ADVERTISEMENT

Upcoming Website Maintenance Notification

On Sunday October 20th, 2019 from 5:00 am cst to 8:00 am cst there will be approximately 3 hours of scheduled downtime while we make upgrades to our servers. During this time-window the JCSM website will be unavailable. Thank you for your patience.

gears

Issue Navigator

Volume 11 No. 12
Earn CME
Accepted Papers





Scientific Investigations

A Comparative Analysis of Sleep Disordered Breathing in Active Duty Service Members with and without Combat-Related Posttraumatic Stress Disorder

Vincent Mysliwiec, MD1; Panagiotis Matsangas, PhD2; Jessica Gill, PhD3; Tristin Baxter, AAS4; Brian O'Reilly, DO4; Jacob F. Collen, MD5; Bernard J. Roth, MD4
1121st General Hospital, Medical Specialties Clinic Unit #15281; 2Naval Postgraduate School, Department of Operations Research, Monterey, CA; 3National Institutes of Health National Institute of Nursing Research, Bethesda, MD; 4Madigan Army Medical Center, Tacoma, WA; 5Brooke Army Medical Center, JBSA FT Sam Houston, TX

ABSTRACT

Study Objectives:

Posttraumatic stress disorder (PTSD) and obstructive sleep apnea (OSA) are frequently co-occurring illnesses. The purpose of this study was to determine whether comorbid PTSD/OSA is associated with increased PTSD symptoms or decreased OSA severity compared to PTSD or OSA alone in recently deployed Active Duty Service Members (ADSM).

Methods:

Cross-sectional observational study of ADSM who returned from combat within 24 months. Participants underwent an attended diagnostic polysomnogram and were assessed for PTSD, depression, combat exposure severity, sleepiness, and sleep quality with validated clinical instruments.

Results:

Our study included 109 military personnel who returned from a combat deployment within 24 months with a mean age of 34.3 ± 8.23 and BMI of 30.8 ± 3.99. Twenty-four participants had PTSD/OSA, 68 had OSA, and 17 had PTSD. Mean PTSD Checklist- Military Version (PCL-M) scores were 62.0 ± 8.95, 60.5 ± 4.73, and 32.5 ± 8.95 in PTSD/OSA, PTSD, and OSA, respectively. The mean AHI was 16.9 ± 15.0, 18.9 ± 17.0, and 1.73 ± 1.3 for those with PTSD/OSA, OSA, and PTSD. PTSD symptoms and OSA severity in military personnel with comorbid PTSD/OSA were not significantly different from those with PTSD or OSA alone. On multivariate analysis, BMI was a significant predictor of OSA (OR, 1.21; 95% CI, 1.04–1.44) and age trended towards significance. Depression, but not OSA severity, was associated with PTSD symptoms.

Conclusions:

Following recent combat exposure, comorbid PTSD/OSA is not associated with increased PTSD symptoms or decreased severity of OSA. Early evaluation after traumatic exposure for comorbid OSA is indicated in PTSD patients with sleep complaints given the high co-occurrence and adverse clinical implications.

Citation:

Mysliwiec V, Matsangas P, Gill J, Baxter T, O'Reilly B, Collen JF, Roth BJ. A comparative analysis of sleep disordered breathing in active duty service members with and without combat-related posttraumatic stress disorder. J Clin Sleep Med 2015;11(12):1393–1401.


Inherent to posttraumatic stress disorder (PTSD) is disturbed sleep, with diagnostic criteria implicating nightmares and insomnia as the underlying sleep disorders. It is increasingly becoming apparent that obstructive sleep apnea (OSA) may significantly contribute to the underlying sleep disturbance.1 OSA results in decreased oxygen levels, elevated carbon dioxide, altered cardiovascular performance and arousals from sleep due to apneas, hypopneas, and respiratory related arousals.2 In both PTSD and OSA there is sleep fragmentation and an increased arousal index. Notably, the combination of PTSD and OSA, or comorbid PTSD/OSA, has been associated with worse physical and mental health outcomes.3

