants were asked to wear a Philips Actiwatch for at least one week. The Actigraphy Software used light and kinetic data to obtain several measures of sleep quality consisting of: sleep duration, sleep onset latency (SOL), wake after sleep onset (WASO ) and sleep efficiency ( as calculated by total sleep time/ [total rest + total sleep time] x 100 ) A means analysis and r epeated measures analysis of variance within subjects were used to assess the relationship of sleep quality before and after the PPD. Results Of the 150 participants of community dwelling older adults from the ages of 45 85 with or at risk for knee OA that participated the Understanding Pain and Limitations in Osteoarthritic Disease (UPLOAD II) study 42 partici pants demonstrated PPD s. Demographics (n = 42) 58.6 (7.7 ) Male (%) 40.4 Female (%) 59.5 AA (%) 42.8 NHW (%) 57.1 Table 1.1 The average pain level on PPD s was reported at 43.9 with additional pain rating s before and after the PPD reported at 26.3 and 25.9 respectively. The within group control illustrated consistent pain ratings of 23.0, 22.1 and 20.1 respectively
ASSESSING KNEE PAIN AND SLEEP QUALITY 8 Figure 1.1 Further stratifying the data, AA individuals were found to have higher levels of reported pain compared to their NHW counterparts. How ever, both groups demonstrated similar PPD trend s Figure 1.2 Sleep quality was assessed using a means analysis and within group repeated measures analysis of variance for both the patient reported sleep diaries and Actigraphy data. The first 0 10 20 30 40 50 1 2 3 Reported Pain Level Time Reported Pain versus Time PPD Series Within Group Control Before PPD PPD After PPD 0 10 20 30 40 50 60 70 1 2 3 Reported Pain Level Time Reported Pain versus Time AA NHW Before PPD PPD After PPD
ASSESSING KNEE PAIN AND SLEEP QUALITY 9 source of sleep quality data assessed was the patient reported sleep diaries using a repeated measures analysis of variance. As illustra ted in table 1.2, sleep duration, sleep quality and sleep refreshment are slightly, but not significantly, lower after versus before the PPD With a P value of 0.07 sleep duration demonstrates a trend which is not quite statistically significant, likely due to sample size. Sleep quality and refreshment however clearly do not demonstrate statistical significance. Moreover, a s originally hypothesized for the with in group control no changes in sleep quality across days emerged for any of the three measures of sleep quality when accounting for gender, age and race Test of Hypothesis within Subject Eff ects, Sleep Diary Before PPD After PPD P value Sleep Duration (mins) 420.6 398.4 0.07 Time*Race 0.06 Time*Gender 0.21 Time*Age 0.05 Sleep Quality Score 3.38 3.19 0.35 Time*Race 0.20 Time*Gender 0.94 Time*Age 0.28 Refreshment Score 3.33 3.15 0.47 Time*Race 0.52 Time*Gender 0.73 Time*Age 0.41 Table 1.2 Sleep quality measured using actigraphy showed similar pattern of results. As seen in table 1.3, almost all actigraphy based measures showed slightly, but not significantly, poorer corrobo rate with the sleep diary data to support the claim that pain drives sleep quality. However, WASO was
ASSESSING KNEE PAIN AND SLEEP QUALITY 10 greater on the before verses after the PPD, supporting to reverse trend. However this relati onship is insignificant with a p value of 0.39 In addition, for sleep duration and WASO t here was significant interaction with time and race with P values of 0.07 and 0.03 respectively. Test of Hy pothesis within Subject Effects, Actigraphy Before PPD After PPD P value Sleep Duration (mins) 4 31.3 (110.1 ) 399.9 (136.3 ) 0.19 Time*Race 0.07 Time*Gender 0.15 Time*Age 0.14 SOL (mins) 1 1.9 (13.3 ) 22.3 (23.8 ) 0.07 Time*Race 0.53 Time*Gender 0.27 Time*Age 0.40 Sleep Efficiency (%) 7 9.5 (13.68) 78.2 (13.1 ) 0.09 Time*Race 0.27 Time*Gender 0.50 Time*Age 0.81 WASO (mins) 5 8.3 (37.9 ) 48.3 (38.8) 0.39 Time*Race 0. 0 3 Time*Gender 0.6 8 Time*Age 0.2 6 Table 1.3
ASSESSING KNEE PAIN AND SLEEP QUALITY 11 Figure 1.3 Figure 1.4 360 370 380 390 400 410 420 430 440 450 Sleep Duration, Reported Sleep Duration, Actiwatch Duration (Minutes) Sleep Duration versus Time Period Before PPD After PPD 0 10 20 30 40 50 60 70 80 90 SOL WASO Sleep Efficiency (%) Duration (Minutes) Test of Hypothesis within Subject Effects Before PPD After PPD
ASSESSING KNEE PAIN AND SLEEP QUALITY 12 Discussion This study extends the existing understanding regarding the recipro cal nature of sleep and pain, by investigating the temporality of the relationship. Whereas early work aimed to establish whether pain and sleep were related, this study is concerned with how pain and sleep are related. The findings contribute further information to elucidate the relationship between pain and sleep in individuals with or at risk for knee OA. Specifically all measures of sleep analysis including patient reported dat a and a ctigraphy data, suggest that sleep q uality is higher the day before the PPD when compared to the day after the PPD. Moreover, several measures of sleep quality including sleep duration and WASO interacted with race ; h owever the sample size was too sample to further stratify sleep quality by race and obtain statistically significant results. The present investigation has several limitations worth noting. First, a sample size of 42 may not provi de significant power to draw statistically significant conclusions. If the sample size wer e increa sed, some of the observed trends may achieve statistical significance Second, the study population was largely composed of community dwelling adults with mild to moderate knee pain. A sample consisting of patients with other characteristics may yield different results. Third, a measure of pain and sleep quality over a thre e day period provides a limited scope of data. Future studies are needed to address the mechanisms linking chronic pain and sleep, with a long term goal of developing treatments improve management of chronic pain conditions.
ASSESSING KNEE PAIN AND SLEEP QUALITY 13 Acknowledgements First and foremost, I would like to thank my primary investigator Dr. Roger Fillingim, Ph.D. for his guidance and mentorship through out my undergraduate research experience at the Pain Research and Intervention Center of Excellence (PRICE) lab I am also grateful f or Josue Cardoso and his assistance in the data analysis phase of this project. Likewise, I would like to thank Ralisa Pop, Eric Weber and Burel Goodin for their support in the examination of actigraphy data.
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