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JAIDS Journal of Acquired Immune Deficiency Syndromes:
doi: 10.1097/QAI.0b013e31829d63ab
Clinical Science

Evaluating Sleep and Cognition in HIV

Gamaldo, Charlene E. MD*; Gamaldo, Alyssa PhD; Creighton, Jason BA*; Salas, Rachel E. MD*; Selnes, Ola A. PhD*; David, Paula M.*; Mbeo, Gilbert MD*; Parker, Benjamin S. BS*; Brown, Amanda PhD*; McArthur, Justin C. MBBS, MPH*,‡; Smith, Michael T. PhD§

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Author Information

*Department of Neurology, Johns Hopkins University, Baltimore, MD;

Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD;

Departments of Pathology, Epidemiology, and Medicine, Johns Hopkins University, Baltimore, MD; and

§Department of Psychiatry and Behavioral Medicine, Johns Hopkins University, Baltimore, MD.

Correspondence to: Charlene E. Gamaldo, MD, The Johns Hopkins Hospital, 600 N. Wolfe St., Meyer 6-119, Baltimore, MD 21287 (e-mail: cgamald1@jhmi.edu).

Supported by grant number UL1 RR 025005 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research. This study was also supported by award 5P30MH075673-S02 from the National Institute of Mental Health (NIMH) (principal investigator, J.C.M.), a Developmental Grant from JHU NIMH Center for Novel Therapeutics of HIV-associated Cognitive Disorders (to author C.E.G., principal investigator, J.C.M.), and a Developmental Grant from JHU Center for Mind-Body Research (PI Jennifer Haythornthwaite PI to author C.E.G.). The recruitment of participants was assisted by an existing cohort, funded by NIMH, the Central Nervous System HIV Antiretroviral Therapy Effects Research (CHARTER). The project described was supported by the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant UL1 RR 025005.

Its contents are solely the responsibility of the authors and do not necessarily represent the official view of NCRR or NIH. Information on NCRR is available at http://www.ncrr.nih.gov/.

The authors have no conflicts of interest to disclose.

Received February 27, 2013

Accepted May 20, 2013

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Abstract

Objective: To examine the relationship between measures of sleep quality and cognitive performance in HIV-positive individuals stable on combination antiretroviral therapy.

Design: Multimethod assessments of sleep quality, patterns, and cognitive performance were assessed in a predominantly black HIV-positive cohort.

Methods: Sleep quality and patterns were characterized in 36 subjects by polysomnogram, 2-week actigraphy monitoring, and validated sleep questionnaires. Cognitive performance was assessed with a battery of neuropsychological tests.

Results: The majority of participants were cognitively impaired [based on Frascati (75%) criteria]. Self-reported mean scores on the Pittsburgh sleep quality index and the insomnia severity scale suggested poor sleep quality. Better cognitive performance, particularly on tasks of attention, frontal/executive function, and psychomotor/motor speed, was associated with polysomnogram sleep indices (ie, reduced wake after sleep onset, greater sleep efficiency, greater sleep latency, and greater total sleep time). Thirty-seven percent of participants had sleep patterns suggestive of chronic partial sleep deprivation, which was associated with significantly worse performance on the digit symbol test (P = 0.006), nondominant pegboard (P = 0.043), and verbal fluency tests (P = 0.044).

Conclusions: Our results suggest that compromised sleep quality and duration may have a significant impact on cognitive performance in HIV-positive individuals. Future studies are warranted to determine the utility of sleep quality and quantity indices as potential predictive biomarkers for development and progression of future HIV-associated neurocognitive disorder.

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INTRODUCTION

Combination antiretroviral therapy (cART) has led to dramatic increases in the survival rate of individuals infected with HIV. Although significant strides have been made in managing several acute and life-threatening HIV-related conditions, significant challenges remain in managing the chronic HIV-specific and nonspecific conditions facing an aging HIV patient population. HIV-associated neurocognitive disorder (HAND) prevalence remains as high as 50%,1–3 even amongst individuals with optimally controlled viral loads and immune function due to cART. The importance of identifying predictive biomarkers of HAND now parallels the importance placed on identifying predictive markers of dementia within the general population.1

Sleep disorders have also been recently identified as a common and debilitating condition for HIV-positive individuals in the post-cART era with a reported prevalence ranging from 30% to 73%,4 as compared with 10%5 prevalence in the general population. These may be among the earliest complications for all seropositive patients, both symptomatic and asymptomatic.6–8 In addition to sleep complaints, neurocognitive deficits, affective disorders, and substance use/abuse have also been identified as common comorbid conditions amongst HIV-seropositive individuals. Studies in the general population suggest a potential correlation between poor sleep quality and/or quantity with reduced neurocognitive performance,9,10 ranging from global measures of overall cognition and mood to more specific cognitive tasks related to attention, vigilance, and decision-making skills (including risk-taking behaviors, such as gambling, aggressive driving, and recreational drug use and relapse rate).11–15 Studies specifically looking at this interrelationship in the HIV-positive subpopulation are timely and may help to shed additional insight on the complex interplay between these variables.