In studies assessing comorbid PTSD and OSA, these two distinct clinical disorders frequently co-occur. In a review of PTSD and sleep disordered breathing Krakow et al. reported a varied prevalence of comorbid PTSD and obstructive sleep apnea (OSA), ranging from 0% to 90%, though they favored a relatively high prevalence of 50% to 90%.4 In a large retrospective study assessing psychiatric diagnoses in older Veterans, those with OSA were 2.7 times as likely to have a diagnosis of PTSD.5 Similarly, 69.2% of young Veterans seeking treatment for PTSD screened at high risk for OSA on the Berlin questionnaire.6 There appears to be a significant association between OSA in both combat and non-combat related PTSD.1,4

BRIEF SUMMARY

Current Knowledge/Study Rationale: Sleep disordered breathing is a common comorbidity of PTSD. The relationship between OSA severity and combat-related PTSD has not been well defined.

Study Impact: There does not appear to be a predictable relationship between disease severity of either PTSD or OSA among patients with comorbid PTSD-OSA.

Thus far the postulated mechanisms for disrupted sleep in comorbid PTSD and OSA are theoretical.1,4 The common link is increased arousals and sleep fragmentation, which in PTSD occurs due to insomnia and nightmares and in OSA from sleep disordered breathing. While not proven, the current thought is that the synergistic effects of these two disorders results in an increased propensity to sleep disordered breathing and exacerbation of PTSD symptoms, contributing to an overall worsened clinical condition.6

It is currently unknown if exposure to trauma contributes to the development of sleep disordered breathing. Further research is required to determine how traumatic events affect sleep, both in terms of timing from the event and the nature of the trauma.1 In order to assess these questions, we hypothesized that Active Duty Service Members (ADSM) with comorbid PTSD/OSA would have more severe PTSD symptoms than those with only PTSD but a lower apnea hypopnea index (AHI) than those with OSA alone. We based our hypothesis on the current literature that OSA likely exacerbates PTSD,4,7 whereas patients with OSA alone would be expected to have worsened sleep primarily from sleep disordered breathing. A secondary aim was to characterize the military specific characteristics of combat severity, time from deployment to a combat zone, number of deployments, and rank to determine if these factors were associated with the diagnoses of PTSD, PTSD/OSA, or OSA.

METHODS

Study Participants

Participants were 109 ADSM who volunteered after being referred to the Madigan Sleep Disorders clinic for sleep complaints between March 2011 and January 2015 (Figure 1). The patients provided voluntary informed consent and completed self-report questionnaires. This observational study was approved by the Institutional Review Board at Madigan Army Medical Center in Tacoma, Washington.

Consort table.

jcsm.11.12.1393a.jpg

jcsm.11.12.1393a.jpg
Figure 1

Consort table.

(more ...)

Measures

Biometric parameters of age, ethnicity, body mass index (BMI), branch of service, rank, number and type of deployments, and time since most recent deployment were recorded during the initial intake evaluation. The BMI values were used to classify participants as underweight (BMI < 18.5), normal weight (18.5 ≤ BMI < 25.0), overweight (25.0 ≤ BMI < 30) and obese (BMI ≥ 30.0). The Posttraumatic Stress Disorder Checklist Military version (PCL-M) was used to assess symptoms of PTSD.8,9 Scores range from 17 to 82, and a score ≥ 50 was used to indicate a positive diagnosis of PTSD.9 The Combat Experiences Scale (CES) was used to assess combat intensity,10 with scores ranging from 0–15. A higher score indicated an increased number of different combat related exposures on one or more occasions. The Epworth Sleepiness Scale (ESS) was used to assess patients' sleepiness.11 The total ESS score, ranges from 0 (better) to 24 (worse). A score > 10 indicates excessive daytime sleepiness. The Pittsburgh Sleep Quality Index (PSQI) was used to determine self-reported sleep quality during the previous month.12 The PSQI includes 18 questions that yield 7 component scores (sleep quality, sleep latency, duration, sleep efficiency, sleep disturbances, sleep medication use, and daytime dysfunction) rated from 0 (better) to 3 (worse). The total score, ranging from 0 (better) to 21 (worse), is the summation of the component scores. Individuals with a PSQI total score ≤ 5 are characterized as good sleepers, whereas scores > 5 are associated with poor sleep quality. The PSQI has a sensitivity of 89.6% and a specificity of 86.5% (κ = 0.75, p < 0.001), and an internal consistency α = 0.83.12

