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Volume 14 No. 11
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Accepted Papers





Scientific Investigations

Increased Sleep Disturbances and Pain in Veterans With Comorbid Traumatic Brain Injury and Posttraumatic Stress Disorder

Nadir M. Balba, MA1,2; Jonathan E. Elliott, PhD1,3; Kris B. Weymann, PhD, RN1,4; Ryan A. Opel, BSc1; Joseph W. Duke, PhD5; Barry S. Oken, MD, PhD2,3; Benjamin J. Morasco, PhD6,7; Mary M. Heinricher, PhD1,2,8; Miranda M. Lim, MD, PhD1,2,3,9,10
1VA Portland Health Care System, Portland, Oregon; 2Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, Oregon; 3Department of Neurology, Oregon Health and Science University, Portland, Oregon; 4School of Nursing, Oregon Health and Science University, Portland, Oregon; 5Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona; 6Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland, Oregon; 7Department of Psychiatry, Oregon Health and Sciences University, Portland, Oregon; 8Department of Neurological Surgery; Oregon Health and Science University, Portland, Oregon; 9Department of Medicine, Division of Pulmonary and Critical Care Medicine, Oregon Health and Science University, Portland, Oregon; 10Oregon Institute of Occupational Health Sciences, Oregon Health and Science University, Portland, Oregon

ABSTRACT

Study Objectives:

Veterans are at an increased risk for traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD), both of which are associated with sleep disturbances and increased pain. Furthermore, sleep disturbances and pain are reciprocally related such that each can exacerbate the other. Although both TBI and PTSD are independently linked to sleep disturbances and pain, it remains unclear whether Veterans with comorbid TBI+PTSD show worse sleep disturbances and pain compared to those with only TBI or PTSD. We hypothesized that sleep and pain would be worse in Veterans with comorbid TBI+PTSD compared to Veterans with only TBI or PTSD.

Methods:

Veterans (n = 639) from the VA Portland Health Care System completed overnight polysomnography and self-report questionnaires. Primary outcome variables were self-reported sleep disturbances and current pain intensity. Participants were categorized into four trauma-exposure groups: (1) neither: without TBI or PTSD (n = 383); (2) TBI: only TBI (n = 67); (3) PTSD: only PTSD (n = 126); and (4) TBI+PTSD: TBI and PTSD (n = 63).

Results:

The PTSD and TBI+PTSD groups reported worse sleep compared to the TBI and neither groups. The TBI+PTSD group reported the greatest pain intensity compared to the other groups.

Conclusions:

These data suggest sleep and pain are worst in Veterans with TBI and PTSD, and that sleep is similarly impaired in Veterans with PTSD despite not having as much pain. Thus, although this is a complex relationship, these data suggest PTSD may be driving sleep disturbances, and the added effect of TBI in the comorbid group may be driving pain in this population.

Citation:

Balba NM, Elliott JE, Weymann KB, Opel RA, Duke JW, Oken BS, Morasco BJ, Heinricher MM, Lim MM. Increased sleep disturbances and pain in Veterans with comorbid traumatic brain injury and posttraumatic stress disorder. J Clin Sleep Med. 2018;14(11):1865–1878.


BRIEF SUMMARY

Current Knowledge/Study Rationale: Traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are common in Veterans and are independently associated with sleep disturbances and pain, both of which can exacerbate the other and impede rehabilitation. Understanding the relationship between TBI, PTSD, sleep, and pain will help improve treatment and rehabilitation in this vulnerable population.

Study Impact: This study demonstrates that Veterans with PTSD and with both PTSD and TBI experience more sleep disturbances, but those with TBI and PTSD report significantly greater current pain intensity. These data help in the limited understanding of how Veterans with comorbid TBI and PTSD differ from Veterans with only TBI or PTSD and contribute to the development of improved therapeutic approaches for Veterans in this vulnerable population.

INTRODUCTION

Traumatic brain injury (TBI) is defined as a disruption in brain function, or other brain pathology, resulting from an external force.1 The most recent estimate from the Centers for Disease Control and Prevention found that approximately 2.5 million people in the United States sustain a TBI each year,2 with a significantly higher incidence of TBI among Veterans. Although TBI severity can be mild, moderate, or severe, ∼80% are classified as mild,3 and are associated with a variety of sequelae as well as an increased risk of the development of posttraumatic stress disorder (PTSD). Among the most prevalent, persistent, and debilitating sequelae in both TBI and PTSD are sleep disturbances and increased pain. Importantly, sleep disturbances and pain also share a reciprocal relationship such that increases in either can independently exacerbate the other.47

It has been estimated that > 50% of people with TBI experience sleep disturbances,810 including insomnia,11 hypersomnia,8 obstructive sleep apnea (OSA),9 and circadian rhythm sleep disorders.9,12 Furthermore, current evidence suggests these sleep disturbances can persist for several years postinjury.13 Sleep disturbances are also a hallmark feature of PTSD with recurrent nightmares and difficulty sleeping being diagnostic symptoms for PTSD.14 One study of Vietnam Veterans revealed that almost 91% of soldiers with PTSD also experienced difficulties sleeping.15 Similar to TBI, individuals with PTSD experience a range of sleep problems,16 including insomnia,17,18 nightmares,18,19 sleep fragmentation,20 OSA,21,22 and parasomnias.2325

Similar to sleep disturbances, both TBI and PTSD are also independently associated with increased pain.2636 In fact, the combination of TBI, PTSD, and pain, referred to clinically as the “polytrauma clinical triad,”31,3739 is very common among Veterans, with recent work reporting a prevalence of approximately 42% from 340 Operation Enduring Freedom and Operation Iraqi Freedom (OEF/OIF) Veterans.38 Irrespective of TBI and PTSD, the presence of sleep disturbances are also independently associated with increased pain.5,4044 Although the mechanism(s) linking sleep disturbances and pain are not fully understood, a bidirectional theory exists acknowledging pain can interfere with sleep, whereas poor sleep can exacerbate pain. For instance, Lang and colleagues found that in Veterans with TBI, PTSD, and pain (ie, the polytrauma clinical triad), insomnia was a significant mediator of both pain severity and pain interference.45 Conversely, improving sleep quality in patients with TBI and/or PTSD can ameliorate pain and thereby improve the efficacy of rehabilitative strategies.31,46 Understanding the link between these disorders and sleep disturbances is therefore highly relevant and important for developing more effective treatment options for Veterans.