Studies in the general population have also shown a great deal of intrasubject and intersubject variability in sleep-wake patterns and vulnerability to sleep loss.16 Moreover, sleep characteristics also seem to be affected by cultural, gender, and socioeconomic demographics. For this reason, we designed a prospective study utilizing multimethod sleep assessments and observations across several time points. To our knowledge, this investigation represents the most comprehensive evaluation to-date of sleep-wake patterns in an HIV-positive population stable on cART. We hypothesized that sleep disruption severity would be associated with reduced performance on tasks of executive function.

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METHODS

Thirty-six HIV-positive participants stable on cART (with the exception of efavirenz due to its potential sleep-altering effects)17 were recruited at Johns Hopkins Medical Institutions to participate in this institutional review board–approved study. A full medical evaluation was conducted to ensure that the participant was medically (including a demonstration of HIV viral loads of ≤1000 copies/mL), cognitively, and psychologically (per physician interview or response on validated mood questionnaires) stable to participate. Participants were excluded if currently prescribed opiate medications or if any changes had been made to their pharmacotherapeutic regimen in the last 60 days. Participants were also dropped from the study if they screened positive for recreational drug use at study entry, midpoint, or exit interview. Participants received a validated clinical sleep interview along with validated sleep questionnaires, including the insomnia severity index18 and the Epworth sleepiness scale (ESS).19 A polysomnogram (PSG) was conducted in the Johns Hopkins Clinical Research Unit followed by 2-week in-home functional assessments with questionnaires and actigraphy monitoring of their sleep and wake activity.

Findings for this report were generated from a larger prospective study evaluating the relationship of sleep and pertinent measures of overall function in a HIV-seropositive cohort. The overall protocol for the study is outlined in Table 1; readers can also refer to a previously published report for a more detailed description of the complete research design and sleep methods.25

Table 1
Table 1
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Neuropsychological Testing

Neurocognitive testing was performed on the final day (day 14) of the protocol and consisted of a comprehensive neuropsychological battery aimed at evaluating several cognitive domains (ie, psychomotor speed, verbal memory, visual memory, frontal/executive, and motor speed) shown to be sensitive to sleep loss in previous general population studies11,12,25 (Table 2).

Table 2
Table 2
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Determination of overall cognitive/neuropsychological functioning was based on a calculated global composite score. Global scores were calculated by averaging the scores from the 10 neuropsychological tests and their subtest scores (Table 2), which were each standardized using Z-scores based on normative data stratified by age and education.34,35 Normative data, for participants with less than or equal to 12 years of education, were derived from the AIDS Link to Intravenous Experience study.34–36 For participants with greater than 12 years of education, normative data were based on the Multicenter AIDS Cohort Study (MACS).36 For neuropsychological subtests not included in the AIDS Link to Intravenous Experience study and the MACS neuropsychological batteries, normative data were based on published data for the Halstead–Reitan battery.37 Using the global neuropsychological score, participants were placed in 1 of several categories [ie, normal, asymptomatic neurocognitive impairment (ANI), minor neurocognitive disorder, and HIV-associated dementia] as defined by the Frascati criteria.

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Functional Measure

In an effort to capture the impact of cognitive deficits on physical functioning, the role functioning items of the Medical Outcomes Study38 were administered to all HIV-seropositive participants.

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Statistical Analyses

Descriptive analyses were conducted to characterize each participant’s demographics, health, cognitive functioning, and sleep patterns. Pearson correlations explored potential relationships between the sleep indices and neuropsychological measures. Due to evidence supporting an association between CD4 nadir and risk of developing HAND,39 partial correlations were conducted to determine whether any significant relationships from our initial correlations remained significant after accounting for CD4 nadir and the HIV medical outcomes study total score. Correlations were 2-tailed with an α level of 0.05. The t tests were conducted to explore whether there were sleep differences between the cognitively unimpaired and impaired HIV-seropositive adults. When Levene test for equality of variances was violated, t tests with unequal variances were conducted. Although several analyses were conducted, the analyses did not control for multiple comparisons because such an approach increases Type II error or decreases the likelihood for observing a significant relationship.40 Given that the relationship between sleep and cognition in HIV is a relatively unexplored area of research, our study’s objective was to take an exploratory approach, identifying potential relationships which future studies can subsequently investigate using alternative more conservative approaches. Analyses were performed using the Statistical Package for Social Sciences (SPSS) Version 17.40