The Quick Inventory of Depressive Symptomatology (QIDS) was used to screen for depression.13 Indicative of moderate to severe depression, a score ≥ 11 resulted in a positive screen for this disorder. The RAND 36-Item Short Form Health Survey (SF-36) was used to assess health related quality of life in study participants.14 The SF-36 consists of 8 health dimensions: physical functioning, bodily pain, role limitations due to physical health problems, role limitations due to personal or emotional problems, emotional well-being, social functioning, energy/fatigue, and general health perceptions. Scores were calculated for each dimension, ranging from 0 to 100, with a higher score indicating improved functioning in that dimension.

All participants underwent a diagnostic attended polysomnogram (PSG) using standardized techniques we have previously reported.15 Initially we scored hypopneas with a ≥ 50% decrease in nasal pressure signal excursion lasting ≥ 10 sec with either ≥ 3% desaturation or arousal in accordance with the American Academy of Sleep Medicine (AASM) alternate criteria.16 For PSGs conducted after August 2013, we required ≥ 30% decrease in nasal pressure signal excursion in accordance with the AASM revised scoring criteria.17 The PSG variables we analyzed included sleep onset latency (SOL), rapid eye movement (REM) onset latency, total sleep time (TST), wakefulness after sleep onset (WASO), sleep efficiency, arousal index, sleep stages (stage N1, stage N2, stage N3, stage R), AHI, and maximal desaturation. The sleep diagnoses of OSA and insomnia were rendered in accordance with the International Classification of Sleep Disorders, 2nd or 3rd edition, depending on the time of their initial evaluation.18

Statistical analysis was conducted with a statistical software package (JMP Pro 10; SAS Institute; Cary, NC). Data normality was assessed with the Shapiro-Wilk test. Given that our data violated the assumption of normality, statistical analysis was based on nonparametric methods. All variables underwent descriptive analysis to describe our population in terms of demographic characteristics. Participants were then classified in three groups, “Only OSA,” “Only PTSD,” and “PTSD/OSA” for patients with comorbid PTSD and OSA.

An α level of 0.05 was used to determine statistical significance. Pairwise comparisons between groups are based on Wilcoxon rank sum test, whereas for multiple comparisons we used Dunn's method for joint ranking accounting for family-wise error. Comparisons between proportions are based on Fisher exact test; for multiple comparisons between proportions, statistical significance was assessed using the Benjamini-Hochberg False Discovery Rate (BH-FDR) controlling procedure.19 When appropriate we report relative risk (RR) with the corresponding 95% confidence interval. Correlation analysis is based on Spearman rho. Data is presented as mean (standard deviation [SD]).

Missing data were interpolated for each patient by the most frequent response in the corresponding questionnaire (6 missing responses in PCLM data, one in CES, 10 in QIDS data). There were 14 (12.9%) patients who had missing PSQI scores which were not interpolated.

RESULTS

Descriptive Analysis

Participants' ages ranged from 20 to 53 years (34.3 ± 8.23) with 97.3% male (Table 1). The BMI ranged from 21.5 to 42.2 (30.8 ± 3.99). Participants were predominantly U.S Army (94.5%); 4.59% were U.S. Air Force, and one was U.S. Navy. The sample was classified into 4 rank groups (8.26% E1-E3, 71.6% E4-E6, 16.6% E7-E9, and 3.67% Officers). Overall, the study sample was ethnically diverse with Caucasian (58.7%), African American (11.9%), Hispanic/Latino (6.42%), Native Hawaiian/ Pacific Islander (4.59%), and Native American (1.84%) ethnicities represented (11.9% Biracial, no response = 4.59%). All participants had deployed at least once, with 70% of the patients having been deployed between 6 and 24 months prior to the data collection. The deployments were to OIF (68.6%), OEF (63.8%) followed by 6.67% to Desert Storm, 3.81% to Joint Endeavor, and 4.76% to Desert Shield (Other = 12.4%, Unknown = 0.95%). The average PSQI score was 12.3 ± 4.54, with 92.6% of patients classified as poor sleepers (PSQI score > 5).12 Overall, the highest occurrence of a comorbid illness was insomnia (95.4%) followed by OSA (84.4%) and depression (51.4%).