Although there is considerable literature describing the association between TBI and PTSD with increased sleep disturbances and pain, few studies have explored how comorbid TBI and PTSD might potentiate this relationship. Thus, the purpose of this study was to determine whether Veterans with comorbid TBI and PTSD exhibit a higher prevalence of sleep disturbances (determined via self-report and objective polysomnography [PSG]) and pain compared to Veterans with only TBI or PTSD. Pain was primarily assessed via self-reported current pain intensity, and secondarily via the prevalence of headache and sensory (light and noise) sensitivity. We hypothesized that Veterans with comorbid TBI and PTSD would report worse sleep disturbances and pain compared to Veterans with only TBI or PTSD.

METHODS

The VA Portland Health Care System (VAPORHCS) institutional review board approved this study (MIRB #3641) and all subjects provided verbal and written informed consent prior to participation.

Overview

Veterans referred to the VAPORHCS Sleep Disorders Clinic between May 2015 and November 2016 were recruited for participation in a cross-sectional study design (n = 639). Participants provided self-report data on sleep quality, pain, and symptom severity relating to TBI and PTSD, as well as completed an overnight PSG study at the VAPORHCS Sleep Clinic.

Participant Grouping and Demographics

Veterans were assessed for a prior history of TBI via a retrospective medical record review (discussed in the following paragraphs), and for the presence of PTSD via the PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, or DSM-5 (also discussed in the following paragraphs). Based on their prior history of trauma exposure, participants were grouped into the following four trauma-exposure categories: (1) neither: no history of TBI or PTSD (n = 383); (2) TBI: at least one instance of TBI documented in the medical record, but no PTSD (n = 67); PTSD: meeting diagnostic criteria for PTSD, but no medical record documented TBI (n = 126); TBI+PTSD: both a medical record documented TBI and meeting diagnostic criteria for PTSD (n = 63). Participants in the neither group constituted the control group in the current manuscript and analyses. Demographic data, including, age, sex, body mass index (BMI), race, education (self-reported highest level of completed education), and current exercise status (self-reported minutes of exercise per week) was also collected for all participants.

Retrospective Medical Record Review

A retrospective medical record review was conducted to assess general health and numerous metrics related to the TBI experienced by the participants. These included determining (1) the number of TBIs; (2) the recency of the TBI (determined from year of most recent TBI if more than one TBI was identified); (3) whether the TBI was caused by blast exposure; (4) whether the TBI caused loss of consciousness, confusion, posttraumatic amnesia, or postconcussive syndrome; (5) if participants now have tinnitus or hearing loss; (6) whether participants were OEF/OIF Veterans; (7) the presence of anxiety; (8) the presence of diabetes; (9) the presence of hypertension; (10) the presence of heart disease; (11) the presence of lung disease; (12) current sleep medication usage; and (13) current pain medication usage. Sleep medication usage included any one of the following: sedative-hypnotics, benzodiazepines, gamma-hydroxybutyric acid, melatonin, doxylamine, trazadone, quetiapine, diphenhydramine, mirtazapine, and over-the-counter herbs. Pain medication usage included any one of the following: oxycontin, hydrocodone, morphine, oxycodone (Percocet), hydrocodone bitartrate (Vicodin), fentanyl patch, methadone, codeine, naltrexone/suboxone, and lidocaine patch. Items 1 through 6 were obtained through manual review of relevant notes; items 7 through 11 were obtained through the VA Computerized Patient Record System Problem List (International Classification of Diseases, Tenth Revision coded diagnoses) and were included only if there were active problems at or around the time of consent. Additionally, the presence of sleep apnea was extracted from participants' overnight PSG.

Survey Instruments

TBI Symptom Severity

Rivermead Post Concussion Questionnaire: Participants with a history of TBI were administered the Rivermead Post Concussion Questionnaire (RPQ) to assess postconcussive syndrome symptom severity, which asks participants to rate 13 commonly occurring symptoms of TBI.47 These include headaches, dizziness, nausea, noise sensitivity, sleep disturbance, fatigue, irritability, depression, frustration, forgetfulness, poor concentration, taking longer to think, blurred vision, light sensitivity, double vision, and restlessness. Each individual symptom is ranked on a 5-point Likert scale: 0 = not experienced at all, 1 = no more of a problem, 2 = a mild problem, 3 = a moderate problem, 4 = a severe problem. Thus, total scores ranged from 0 to 52, with higher scores indicating greater severity of symptoms.