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RESULTS

Clinical Characteristics

Table 3 shows the demographic, health, and neuropsychological test scores of the sample. Two participants were terminated from the study and excluded from analysis due to positive drug toxicology—1 at the mid-protocol follow-up visit and the other at the final visit. Participants were between the ages of 38 and 63 years (mean = 49.89; SD = 6.07) and were predominantly black males, with 50% of the participants having less than or equal to a high school education. On aggregate, participants were within normal levels for fatigue, depression, and anxiety. A majority of the participants, however, were considered mildly impaired according to their global score based on the Frascati criteria.39 Given the limited sample size, 2 groups were created for each measure and included in the analyses [Frascati: impaired (ie, ANI, minor neurocognitive disorder and HIV-associated dementia) = 75.0% vs. unimpaired (ie, normal) = 25.0%].

Table 3
Table 3
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Sleep Parameters

The mean Pittsburgh sleep quality index score was suggestive of “poor sleep” based upon the commonly used cutoff score of 5 and mean scores for the ESS and insomnia severity index in the abnormal range (Table 4). The mean apnea–hypopnea index on the PSG was 9.09, representing a mild level of apnea severity (Table 3). The average PSG sleep latency for the participant sample was relatively low (M = 9.42 min) and well within the established normal limits of less than 30 minutes.41 Paired t tests demonstrated reduced sleep quality during the 2-week actigraphic home monitoring as compared with the single-night inpatient PSG monitoring based on several objective markers of overall sleep architecture. The mean actigraphy sleep latency (46.30 ± SE = 5.60) was significantly greater than mean PSG latency [10.02 ± SE = 1.71; t (32) = 6.02, P = 0.000], and mean actigraphy sleep efficiency (66.71 ± SE = 2.21) (sleep efficiency = total sleep time/time in bed × 100) was significantly worse than mean PSG sleep efficiency [82.06 ± SE = 1.61; t (32) = −5.73, P = 0.000]. In addition, mean PSG sleep duration (406.88 ± 11.58) was significantly longer than mean actigraphic sleep duration [343.08 ± 14.10; t (32) = −3.95, P = 0.000]. Mean actigraphy wake after sleep onset time (WASO) minutes (88.87 ± SE = 6.86) trended higher than mean PSG WASO (77.14 ± SE = 7.26), but was not significantly different [t (32) = 1.18, P = 0.245]. A subgroup of 13 participants demonstrated a markedly reduced PSG sleep latency (<5 minutes) and a much greater PSG total sleep time (408.39 ± 29.08) compared with their mean actigraphic sleep duration (305.86 ± 24.55) recorded over the 2-week outpatient observation. Such a marked reduction in sleep latency and increased total sleep time on the PSG during a stay in the sleep research unit as compared to a home environment is consistent with individuals experiencing chronic partial sleep deprivation due to self-imposed or environmental factors. Our analyses also found that participants with a PSG sleep latency of <5 minutes (11.40 ± 1.63) had significantly greater ESS scores the morning after the PSG compared with the participants with PSG sleep latencies between 5 and 30 minutes [4.18 ± 1.49; t (19) = 3.27, P = 0.004], which supports our chronic partial sleep deprivation hypothesis in the former group.

Table 4
Table 4
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Relationship Between Sleep and Neuropsychological Performance