Sample demographic characteristics and polysomnographic variables.

jcsm.11.12.1393.t01.jpg

table icon
Table 1

Sample demographic characteristics and polysomnographic variables.

(more ...)

We performed a multivariate analysis to identify predictors (age, BMI, number of deployments, CES scores, and ESS) of OSA occurrence in our sample. BMI was the only statistically significant predictor of OSA occurrence at the 0.05 level. However, age and CES scores also showed a trend towards predicting OSA. Specifically, age was associated with increased OSA occurrence, while CES scores with less OSA (Table 2).

Predictors of OSA occurrence.

jcsm.11.12.1393.t02.jpg

table icon
Table 2

Predictors of OSA occurrence.

(more ...)

Pairwise correlation analysis between age, BMI, number of deployments, CES, ESS, PCL-M and QIDS scores (Table 3) showed that PCL-M scores were associated with QIDS (rho = 0.767, p < 0.001) and CES scores (rho = 0.496, p < 0.001); CES scores were correlated with QIDS scores (rho = 0.354, p < 0.001). We further assessed these correlations by comparing the occurrence of PTSD (PCL-M score ≥ 50), and depression (QIDS score ≥ 11). Results show that patients with PTSD are more likely to be diagnosed with depression (RR = 2.76 [1.90–4.03]). Figure 2 shows PCL-M versus CES scores grouped by the occurrence of depression.

Pairwise correlation analysis.

jcsm.11.12.1393.t03.jpg

table icon
Table 3

Pairwise correlation analysis.

(more ...)

PCL-M versus CES scores grouped by depression occurrence.

jcsm.11.12.1393b.jpg

jcsm.11.12.1393b.jpg
Figure 2

PCL-M versus CES scores grouped by depression occurrence.

(more ...)

Although older military personnel had participated in more deployments than the younger ones (rho = 0.477, p < 0.001), they reported less severe PTSD symptoms (PCL-M scores), fewer symptoms of depression (QIDS scores), and decreased combat intensity experience (CES scores). Furthermore, military personnel with OSA were older (35.4 ± 7.87), had less severe PTSD symptoms (PCL-M scores: 40.2 ± 15.8), and less intense combat experience (CES scores: 6.42 ± 4.09) than patients without OSA who were younger (29.0 ± 8.31; Wilcoxon rank sum test, Z = 3.22, p = 0.001), had more severe PTSD symptoms (PCL-M scores: 60.5 ± 4.73; Z = 4.77, p < 0.001), and had more intense combat experience (CES scores: 9.0 ± 4.03; Z = 2.32, p = 0.021).

After excluding the patients without OSA, the severity of OSA (mild, moderate, severe) per se was not associated with PCL-M scores (p > 0.50). A multiple regression analysis showed that this lack of correlation pattern was evident even after adjusting for CES scores (p = 0.479) and time since last deployment (p = 0.659). However, depression was a significant factor (p < 0.001); specifically, military personnel with OSA and depression had significantly higher PCL-M scores (50.9 ± 14.4) than those with OSA without depression (31.6 ± 10.9; Figure 2).

Comparisons between Groups

Next, we compared the 3 groups, “PTSD/OSA,” “Only OSA,” and “Only PTSD” (Table 4). All 4 officers were in the OSA group, whereas the other rank classifications did not differ substantively between patient groups. Time since last deployment also did not differ between patient groups (p > 0.30).

Polysomnographic variables and demographic characteristics by group.

jcsm.11.12.1393.t04.jpg

table icon
Table 4

Polysomnographic variables and demographic characteristics by group.

(more ...)

Military personnel with comorbid PTSD/OSA compared to those with OSA alone had increased QIDS (p < 0.001) and CES scores (p < 0.05). These findings suggest that patients with comorbid PTSD/OSA had increased depressive symptoms and assessed their combat experiences of increased intensity compared to patients with OSA alone. Therefore, it was not surprising that the occurrence of depression in the PTSD/OSA group was nearly 3 times higher (83.3%) than the OSA group (30.9%; Fisher exact test, p < 0.001; RR = 2.70 [1.81–4.02]). Figure 3 shows the PCL-M data versus CES scores grouped by depression occurrence and patient groups (comorbid PTSD/ OSA, OSA alone, and PTSD alone).