PTSD Status and Symptom Severity

PTSD Checklist DSM-5: The PTSD Checklist for DSM-5 (PCL-5)48 is a 20-item measure used for screening and provisionally diagnosing PTSD in participants, as well as for assessing PTSD symptom severity. Individual items ranked on a 5-point Likert scales: 0 = not at all, 1 = a little bit, 2 = moderately, 3 = quite a bit, 4 = extremely. Thus, the total score ranges from 0 to 80. The survey questions are subdivided into four subscales, or clusters: cluster B (intrusion; 1–5), cluster C (avoidance; 6–7), cluster D (mood and cognition; 8–14), and cluster E (arousal activity; 15–20). Cluster A, which was not administered in this study, is a structured clinical interview (eg, Clinician-Administered PTSD Scale) and is required for administering an official diagnosis of PTSD. Thus, participants in the current study were categorized as having PTSD based on their PCL-5 cluster criteria, and total score (≥ 33).48 PCL-5 cluster criteria required participants to rate one item from cluster B, one item from cluster C, two items from cluster D, and two items from cluster E as 2 (moderately) or higher. Cronbach alpha in our sample was .97 (.97–.97), which is consistent with previously reported values.49

Sleep

Insomnia Severity Index: The Insomnia Severity Index (ISI) is a 7-item measure assessing insomnia severity (ie, difficulty initiating and staying asleep), with the total score ranging from 0 to 28.50 Individual items are ranked on 5-point Likert scales: 0 = none, 1 = mild, 2 = moderate, 3 = severe, 4 = very severe. Cronbach alpha in our sample was .88 (.87–.90), which is consistent with previously reported values.51

Functional Outcomes of Sleep Questionnaire-10: The Functional Outcomes of Sleep Questionnaire (FOSQ-10) is a 10-item measure assessing quality of life due to sleep quality.52 Individual items are ranked on 4-point Likert scales: 1 = yes, extreme difficulty, 2 = yes, moderate difficulty, 3 = yes, a little difficulty, 4 = no difficulty. Half of the items include a rating of 0 = I don't do this activity for other reasons, and items answered as zero are not used in determining total score (range, 5 to 40). The survey has five subscales reflecting how their sleep quality affects different aspects of their lives: (1) general productivity, indicating participant's inability to complete important daily tasks (2 items); (2) activity level, indicating participant's struggle to participate in normal physical activities (3 items); (3) vigilance, indicating participant's inability to sustain attention during normal activities (1 item); (4) social outcomes, indicating participant's level of daily socialization (2 items); and (5) intimacy and sexual relationships, indicating participant's level of sexual satisfaction (1 item).53 To obtain the total score, the mean of each subscale was calculated, then summed, divided by the number of subscales with an answer, and then multiplied by five, for a total score of 5 to 20.54 The higher score indicates higher function. Cronbach alpha in our sample was .85 (.83–.87), which is consistent with previously reported values.52

Pain

PROMIS Global Health Survey: The National Institute of Health Patient-Reported Outcome Measurement Information System (PROMIS) Global Health Survey is a validated self-report that measures several domains related to the patient's overall health.55 For this study we used the item 7 score, which rates the patient's overall level of pain on an 11-point Likert scale: 0 = no pain to 10 = worst imaginable pain.55

Overnight Polysomnography

All participants completed a clinically indicated in-laboratory, technician-attended overnight PSG (ie, type I sleep study). Clinically indicated PSG studies were either (1) a full-night positive airway pressure (PAP) titration study, where participants wore a PAP mask throughout the night; (2) a split-night study, where participants wore a PAP mask through the second half of the night; or (3) a full-night diagnostic study where the participant did not wear a PAP mask. Of note, the statistical analysis of PSG-related variables was done using a one-way analysis of covariance with PSG type as the covariate. All sleep studies were recorded using Polysmith version 9.0 (Nihon Kohden; 2012). Sleep staging was performed by a certified sleep technician and verified by a board-certified sleep medicine physician. Standard parameters as specified by the American Academy of Sleep Medicine28 were captured in the PSG recordings, including electroencephalography, electromyography of the mentalis muscle, electrooculography (left and right eyes), electrocardiography, peripheral blood-oxygen saturation, respiratory movement/effort (thorax and abdominal), airflow (nasal and oral), auditory (snoring), and body positioning (right side, left side, supine, prone).

Individual PSG data were analyzed for total sleep time (TST), time spent in each sleep stage as a percent of TST, number of sleep stage transitions, sleep efficiency, sleep latency, wake after sleep onset (WASO), and body position transitions. TST was calculated by summing the total number of epochs scored as non-rapid eye movement sleep (NREM) or rapid eye movement (REM) sleep and converting to minutes. Sleep stage transitions was determined by counting the number of times a patient changed from one sleep stage (wake, N1, N2, N3, or R) to another stage, with the tally beginning at lights off. Sleep efficiency was calculated as the percentage of time a patient spent sleeping after initially falling asleep. Sleep latency was determined by counting the number of 30-second epochs between lights offand the initial onset of NREM sleep. WASO was determined to be the length of time in minutes a patient spent awake after initially falling asleep for the night. Finally, body position transitions were calculated similarly to sleep stage transitions; transitions that occurred before sleep onset were ignored.

Statistical Analyses

All statistical analyses were performed using R version 3.3.2,56 and alpha was set to P = .05 a priori. Mean differences between groups were assessed using either an unpaired t test or a one-way analysis of variance (ANOVA) or covariance (ANCOVA), where appropriate. Post hoc testing was performed after a significant omnibus ANOVA or ANCOVA using Newman-Keuls or Tukey Honestly Significant Difference. Differences in categorical data were assessed using a chi-square test, with a Bonferroni post hoc test if warranted.57 Alternatively, if the expected value in the 2 × 2 contingency table was less than 5, Fisher exact test with a simulated P value was used instead of chi-square. Normality was assessed via the Shapiro-Wilk test. Although not all datasets were normally distributed, given the large sample size, our analyses are relatively robust to the violation of normality assumptions. Finally, multiple linear regression was used to examine the individual contributions of TBI and PTSD to the relationship between sleep disturbances and pain. Standardized beta coefficients were calculated by standardizing each variable (ie, subtracting the mean from the variables and dividing by their standard deviation) such that each standardized variable has a mean of 0 and standard deviation of 1.