As illustrated in Table 5, significant relationships were observed between performance on a number of neuropsychological tests and sleep architectural indices on the PSG. Greater sleep latency and reduced time WASO on PSG was associated with better performance on digit symbol test. Greater PSG sleep efficiency and reduced WASO was associated with faster performance on trails B. Greater total sleep time and sleep efficiency and reduced WASO on PSG were also associated with better performance on letter–number sequence. Last, reduced WASO was associated with better performance on the Pegboard-dominant hand task. After controlling for the CD4 nadir or HIV medical outcomes study, many of the observed relationships remained significant (Table 5). The sleep questionnaires and actigraphy indices were not significantly associated with any of the neuropsychological measures. However, after adjusting for the CD4 nadir or HIV medical outcomes study, reduced actigraphic sleep latency was associated with worse dominant Pegboard task Sequence performance. Using the Frascati categorization, the only significant difference observed between the unimpaired and impaired groups, across all sleep measures, was for the ESS [unimpaired: 12.50 ± SE = 1.43 vs. impaired: 8.69 ± SE = 0.86; t (32) = 2.18, P = 0.037], suggesting that the cognitively unimpaired tended to report more elevated levels of sleepiness than the cognitively impaired. Based on a large subset of our cohort’s demonstration of sleep patterns suggestive of chronic partial sleep deprivation, we conducted comparative group analyses of cognitive performance based on individuals with markedly short PSG sleep latency (<5 minutes) as compared with individuals with normal sleep latency (5–30 minutes). Participants with reduced sleep latencies demonstrated worse performance on digits symbol test [<5 minute: 55.54 ± 3.72 vs. 5–30 minute: 71.18 ± 3.48; t (33) = −2.92, P = 0.006], pegboard nondominant [<5 minute: 92.00 seconds ± 4.22 vs. 5–30 minute: 79.64 seconds ± 3.67; t (32) = 2.11, P = 0.043], and verbal fluency [<5 minute: 32.69 ± 2.60 vs. 5–30 minute: 41.50 ± 3.30; t (33) = −2.10, P = 0.044; Fig. 1].

Table 5
Table 5
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Figure 1
Figure 1
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DISCUSSION

Despite the widespread use of cART, cognitive impairment continues to be a prevalent concern in both symptomatic and asymptomatic individuals with chronic HIV infection.1 The relationship between sleep and cognitive performance assessed by comprehensive neuropsychological and sleep function evaluation in an HIV cohort has not been previously reported. Our results suggest that both subjective and objective indices of sleep continuity and quality may have a significant relationship with cognitive performance in HIV-positive individuals.

Furthermore, many participants demonstrated patterns strongly suggestive of chronic partial sleep deprivation, which may be the result of behaviorally induced insufficient sleep syndrome.42 According to the International Classification of Sleep Disorders-2 classification, the key diagnostic features of this syndrome refer to an individual who reports customary sleep times (at home during their “normal routine”) measured by history, sleep diary, or actigraphy which is significantly shorter than the sleep time recorded when placed in a noncustomary setting (eg, PSG in sleep research facility). Due to this self-imposed chronic partial sleep debt, when the individual is provided an ad libitum sleep opportunity in a research facility (despite the unfamiliar environment and cumbersome recording techniques), he or she will often show “supra” efficient sleep architectural patterns, including very high sleep efficiency, markedly short sleep onset latency, and minimal sleep fragmentation on PSG. Similar to the patterns characterized by those with behaviorally induced insufficient sleep syndrome, many of the individuals in our cohort demonstrated markedly reduced sleep latencies of <10 minutes with sleep efficiencies often greater than 90% on their PSGs. In turn, many of these same participants demonstrated significantly shorter sleep durations on their 2-week home monitoring compared with their PSG and much shorter durations than the recommended 7.5–8.5 hours needed for most adults to function optimally. Study participants demonstrating patterns suggestive of chronic partial sleep deprivation reported more complaints of daytime sleepiness and performed significantly poorer on several measures of cognitive function compared with participants without these suggestive patterns.

Interestingly, self-reported daytime sleepiness, based on the ESS, was significantly higher in the cognitively unimpaired group (using Frascati criteria) than in the impaired group. The ESS inquires about the likelihood of “dozing” in specific scenarios, such as while in a movie theatre or meeting or while driving. Because most of our cohort was not actively employed and did not own an automobile, these scenarios may not have occurred customarily enough for our cohort to accurately respond. Based on our findings, future studies evaluating the relationship between sleep and cognition amongst HIV-positive individuals should consider the participant’s historical sleep behaviors, attitudes, daily habits, and relevant sociodemographic factors (ie, employment and residential status, common means of transportation).

Some studies have suggested that demographics, such as female gender, age, low body mass index, and history of intravenous drug use, may increase the risk for future cognitive impairment in seropositive individuals. Overall, health status may also be a potential issue, with 2 large longitudinal cohort studies (the Central Nervous System HIV Antiretroviral Therapy Effects Research and MACS) reporting increased risk for HAND development in aviremic subjects who suffered with “incidental” comorbidities (examples include low reading level, school problems, brain trauma, history of cerebrovascular events, epilepsy, central nervous system opportunistic diseases, major depression, psychotic disorder, and substance abuse) compared with aviremic participants without these comorbidities.1,3