PCL-M by OSA and depression occurrence.

Vertical bars denote one standard deviation.

jcsm.11.12.1393c.jpg

jcsm.11.12.1393c.jpg
Figure 3

PCL-M by OSA and depression occurrence.Vertical bars denote one standard deviation.

(more ...)

A detailed picture of the severe responses (“Quite a bit” and “Extremely” ratings) by patient group in each of the 17 items of the PCL-M survey is shown in Table 5. Results show the PTSD/OSA group (61.3%) has on average considerably higher occurrence of severe responses than the OSA group (8.91%), but similar to the PTSD group (57.1%). This difference between the PTSD/OSA and the OSA groups appears consistent in all items of the PCL-M (Fisher exact test, in all cases p < 0.001). The similarity between the PTSD/OSA and the PTSD groups is also consistent in all items of the PCL-M (Fisher exact test, in all cases p > 0.15).

Percentage of ratings “Quite a bit” / “Extremely” by PCL-M item and group.

jcsm.11.12.1393.t05.jpg

table icon
Table 5

Percentage of ratings “Quite a bit” / “Extremely” by PCL-M item and group.

(more ...)

DISCUSSION

Among active duty military personnel evaluated within two years following combat exposure, comorbid PTSD/OSA was not associated with either a decreased severity of OSA or an increased severity of PTSD symptoms compared to OSA or PTSD alone. There were significant differences in sleep quality between the PTSD/OSA and OSA groups as measured by the PSQI; however, there was no difference between the PTSD/ OSA and PTSD groups. Although sleepiness (measured by the ESS) did not differ between any of the groups, fatigue was significantly increased in PTSD and PTSD/OSA compared to OSA alone. These findings suggest that the deleterious effects on sleep and overall health are predominantly due to the PTSD component and not a synergistic interaction between PTSD and sleep disordered breathing.

The finding that comorbid PTSD/OSA is not associated with increased clinical severity is in contrast to other studies and recent reviews.1,4,6 In a small study with 6 patients with comorbid PTSD/OSA, PTSD severity as measured by the CAPS was related to OSA severity.20 An older population of Vietnam Veterans with PTSD/OSA who were followed in a longitudinal study had worsening of their OSA with an overall AHI increase of 2.19/h/year without a corresponding increase in BMI.21 There are several potential reasons for our findings. First, all subjects were evaluated in close proximity to their traumatic exposure. Second, all participants underwent an attended PSG. Finally, our cohort is relatively uniform, as all subjects were on Active Duty. Interestingly, there were not any significant differences in the PSG variables between the three groups in sleep stages or sleep efficiency except as would otherwise be explained by the contribution of sleep disordered breathing. This contrasts with previous findings where PTSD was associated with increased N1 and decreased N3 sleep.22 Overall, these findings reinforce the possibility that sleep disordered breathing and PTSD are present soon after experiencing traumatic events, and potentially offer an early window for intervention.

All of the military personnel returned from a combat deployment. Not surprisingly those with a PTSD diagnosis had significantly increased CES scores as a more intense combat exposure is associated with increased PTSD symptom severity.23 Otherwise neither the number of deployments nor time since returning from combat was associated with any of the diagnoses. Age was associated with specific diagnoses, as younger military personnel were more likely to have PTSD alone whereas older military personnel were more likely to have OSA alone. This could have biased our results since the PTSD/OSA group may have compared differently with a group of OSA patients who were closer in age. Similar findings were reported by Williams et al., as younger soldiers with PTSD in their study were more likely to have combat-associated injuries and less likely to have OSA compared to older soldiers.24 Further, in both reports, younger military personnel had a lower BMI, noting that BMI significantly predicted the occurrence of OSA in our study. The finding that the known risk factors of increased age and BMI, and not PTSD, are associated with the diagnosis of OSA supports that the co-occurrence of PTSD and OSA is an epiphenomenon. Sleep disturbances are inherent to PTSD, and OSA is a relatively common disorder in this population.