RESULTS

Demographic and General Health Parameters

Demographic and general health parameters are shown in Table 1. The primary difference across groups was with respect to participants' age. Specifically, the TBI+PTSD group was younger than the PTSD (P < .001), TBI (P = .047), and neither groups (P < .001). Additionally, although the age of the TBI and PTSD groups did not differ from each other (P = .628), they were also both younger than the neither group (P < .001 for both). No other differences were detected across groups with respect to BMI, sex, race, education level, or weekly exercise level.

Demographic and general health parameters.

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Table 1

Demographic and general health parameters.

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There were also very few differences across groups within general health parameters assessed via the retrospective chart review. No differences across groups were found in the rates of anxiety, hypertension, heart disease, lung disease, or OSA. However, we did detect differences in the proportion of participants with diabetes and tinnitus. With respect to diabetes, both the TBI and TBI+PTSD groups showed significantly lower rates compared to the neither group (TBI+PTSD versus neither P = .002; TBI versus neither P = .006), whereas the PTSD group had significantly lower rates compared to the TBI group (P = .002). With respect to tinnitus, the TBI (P = .039), PTSD (P = .001), and TBI+PTSD (P < .001) groups all showed significantly higher rates compared to the neither group. However, the TBI+PTSD group reported the highest prevalence, with it also being significantly higher than the TBI (P = .008) and PTSD (P = .004) groups.

TBI and PTSD Parameters

Characteristics and postconcussive symptomology related to participants' TBIs are presented in Table 2. Although the TBI+PTSD group experienced a significantly higher number of TBIs compared to the TBI group (P = .030), there were no differences detected in the recency (measured in years) of participants' TBI between groups despite an overall difference in the proportion of participants being OEF/OIF Veterans (P = .002). With respect to specific postinjury characteristics, we found differences between groups in the proportion of participants experiencing a blast-related TBI (P = .013), postconcussive syndrome (P = .036), and postinjury confusion (P = .037). However, there were no differences in the distribution of participants experiencing posttraumatic loss of consciousness (P = .486), posttraumatic amnesia (P = .874), or hearing loss (P = .236).

TBI characteristics.

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Table 2

TBI characteristics.

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Sleep Disturbances

Participants in the TBI+PTSD and PTSD groups had significantly worse ISI scores (ie, higher scores) compared to both the TBI and neither groups (P < .001; all comparisons; Figure 1A). Furthermore, participants in the TBI+PTSD and PTSD groups had significantly worse FOSQ-10 scores (ie, lower scores) compared to both the TBI and neither groups (P < .001; all comparisons; Figure 1B). However, in both cases, no differences were detected between the neither and TBI groups, as well as the PTSD and TBI+PTSD groups. There were also significant positive correlations between RPQ and ISI scores (r = .53, P < .001; Figure 1C) in participants with TBI, as well as between PCL-5 and ISI scores (r = .46; P < .001; Figure 1D) in participants with PTSD.

Sleep disturbances and correlation with postconcussive and PTSD symptom severity.

(A) Symptom severity for insomnia determined by ISI scores (0 to 28, higher = worse insomnia). (B) Functional outcomes of sleep, determined by the FOSQ-10 (5–40, lower = worse outcomes). For both A and B, participants in the TBI+PTSD group (black bar, n = 58) or PTSD group (dark gray bar, n = 106) had significantly worse scores than those in the TBI group (light gray bar, n = 59) or neither group (white bar, n = 326). Symbols indicate statistical significance: * = P < .05 versus neither group, † = P < .05 versus TBI group. (C) The correlation between ISI scores and postconcussive symptom severity determined by the RPQ (n = 106, r = .53, P < .001). (D) PTSD symptom severity determined by the PCL-5 (n = 164, r = .46, P < .001). The number of participants reported for each group are slightly less than group totals presented elsewhere due to participants not completing or missing specific questions that preclude obtaining a meaningful total score. FOSQ-10 = Functional Outcomes of Sleep Questionnaire-10, ISI = Insomnia Severity Index, PCL-5 = PTSD Checklist for DSM-5, PTSD = posttraumatic stress disorder, RPQ = Rivermead Post Concussion Questionnaire, TBI = traumatic brain injury.

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Figure 1

Sleep disturbances and correlation with postconcussive and PTSD symptom severity.

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With respect to current sleep medication usage (Table 1), there were few overall differences observed across groups. The PTSD group reported a significantly higher usage of “any sleep medication” compared to the neither group (P < .001), but no differences were seen between the TBI, PTSD, and TBI+PTSD groups. There was a higher rate of sedative-hypnotic use in the PTSD and TBI-PTSD group compared to the neither group, as well as a higher rate of quetiapine use in the TBI+PTSD group compared to the neither, TBI, and PTSD groups (P < .001; all comparisons) (data not shown).

Pain

Self-reported current pain intensity was significantly higher in the TBI (P < .05), PTSD (P < .001), and TBI+PTSD (P < .001) groups compared to the neither group (Figure 2A). However, the TBI+PTSD group also reported significantly higher pain scores than both the TBI (P < .001) and PTSD (P < .05) groups. There were also significant positive correlations between the RPQ and pain scores (r = .42, P < .001; Figure 2B) in participants with TBI, as well as between the PCL-5 and pain scores (r = .30; P < .001; Figure 2C) in participants with PTSD.

