[n1]These numbers seem   reversed: SOL mean should be 14.6minutes with a SD of 11.2 minutes. Does this change any of the a...
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Polysomnographic Variables Describing Comorbid Insomnia and Mild Obstructive Sleep Apnea in Military Personnel as Revealed by Cluster Analysis

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Polysomnographic Variables Describing Comorbid Insomnia and Mild Obstructive Sleep Apnea in Military Personnel as Revealed by Cluster Analysis

  1. 1. [n1]These numbers seem reversed: SOL mean should be 14.6minutes with a SD of 11.2 minutes. Does this change any of the analysis?Characteristics of Military Personnel Diagnosed with Mild OSA Polysomnographic Variables Describing Comorbid Insomnia and Mild Obstructive Sleep Apnea in Military Personnel as Revealed by Cluster Analysis CPT David Anderson MD; LTC Vincent Mysliwiec, MD; Panagiotis Matsangas, M.Sc; Marquisha Lee, Ph.D; LTC Nici Bothwell, MD; Tristin Baxter, AAS; Bernard Roth, MD Madigan Healthcare System, Tacoma WA Comorbid Insomnia and OSA Demographic Characteristics Diagnosis of Insomnia and Mild OSA Results Well recognized yet under appreciated clinical entity Comorbid Insomnia . Estimated prevalence is as high as 55% (1) Age 36.2(8.14) 195 patients with adequate data to assess for insomnia PSG variables: sleep onset latency (SOL), sleep efficiency (SE) Male,% (No.) 96.6(199) 11 with inadequate data and wakefulness after sleep onset (WASO) when abnormal are BMI in Kg/m2 30.3(3.66) 167 (81%) were positive 100 consistent with insomnia(2) Deployment Status% 85.4(176) PSG variables of interest Cohort Comorbid SOL ≥ 31 minutes: 18 (8.7%) 17 (10.2%) 95 WASO ≥ 31 minutes: 102 (49.5%) 92 (55.1%) Military Significance Epworth Sleepiness Scale 12.5(5.06) SE < 85%: 35 (17.0%) 32 (19.2%) Military personnel frequently report “sleep disturbances” Self Reported Home Sleep 5.36(1.7) 90 96% . Medical comorbidities Prevalence as high as 80% Sleep<5 hours, % (No.) 47(95) All patients with anxiety diagnosed with insomnia (37/37) Etiologies include: sleep disorders (OSA , insomnia), 85 Patients with comorbid insomnia/OSA, 2.49 (1.17-5.28) PTSD, mTBI, anxiety, depression and pain Medical Co-morbidity more likely to have anxiety Anxiety,% (No.) 18(37) Patients with insomnia and Mild OSA are more likely to be in 80 82% Hypothesis/Objectives Depression,% (No.) 21.95(45) Cluster 1 (1-sided Fischers exact test p = .009; Odds ratio = 5.27 There is a high prevalence of comorbid insomnia and mild OSA in PTSD,%(No.) 9.71(20) [1.20-23.1]) 75 military personnel. mTBI,%(no.) 14.6(30) Cluster 1 Cluster 3 1. Determine prevalence of comorbid insomnia and mild OSA 2. Identify PSG phenotypes of patients with comorbid insomnia Conclusion and Discussion and mild OSA vs. mild OSA alone by cluster analysis Mild OSA Clusters Comorbid insomnia and mild OSA are highly prevalent in the Active Duty population PSG variable Cluster 1 (n=52) Cluster 3 (n=150) Wilcoxon Rank Sum Test Cohen’s d Higher prevalence than civilian studies Methods Likely due to deployments/comorbid illnesses Retrospective cross-sectional cohort study Findings from a PSG can indicate the diagnosis of Insomnia even 206 PSGs and linked clinic notes were reviewed to obtain: M (SD) M (SD) in setting of mild OSA, these include: Biometric parameters of age, height, weight and BMI along Increased WASO (≥ 31 minutes) with gender and deployment history SOL n(%) 16.1 (14.5) 8.61 (10.8) X2(1)=15.6, p<0.001* 0.586 Decreased sleep efficiency (<85%) Self-reported sleep and Epworth Sleepiness Scale score REML (min) 140 (87.5) 96.2 (41.9) X2(1)=4.97, p=0.026* 0.639 PSG has a role in assessing insomnia Diagnoses of PTSD, mTBI , anxiety and depression Treatment of both OSA and Insomnia is indicated in military Medical co-morbidities TST (hrs) 6.28 (0.698) 7.53 (0.526) X2(1)=89.6, p<0.001* 2.02 personnel with comorbid disease Diagnosis of Insomnia SE n(%) 82.6 (5.82) 94.7 (2.82) X2(1)=112, p<0.001* 2.65 Continuous positive airway pressure and cognitive Medical records assessed to determine if they met ICSD-2 behavioral therapy are recommended criteria for insomnia %I 12.9 (6.14) 8.23 (3.77) X2(1)=25.4, p<0.001* 0.917 % II 40.2 (8.19) 49.6 (9.72) X2(1)=35.1, p<0.001* 1.05 Statistical Analysis %SWS 15.7 (7.54) 18.1 (8.16) X2(1)=3.02, p=0.082** 0.306 Cluster analysis, multivariate technique used in exploratory data analysis, implemented using K means method % REM 14.3 (5.44) 18.8 (5.05) X2(1)=27.8, p<0.001* 0.857 Utilized all PSG variables WASO n(%) 77.3 (27.7) 24.9 (13.5) X2(1)=103, p<0.001* 2.41 Resulted in 3 groups, 2 of which were clinically significant Comparison based on Wilcoxon Rank Sum Test and effect AR 24.9 (8.92) 18.6 (7.34) X2(1)=20.5, p<0.001* 0.771 size assessed by Cohen’s d AHI 8.67 (3.78) 8.30 (2.76) X2(1)=0.673, p>0.400 0.112 Abbreviations: ADSM – Active Duty Service Member ICSD – International Classification of Sleep OSA – Obstructive Sleep Apnea % desat 86.4 (3.87) 85.7 (4.39) X2(1)=1.22, p=0.269 0.169 AHI – Apnea Hypopnea Index CIO – Comorbid Insomnia and OSA Disorders BMIT – Body Mass Index SOL – Sleep Onset Latency PSG – Polysomnography References PTSD – Post Traumatic Stress Disorder REM – Rapid Eye Movement 1. Okun ML, Kravitz HM, Sowers MF, Moul DE, Buysse DJ, Hall M.. J Clin Sleep Med. 2009 Feb 15;5(1):41-51. TST – Total Sleep Time mTBI – Mild Traumatic Brain Injury 2. Al-Jawder SE, Bahammam AS. Sleep Breath. 2012 Jun;16(2):295-304. WASO – Wakefulness After Sleep Onset 3. Krakow B, Melendrez D, Ferreira E, Clark J, Warner TD, Sisley B, et al. Chest. 2001 Dec;120(6):1923-9. Disclaimer 4. Chung KF.. Respiration. 2005 Sep-Oct;72(5):460-5.  The opinions and assertions in this manuscript are those of the authors and do not necessarily represent those of the Department of the Army, Department of Defense, US Government, or the Center for 5. Krell SB, Kapur VK. Sleep Breath. 2005 Sep;9(3):104-10. Neuroscience and Regenerative Medicine.

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