The rate of OSA in military personnel with PTSD in our study was 58.5%. This is consistent with other reports of PTSD/ OSA in active duty soldiers. Williams et al. reported on a similar population (80% underwent a PSG), with 67.3% having PTSD/OSA.24 The overall characteristics of their population in terms of age, BMI, OSA severity, and comorbid illnesses are similar to ours, with a mean age of 35.1, BMI of 28.1 kg/m2, AHI of 16.7 ± 21.3, and 88.5% having depression. In another report, Capaldi et al. reported on 69 active duty military personnel with sleep disturbances, 28 having PTSD/OSA.25 Their cohort was also similar in terms of age (37.9 years), BMI (29.0 kg/m2), and comorbidities.

Our results highlight depressive symptoms as a marker for more severe PTSD/OSA. Depression is common in patients with PTSD,26 and OSA is a frequent comorbidity of both disorders. Our findings substantiate this, as the rate of depression among ADSM with PTSD/OSA was markedly higher than in those with OSA alone. Patients with depression and sleep disorders may have a more severe course with an increased likelihood of suicide and diminished response to therapy.27 While treatment of sleep disordered breathing in PTSD can improve neurocognitive and mood related symptoms,1 including depression,28 PAP adherence is usually poor.29 Further, patients with depression may experience weight gain due to depression and antidepressant medication, which could increase the risk for OSA.27 This provides additional rationale for early interventions in this vulnerable population.

Treatment of sleep disordered breathing in PTSD is felt to have a positive impact on symptoms, although the evidence is limited.30,31 A retrospective study by Tamanna et al. reported that veterans with PTSD/OSA who were adherent to positive airway pressure (PAP) not only had improved sleepiness but nightmares as well.32 This is consistent with our clinical practice where patients with PTSD/OSA adherent to PAP have improved sleep, sleepiness, and decreased PTSD symptoms. In part, though, this may occur because we concomitantly treat OSA, nightmares, and insomnia at our sleep disorders center. Treatment of OSA in PTSD is limited by poor adherence with PAP.33 There are two recent studies which used cognitive behavioral therapy for insomnia (CBT-i) and demonstrated significant improvements in both insomnia and PTSD symptoms.34,35 A similar multidisciplinary approach with PAP, CBTi, and image rehearsal therapy or prazosin for the OSA, insomnia and nightmares in patients with PTSD/OSA may prove the optimal treatment regimen.

Limitations

Our study may have some limitations. Patients with PTSD were not stratified according to clinical diagnoses or treatment; specifically their diagnosis was based on PCL-M scores alone. In contrast the diagnosis of OSA was determined by polysomnography. There is the potential for referral bias in that patients with PTSD may have had refractory sleep disturbances prompting referral for sleep consultation. The population we studied is fairly specific, encompassing an active duty, predominantly male population with recent combat exposure. Thus, the findings are not necessarily generalizable to non-combat related PTSD or female patients with PTSD. Notwithstanding these limitations, our findings provide a new insight into comorbid PTSD/OSA, especially relatively early in the development of this chronic illness.

CONCLUSIONS

In active duty military personnel with recently diagnosed PTSD and sleep disturbances, there does not appear to be a significant difference between PTSD/OSA and PTSD or OSA alone in terms of severity of PTSD symptoms or AHI severity, respectively. Targeting this population early, in terms of diagnostic and treatment strategies should be a clinical imperative given the high number of military personnel and veterans with sleep disorders and PTSD.

DISCLOSURE STATEMENT

This was not an industry supported study. The authors have indicated no financial conflicts of interest. The opinions and assertions in this manuscript are those of the authors and do not necessarily represent those of the Department of the Army, the Department of Defense, or the U.S. government.