Pain intensity and correlation with postconcussive and PTSD symptom severity.

(A) Current pain intensity determined by the PROMIS Global Health Survey item 7 score (0–10, higher = worse pain). Participants in the TBI+PTSD group (black bar, n = 58) had significantly higher scores than participants in the TBI group (light gray bar, n = 64) or the neither group (white bar, n = 356). Participants in the PTSD group (dark gray bar, n = 118) also scored higher than the neither group. Symbols indicate statistical significance: * = P < .05 versus neither group, † = P < .05 versus TBI group, ‡ = P < .05 versus PTSD group. (B) The correlation between pain intensity and postconcussive symptom severity determined by the RPQ (n = 117, r = .42, P < .001). (C) PTSD symptom severity determined by the PCL-5 (n = 188, r = .30, P < .001). The number of participants reported for each group are slightly less than group totals presented elsewhere due to participants not completing or missing specific questions that preclude obtaining a meaningful total score. PCL-5 = PTSD Checklist for DSM-5, PTSD = posttraumatic stress disorder, RPQ = Rivermead Post Concussion Questionnaire, TBI = traumatic brain injury.

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Figure 2

Pain intensity and correlation with postconcussive and PTSD symptom severity.

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With respect to current pain medication usage (Table 1), no differences were observed in “any pain medications” analyzed across groups. However, we did detect a higher usage of oxycontin in the TBI group compared to the neither group (P = .016), and a higher usage of topical lidocaine in the TBI group compared to the neither group (P = .007) (data not shown).

The Relationship Between Sleep Disturbances and Pain

The relationship between pain scores and ISI showed significant correlations within each group, albeit no differences were detected in the slopes of these relationships (Figure 3A). The TBI group had the highest correlation coefficient (r = .37, P = .005), followed by the TBI+PTSD group (r = .30, P = .022), the neither group (r = .293, P < .001), and the PTSD group (r = .22, P = .024). Similarly, all groups showed a significant correlation between pain scores and the FOSQ-10, albeit without differences in the slopes of these relationships (Figure 3B): the PTSD group had the highest correlation coefficient (r = −.35, P < .001), followed by the TBI+PTSD group (r = −.30, P = .021) the TBI group (r = −.22, P = .076), and the neither group (r = .22, P < .001).

Correlation of sleep disturbances and pain intensity.

Sleep disturbances, as measured by ISI and FOSQ-10 scores, plotted against pain scores. Groups are represented as follows: neither = open symbols and dashed line, TBI = light gray shaded symbols and line, PTSD = dark gray symbols and line, TBI+PTSD = filled symbols and solid line. (A) ISI scores showed a statistically positive correlation with pain scores in all groups (neither: n = 324, r = .30, P < .001; TBI: n = 58, r = .37, P = .005; PTSD: n = 105, r = .22, P = .024; TBI+PTSD: n = 58, r = .30, P = .022). (B) FOSQ-10 scores showed a statistically negative correlation in all groups (neither: n = 359, r = −.22, P < .001; TBI: n = 64, r = −.22, P = .076; PTSD: n = 123, r = −.35, P < .001; TBI+PTSD: n = 60, r = −.30, P = .021). Random jitter between −0.25 and 0.25 was applied to pain and ISI data points for illustrative purposes in order to avoid overlapping data points. The number of participants reported for each group are slightly less than group totals presented elsewhere due to participants not completing or missing specific questions that preclude obtaining a meaningful total score. FOSQ-10 = Functional Outcomes of Sleep Questionnaire-10, ISI = Insomnia Severity Index, PTSD = posttraumatic stress disorder, TBI = traumatic brain injury.

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Figure 3

Correlation of sleep disturbances and pain intensity.

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Headache, Photosensitivity, and Phonosensitivity

Although not a primary outcome variable, headaches are a very common manifestation of pain following TBI. Therefore, we examined rates of headaches in this population, and found significantly higher rates of self-reported headache in the PTSD (P = .007) and TBI+PTSD (P < .001) groups compared to the neither group (Figure 4A). Participants in the PTSD (P = .016) and TBI+PTSD (P < .001) groups also reported a significantly increased frequency of headache (in days per month) compared to the neither group (Figure 4B).

Prevalence of headaches.

(A) Proportion of participants who reported experiencing chronic headaches and (B) frequency of headache. PTSD (n = 109; χ2 = 10.61, P = .001) and TBI+PTSD (n = 59; χ2 = 20.89, P < .001) groups reported significantly more headaches than the neither group (n = 343). The TBI group (n = 59) did not significantly differ from any other group. The number of participants reported are slightly less than group totals presented elsewhere due to participants not completing or missing specific questions relating to their headache characterization.

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Figure 4

Prevalence of headaches.

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Similarly, photosensitivity (Figure 5A) and phonosensitivity (Figure 5B) are also common manifestations following TBI and may indicate lower pain thresholds in this population. These parameters (part of the RPQ) were assessed on a 5-point Likert scale, and were phrased as “light sensitivity, easily upset by bright light” and “noise sensitivity, easily upset by loud noise.” The TBI+PTSD group showed the worse (ie, the highest) photosensitivity score compared to the PTSD, TBI and neither groups (P < .001; all comparisons). Furthermore, the PTSD group had significantly worse scores than the TBI and neither groups, as well as the TBI group compared to the neither group (P < .001; all comparisons). A similar pattern was observed with respect to phonosensitivity, with the PTSD and TBI+PTSD group reporting the higher scores compared to the neither and TBI groups (P < .001; all comparisons). Again, similar to the photosensitivity data, the TBI group reported higher phonosensitivity compared to the neither group (P < .001).