ABBREVIATIONS

ADSM

Active Duty Service Members

AHI

apnea-hypopnea index

AASM

American Academy of Sleep Medicine

BH-FDR

Benjamini-Hochberg False Discovery Rate

BMI

body mass index

CES

Combat Experiences Scale

ESS

Epworth Sleepiness Scale

OSA

obstructive sleep apnea

PSQI

Pittsburgh Sleep Quality Index

PSG

polysomnogram

PCL-M

Posttraumatic Stress Disorder Checklist Military version

PTSD

posttraumatic stress disorder

QIDS

Quick Inventory of Depressive Symptomatology

REM

rapid eye movement

RR

relative risk

SF-36

RAND 36-Item Short Form Health Survey

SD

standard deviation

SOL

sleep onset latency

TST

total sleep time

WASO

wakefulness after sleep onset

REFERENCES

1 

Jaoude P, Vermont LN, Porhomayon J, El-Solh AA, authors. Sleep-disordered breathing in patients with post-traumatic stress disorder. Ann Am Thorac Soc. 2015;12:259–68. [PubMed]

2 

Dempsey JA, Veasey SC, Morgan BJ, O'Donnell CP, authors. Pathophysiology of sleep apnea. Physiol Rev. 2010;90:47–112. [PubMed Central][PubMed]

3 

Krakow B, Melendrez D, Johnston L, et al., authors. Sleep-disordered breathing, psychiatric distress, and quality of life impairment in sexual assault survivors. J Nerv Ment Dis. 2002;190:442–52. [PubMed]

4 

Krakow BJ, Ulibarri VA, Moore BA, McIver ND, authors. Posttraumatic stress disorder and sleep-disordered breathing: a review of comorbidity research. Sleep Med Rev. 2014;24C:37–45.

5 

Sharafkhaneh A, Giray N, Richardson P, Young T, Hirshkowitz M, authors. Association of psychiatric disorders and sleep apnea in a large cohort. Sleep. 2005;28:1405–11. [PubMed]

6 

Colvonen P, Masino T, Drummond S, Myers U, Angkaw A, Norman S, authors. Obstructive sleep apnea and posttraumatic stress disorder among OEF/OIF/ OND veterans. J Clin Sleep Med. 2015;11:513–8. [PubMed Central][PubMed]

7 

Arnetz BB, Templin T, Saudi W, Jamil H, authors. Obstructive sleep apnea, posttraumatic stress disorder, and health in immigrants. Psychosom Med. 2012;74:824–31. [PubMed Central][PubMed]

8 

Wilkins KC, Lang AJ, Norman SB, authors. Synthesis of the psychometric properties of the PTSD checklist (PCL) military, civilian, and specific versions. Depress Anxiety. 2011;28:596–606. [PubMed Central][PubMed]

9 

Weathers FW, Litz BT, Keane TM, Palmieri PA, Marx BP, Schnurr PP, authors. The PTSD Checklist for DSM-5 (PCL-5). 2013. Scale available from the National Center for PTSD at www.ptsd.va.gov.

10 

Vogt DS, Proctor SP, King DW, King LA, Vasterling JJ, authors. Validation of scales from the Deployment Risk and Resilience Inventory in a sample of Operation Iraqi Freedom veterans. Assessment. 2008;15:391–403. [PubMed]

11 

Johns MW, author. A new method for measuring daytime sleepiness: the Epworth Sleepiness Scale. Sleep. 1991;14:540–5. [PubMed]

12 

Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ, authors. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. J Psychiatr Res. 1989;28:193–213.

13 

Trivedi MH, Rush AJ, Ibrahim HM, et al., authors. The Inventory of Depressive Symptomatology, Clinician Rating (IDS-C) and Self-Report (IDS-SR), and the Quick Inventory of Depressive Symptomatology, Clinician Rating (QIDS-C) and Self-Report (QIDS-SR) in public sector patients with mood disorders: a psychometric evaluation. Psychol Med. 2004;34:73–82. [PubMed]

14 

McHorney CA, Ware JE Jr.; Lu JF, Sherbourne CD, authors. The MOS 36-item Short-Form Health Survey (SF-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups. Med Care. 1994;32:40–66. [PubMed]

15 

Mysliwiec V, Gill J, Lee H, et al., authors. Sleep disorders in US military personnel: a high rate of comorbid insomnia and obstructive sleep apnea. Chest. 2013;144:549–57. [PubMed]

16 

Iber C, Ancoli-Israel S, Chesson A, Quan S, authors. AASM manual for the scoring of sleep and associated events: rules, terminology and technical specifications. Westchester, IL: American Academy of Sleep Medicine, 2007.