Photosensitivity and phonosensitivity.

Participants self-reported (A) photosensitivity and (B) phonosensitivity scores (0 to 4, higher = greater sensitivity). Participants in the TBI+PTSD group (black bar, n = 57) had significantly higher photosensitivity scores than all other groups, and participants with PTSD (dark gray bar, n = 88) or TBI+PTSD had significantly higher phonosensitivity scores than the TBI (light gray bar, n = 54) and neither groups (white bar, n = 277). Symbols indicate statistical significance: * = P < .05 versus neither group; † = P < .05 versus TBI group; ‡ = P < .05 versus PTSD group. The number of participants reported is slightly less than group totals presented elsewhere due to participants not completing or missing specific questions relating to their photosensitivity and phonosensitivity.

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Figure 5

Photosensitivity and phonosensitivity.

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Polysomnography

Overnight PSG data (Table 3) from each participant was analyzed using a one-way ANCOVA while controlling for age and PSG type (full-night diagnostic, split-night, or full-night PAP titration study). There were no statistically significant differences between groups in sleep latency, heart rate, sleep stage transitions, total sleep time, sleep efficiency, amount of REM sleep, total NREM sleep, amount of stage N1 sleep, or amount of stage N2 sleep. There were significant group differences in WASO (P = .006), with post hoc tests revealing that the TBI+PTSD group was significantly lower than the neither group (P = .039). We also found group differences in time spent awake (P = .004), with the TBI+PTSD group being significantly lower than the neither group (P = .040). Last, although overall amounts of stage N3 sleep were low, there was a significant difference (P < .001) with the TBI+PTSD group being significantly higher than the neither group (P < .001).

PSG metrics.

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Table 3

PSG metrics.

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Multiple Linear Regression Analyses

In order to better explore the relationship between TBI, PTSD, sleep, and pain, multiple regression models were employed. Three models were developed based on primary outcome variables, including current pain intensity, ISI, and FOSQ-10 scores (Table 4). Predictor variables across all outcome variables included RPQ, PCL-5, sleep and pain medication usage, and number of TBIs sustained. Additional predictor variables depending on the outcome variable of interest included pain intensity, ISI scores, and FOSQ-10 scores. While predicting current pain intensity based on ISI, FOSQ-10, RPQ, PCL-5, sleep and pain medication usage, and number of sustained TBIs, a significant regression equation was found (F = 24.27, P < .001, R2 = .282). We found that ISI, RPQ, and pain medication usage significantly contributed to the model (P < .01), all of which increased predicted current pain intensity. After standardizing the resulting beta coefficients, ISI and RPQ appeared to be the strongest contributors to the model. When predicting ISI scores using current pain intensity, RPQ, PCL-5, sleep and pain medication usage, and number of sustained TBIs, a significant regression equation was found (F = 31.48, P < .001, R2 = .414). Predicting FOSQ-10 scores using this same model also produced a significant regression (F = 43.87, P < .001, R2 = .406). For both ISI and FOSQ-10, we found that PCL-5, current pain intensity, RPQ score, and sleep medication usage all significantly contributed to the model (P < .01). After standardizing the resulting beta coefficients, PCL-5 score appeared to be the strongest contributor.

Multivariate regression analyses.

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Table 4

Multivariate regression analyses.

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DISCUSSION

This study sought to explore the complex relationship between sleep disturbances and pain within a large sample of Veterans with TBI, PTSD, and comorbid TBI and PTSD (ie, TBI+PTSD). Self-reported sleep disturbances were the worst in Veterans with PTSD and comorbid TBI and PTSD. Thus, these data suggest that PTSD may be a stronger contributor to the development of sleep disturbances compared to TBI in this patient population, and that those with comorbid TBI and PTSD do not show a potentiation in sleep disturbances. However, self-reported current pain intensity showed a different relationship in that Veterans with comorbid TBI and PTSD reported the worst pain (including more frequent headaches and worse photosensitivity and phonosensitivity). Furthermore, Veterans with only TBI or PTSD reported the same degree of pain intensity, despite those with PTSD reporting worse photosensitivity and phonosensitivity. Accordingly, TBI status appears to be a stronger contributor to pain intensity. Our multiple linear regression models demonstrated that pain scores were predicted by ISI, RPQ, and pain medication usage. Both of our self-report sleep measures (ISI and FOSQ-10) were predicted by current pain intensity, PCL-5, RPQ, and sleep medication usage. The contribution of pain and sleep medications in these models likely reflects the underlying need to treat the underlying problem.58,59

Although previous research has documented a high prevalence of sleep disturbances and pain co-occurring in Veterans with TBI and with PTSD,37,45,60 to our knowledge, previous research has not yet demonstrated how the comorbidity of TBI and PTSD can exacerbate or influence the persistence of these sequelae more than 10 years postinjury. Collectively, our results suggest that TBI and PTSD contribute independently to sleep disturbances and current pain intensity and that Veterans that have comorbid TBI and PTSD show potentiation of these symptoms.

Comorbid TBI and PTSD Is Associated With More Sleep Disturbances

Veterans with TBI and PTSD reported the most severe insomnia (ie, highest ISI score) and the worst quality of life due to poor sleep (ie, lowest FOSQ-10 score). However, the TBI and PTSD group did not differ statistically from the PTSD group, suggesting that PTSD may be a primary contributor of sleep disturbances in Veterans with both TBI and PTSD. Additionally, PCL-5 scores were a significant contributor to sleep disturbances according to our multiple linear regression models. These results mirror several previous studies, including a recent one by Lew et al. examining sleep disturbances in a sample of 200 OEF/OIF Veterans.60 Lew et al. found that Veterans with the polytrauma clinical triad (ie, TBI, PTSD, and pain) reported more sleep disturbances than Veterans in whom a single disorder was diagnosed, and that PTSD was the most significant predictor of sleep complaints. However, these authors also concluded that TBI and pain “were separately and independently interacting with PTSD or amplifying” its effect on sleep impairments. Although we found that the TBI group curiously did not show worse self-reported or objective sleep compared to participants in the control group, this could be due to a number of factors specific to our population. The most likely explanation is that participants in our neither group were also recruited from the sleep clinic and thus, were referred due to sleep complaints. Other potential contributors could be that Veterans with TBI were all in the chronic phase of recovery from their injury (an average of approximately 21 years postinjury), as well as our focus on insomnia symptoms, compared to other more sleep-specific questionnaires with more granularity.

Nevertheless, we did find a positive correlation between RPQ (postconcussive symptom severity) and ISI scores in our sample of Veterans with TBI. These results are in agreement with several previously published studies that show postconcussive symptoms are correlated with sleep disturbances.6163 We also found a positive correlation between PCL-5 scores (PTSD symptom severity) and ISI scores. This too mirrors several other studies demonstrating that PTSD symptom severity is associated with increased sleep disturbances.6466 It is important to note that our PSG data does not directly support greater sleep disturbances in Veterans in the TBI, PTSD, and TBI+PTSD groups, which on average had a lower WASO and more stage N3 sleep compared to Veterans in the neither group. This could be due to the well documented and paradoxical “first-night effect” that was likely present in our population, where people with insomnia, unlike those without insomnia, have a tendency to sleep better during the first night in a sleep laboratory.67 Due to the night-to-night variability seen in PSG data, consecutive overnight studies would be helpful to evaluate whether the first-night effect is contributing to group differences in sleep metrics in the TBI+PTSD group.

Comorbid TBI and PTSD Is Associated With Worse Pain

The TBI+PTSD group also self-reported greater pain compared to all other groups. This was not surprising, as there was a strong correlation between RPQ/PCL scores and pain scores, suggesting both conditions contribute to increased pain. Furthermore, both the TBI and PTSD groups scored significantly higher than the neither group, suggesting that each of these conditions independently contributes to increased pain. Nevertheless, our multiple linear regression models implicate sleep disturbances and TBI symptom severity to be primary contributors to the development of pain. Despite significant group differences in age, age was not applied as a covariate in our analyses given that age is known to be positively correlated with pain,6870 yet we found an inverse relationship such that the TBI+PTSD group was the youngest group but reported the worst pain. Although previous research has reported similar findings,7176 these data are the first to report the persistence of pain in Veterans in the chronic phase of recovery from TBI (average duration since last TBI was approximately 23 years in the TBI group and 19 years in the TBI+PTSD group).

Similar results were obtained with headache frequency and photosensitivity and phonosensitivity, all of which commonly co-occur with pain. With respect to headache, 73% of Veterans with TBI and PTSD self-reported experiencing a headache in the previous 30 days, and 34% self-reported they experienced headaches on more than half of the days in the past month. Photosensitivity and phonosensitivity are known symptoms of TBI, and previous research has found that these symptoms can persist for several months after the initial injury.47,77,78 However, photosensitivity and phonosensitivity have not been examined in a large cohort of Veterans with comorbid TBI and PTSD, with separate comparison groups of Veterans with only TBI or PTSD. Thus, the current study extends recent work by our group that reports an increased incidence of photosensitivity and phonosensitivity in Veterans with TBI who were also in the chronic phase of recovery of their injury.79 This previous work also showed a connection between sleep disturbances, which were possibly driven by autonomic nervous system hyperarousal, and photosensitivity and phonosensitivity.79 We found that Veterans with TBI or PTSD reported higher levels of light and noise sensitivity, and that the TBI+PTSD group reported the highest levels. This is especially interesting because of the scarcity of research examining the relationship between PTSD and sensory sensitivity, although there have been other studies that suggest PTSD can exacerbate postconcussive symptoms in individuals with a history of TBI, which may include sensory hypersensitivity.72 Of note, both current pain intensity and increased light sensitivity are also common complaints of patients with fibromyalgia80,81 and chronic migraines,82,83 which have both been linked to the sensitization of pain-processing circuits.8486 Further studies are needed to determine whether photosensitivity and/or phonosensitivity could be a useful marker to predict central sensitization of pain in Veterans with TBI and PTSD.

Correlation Between Sleep Disturbances and Pain

It is well established that sleep disturbances and pain are inextricably linked. In the current study we found that Veterans with TBI or comorbid TBI and PTSD had the strongest correlation between ISI and pain scores, but there was also a significant positive correlation between these scores in the PTSD and neither groups. We found similar results when correlating FOSQ-10 and pain scores, with the PTSD and TBI+PTSD groups displaying the strongest correlations, followed by the TBI and neither groups. These results reaffirm the well-established connection between increased sleep disturbances and pain,87,88 but also suggest this link may be even stronger in those with comorbid TBI and PTSD. Although disentangling this relationship and determining cause and effect is challenging, the current consensus explanation includes a bidirectional relationship between sleep disturbances and pain. Several animal studies have shown that sleep deprivation and reduced REM sleep can induce hyperalgesia in mice and rats.8991 Studies on humans are consistent with this idea. For example, the self-reported quality of sleep in patients with severe burn injuries was a significant predictor for pain intensity the following day,92 which replicated a comparable study on patients with rheumatoid arthritis.93 But the converse is also true: pain can lead to poor sleep. Previous work on patients with fibromyalgia indicated that pain intensity predicted their quality of sleep and suggested that this may be mediated by increased attention to pain.94 Thus, a mutual relationship exists, in which one disorder increases the symptoms of the other, and this vicious cycle may be exceptionally severe in Veterans with the polytrauma clinical triad.60