17 

Berry R, Budhiraja R, Gottlieb D, authors. Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine. Rules for scoring respiratory events in sleep: update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events. J Clin Sleep Med. 2012;8:597–619. [PubMed Central][PubMed]

18 

American Academy of Sleep Medicine. International classification of sleep disorders, 3rd edition. Darien, IL: American Academy of Sleep Medicine, 2013.

19 

Benjamini Y, Hochberg Y, authors. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Stat Methodol. 1995;57:289–300.

20 

van Liempt S, Westenberg HG, Arends J, Vermetten E, authors. Obstructive sleep apnea in combat-related posttraumatic stress disorder: a controlled polysomnography study. Eur J Psychotraumatol. 2011;2.

21 

Yesavage JA, Kinoshita LM, Noda A, et al., authors. Longitudinal assessment of sleep disordered breathing in Vietnam veterans with post-traumatic stress disorder. Nat Sci Sleep. 2014;6:123–7. [PubMed Central][PubMed]

22 

Kobayashi I, Boarts JM, Delahanty DL, authors. Polysomnographically measured sleep abnormalities in PTSD: a meta-analytic review. Psychophysiology. 2007;44:660–9. [PubMed]

23 

Foy DW, Sipprelle RC, Rueger DB, Carroll EM, authors. Etiology of posttraumatic stress disorder in Vietnam veterans: analysis of premilitary, military, and combat exposure influences. J Consult Clin Psychol. 1984;52:79–87. [PubMed]

24 

Williams SG, Collen J, Orr N, Holley AB, Lettieri CJ, authors. Sleep disorders in combat-related PTSD. Sleep Breath. 2015;19:175–82. [PubMed]

25 

Capaldi VF II, Guerrero ML, Killgore WD, authors. Sleep disruptions among returning combat veterans from Iraq and Afghanistan. Mil Med. 2011;176:879–88. [PubMed]

26 

Shalev AY, Freedman S, Peri T, et al., authors. Prospective study of posttraumatic stress disorder and depression following trauma. Am J Psychiatry. 1998;155:630–7. [PubMed]

27 

Murphy MJ, Peterson MJ, authors. Sleep disturbances in depression. Sleep Med Clin. 2015;10:17–23. [PubMed]

28 

Mysliwiec V, Capaldi VF 2nd, Gill J, et al., authors. Adherence to positive airway pressure therapy in U.S. military personnel with sleep apnea improves sleepiness, sleep quality, and depressive symptoms. Mil Med. 2015;180:475–82. [PubMed]

29 

Law M, Naughton M, Ho S, Roebuck T, Dabscheck E, authors. Depression may reduce adherenceduring CPAP titration trial. J Clin Sleep Med. 2014;10:163–9. [PubMed Central][PubMed]

30 

McMahon JP, Foresman BH, Chisholm RC, authors. The influence of CPAP on the neurobehavioral performance of patients with obstructive sleep apnea hypopnea syndrome: a systematic review. WMJ. 2003;102:36–43.

31 

Krakow B, Lowry C, Germain A, et al., authors. A retrospective study on improvements in nightmares and post-traumatic stress disorder following treatment for co-morbid sleep-disordered breathing. J Psychosom Res. 2000;49:291–8. [PubMed]

32 

Tamanna S, Parker JD, Lyons J, Ullah MI, authors. The effect of continuous positive air pressure (CPAP) on nightmares in patients with posttraumatic stress disorder (PTSD) and obstructive sleep apnea (OSA). J Clin Sleep Med. 2014;10:631–6. [PubMed Central][PubMed]

33 

Collen JF, Lettieri CJ, Hoffman M, authors. The impact of posttraumatic stress disorder on CPAP adherence in patients with obstructive sleep apnea. J Clin Sleep Med. 2012;8:667–72. [PubMed Central][PubMed]

34 

Ulmer CS, Edinger JD, Calhoun PS, authors. A multi-component cognitive-behavioral intervention for sleep disturbance in veterans with PTSD: a pilot study. J Clin Sleep Med. 2011;7:57–68. [PubMed Central][PubMed]

35 

Talbot LS, Maguen S, Metzler TJ, et al., authors. Cognitive behavioral therapy for insomnia in posttraumatic stress disorder: a randomized controlled trial. Sleep. 2014;37:327–41. [PubMed Central][PubMed]