Limitations

The current study demonstrates strong evidence that Veterans with both TBI and PTSD are at greater risk for experiencing sleep disturbances and pain than Veterans with either TBI or PTSD. However, limitations of our study include caveats that come with correlational analyses, including inference of causality between these variables. Our study is also reliant on self-reported data, rather than objective methods of quantifying sleep impairments and pain. Although both are relevant, self-reported data for these metrics are potentially of greater importance because ultimately it reflects how the individual patient perceives these symptoms. However, the ISI has been repeatedly validated as an accurate assessment to quantify insomnia severity by comparing results obtained from sleep diaries, observations from significant others and clinicians, and PSG.50,95,96 Other survey instruments used here have also been well validated.47,48,5355,96 Nevertheless, in order to address the limitations of self-reported data, our future studies will be using objective pain testing combined with functional neuroimaging in our cohort of Veterans with TBI, PTSD, and TBI and PTSD to more precisely quantify pain in this patient population.

It is also possible that a third independent variable, such as comorbid depression, could influence symptom severity and contribute to sleep disturbances and pain.97100 Previous research has implicated that individuals with pain and depression may be excessively attending to external or internal stimuli,94,101 and mind-body interventions could be particularly effective in treating these patients.102 Additionally, comorbid substance use disorder would likely also contribute to a combination of worse sleep disturbances and pain.103 Future analyses could collect data on mood disorders and substance use disorder, and explore potential mediators and moderators between these relationships.

Finally, regarding other factors that might potentially contribute to group differences in this study, we were unable to match groups on age; the trauma-exposed groups (TBI, PTSD, and TBI+PTSD) were all significantly younger than the neither group. However, because pain intensity and sleep disturbances are positively correlated with age (eg, the opposite of our effect), using age-matched groups would likely show similar, if not more pronounced, results as the current study. It is also worth noting that our TBI+PTSD group experienced more TBIs than our TBI alone group (2.94 versus 1.99). For this reason, the number of TBIs was included as a predictor variable in our multivariate linear regression models but did not present as a significant contributor. However, the number of TBIs experienced does increase the risk for comorbid PTSD, and for this reason it may be difficult to dissociate this as an independent factor. The current study is limited in the ability to strictly characterize TBI severity given the chronic nature of the injury and lack of necessary details in participants' medical records.

CONCLUSIONS

The current study demonstrates that Veterans with comorbid TBI+PTSD report worse pain compared to Veterans with only TBI or PTSD, and their sleep disturbances and pain complaints are strongly correlated with TBI and PTSD symptom severity. Sleep disturbances appear to be primarily driven by pain and PTSD symptom severity, whereas pain appears to be primarily driven by sleep disturbances and TBI symptom severity. Clearly, additional work is needed to elucidate cause and effect, and better understand how each of these factors, including unidentified comorbid conditions, are contributing. Veterans with TBI and PTSD were especially vulnerable to common manifestations of pain including persistent headaches and photosensitivity and phonosensitivity. Future research should examine how TBI and PTSD interact with one another to exacerbate these symptoms and develop more effective treatments for those with TBI and PTSD. Our results, in combination with our planned future studies and basic science approaches to understanding the neurobiology underlying these phenomena (eg, rodent models of TBI/PTSD conducted in parallel), will be critical to a better understanding and design of more effective interventions for sleep and pain problems after polytrauma.

DISCLOSURE STATEMENT

All authors have seen and approved this manuscript. Work for this study was performed at VA Portland Health Care System, Portland, OR. This material is the result of work supported with resources and the use of facilities at the VA Portland Health Care System, VA Career Development Award #IK2 BX002712, NIH EXITO Institutional Core, # UL1GM118964, and the Portland VA Research Foundation to M.M.L.; N.I.H. T32 AT 002688 to J.E.E.; VA OAA Post-doctoral Nursing Research Fellowship to K.B.W.; and Department of Defense award #D01 W81XWH-17-1-0423 to M.M.H. and M.M.L., awarded and administered through the US Army Medical Research Acquisition Activity, Fort Detrick, MD. Interpretations and conclusions are those of the authors and do not represent the views of the U.S. Department of Veterans Affairs or the United States Government. The authors report no conflicts of interest.

ABBREVIATIONS

ANOVA

analysis of variance

ANCOVA

analysis of covariance

BMI

body mass index

FOSQ-10

Functional Outcomes of Sleep Questionnaire-10

ISI

Insomnia Severity Index

NREM

non-rapid eye movement

OEF/OIF

Operation Enduring Freedom/Operation Iraqi Freedom

OSA

obstructive sleep apnea

TBI

traumatic brain injury

PAP

positive airway pressure

PCL-5

Posttraumatic Stress Disorder Checklist for DSM-5

PCS

postconcussive syndrome

PROMIS

Patient-Reported Outcomes Measurement Information System

PSG

polysomnography

PTSD

posttraumatic stress disorder

REM

rapid eye movement

RPQ

Rivermead Post Concussion Questionnaire

TST

total sleep time

VAPORHCS

Veteran Affairs Portland Health Care System

WASO

wake after sleep onset

ACKNOWLEDGMENTS

The authors express their sincere appreciation and gratitude for those who participated in this study, to the staff at the VA Portland Health Care System Sleep Disorders Clinic, and to Yvonne Barsalou, Alex Q. Chau, and Dennis Pleshakov for assistance with data collection and entry.

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