Obtaining ideal sleep quality and quantity is another critical component for both optimal cognitive performance and immune function.43 HIV enters the brain early after infection, and disturbances in sleep patterns during the asymptomatic stage of HIV infection were recognized and reported very early in the HIV/AIDS epidemic.44 The release of cytokines including monocyte chemoattractant protein-1 (CCL2), tumor necrosis factor alpha, interleukin (IL) 1 beta, IL-6, interferon gamma, and IL-15 in the brain is thought to lead to neuronal injury and dysfunction45 and has recently been correlated with the development of HAND.46,47 In addition, many of these same cytokines such as tumor necrosis factor alpha, IL-1, and interferon alpha can modulate sleep wake patterns and can be associated with significant sleep architectural changes.48–50 Studies are warranted to look at the effect of sleep loss on central nervous system immune activity, especially because there is evidence to suggest that sleep disruption can increase blood–brain barrier permeability for proinflammatory substances.1,51,52 Thus, identification of the sleep wake patterns and disturbances specific to HIV-positive individuals may prove fertile in furthering our understanding of HAND manifestation and suggest future preventative and therapeutic avenues.

Although this study yielded several important findings, its ability to detect subtle cognitive differences based on a 4-tiered Frascati classification may have been limited by its relatively small sample size. Conducting this type of study utilizing multimethod sleep assessments and observations across several time points requires an inordinate amount of financial and personnel resources. Even though our study sample of predominantly black males may place limits on generalizability, CDC statistics continue to show that black males are disproportionately affected by HIV as compared with other demographic groups.53 Significantly lower mean sleep durations have also been reported for black men compared with other demographic groups in general population studies,53 and similar sleep behavioral patterns suggestive of self-imposed chronic partial sleep deprivation were also revealed in our cohort. Providing counseling on the importance of adequate sleep opportunity may prove to be an effective health care management strategy. Although HIV-positive individuals undergoing treatment with efavirenz were excluded in this study to minimize confounding medication-related effects on sleep,54,55 evidence regarding the impact of efavirenz on sleep is mixed with some reports actually demonstrating no significant difference in sleep disturbance among individuals on efavirenz compared with other cART regimens.4,56 Moreover, even among the studies reporting an association between sleep disruption and efavirenz, the findings ranged from significant changes in sleep architecture in some studies although others may have only found significant differences in reports of “unusual dream.”57,58 With the wide prevalence of efavirenz use in modern cART, future studies may consider including those undergoing treatment with efavirenz to provide further insight and generalizability. Thus, we anticipate that the findings revealed in this study will serve as additional support for conducting future and larger-scale studies to evaluate the relationship between sleep and cognition across multiple demographic groups living with HIV and undergoing varying cART regimens.

Even in the context of optimally controlled viral replication (low or undetectable viral loads), patients may still continue to experience mild or asymptomatic forms of neurocognitive dysfunction at a surprisingly high rate.59 The stringent inclusion criteria and intricate protocol employed in this study certainly biased toward the inclusion of subjects who were more stable cognitively. However, individuals demonstrating even milder forms of impairment such as ANI are at higher risk for eventual progression to more severe forms of HAND.3 Moreover, deficits sufficient to impact activities of daily living that are essential for disease management, including medication adherence, have been shown in seropositive individuals, especially those younger than 50 years, regardless of their level of cognitive impairment.60 Thus, identifying confounding factors, such as sleep disturbances that might influence the manifestation of neurocognitive impairment, is critical in the post-cART era.

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ACKNOWLEDGMENT

The authors acknowledge Dr Adam Spira for his invaluable contributions to this project.

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REFERENCES

1. McArthur JC, Steiner J, Sacktor N, et al.. Human immunodeficiency virus-associated neurocognitive disorders: mind the gap. Ann Neurol. 2010;67:699–714. doi:10.1002/ana.22053.

2. Wright EJ, Nunn M, Joseph J, et al.. NeuroAIDS in the Asia Pacific Region. J Neurovirol. 2008;14:465–473. doi:10.1080/13550280802235932.

3. Heaton RK, Clifford DB, Franklin DR Jr, et al.. HIV-associated neurocognitive disorders persist in the era of potent antiretroviral therapy: CHARTER study. Neurology. 2010;75:2087–2096. doi:10.1212/WNL.0b013e318200d727.

4. Reid S, Dwyer J. Insomnia in HIV infection: a systematic review of prevalence, correlates, and management. Psychosom Med. 2005;67:260–269. doi:10.1097/01.psy.0000151771.46127.df.

5. Ram S, Seirawan H, Kumar SK, et al.. Prevalence and impact of sleep disorders and sleep habits in the United States. Sleep Breath. 2010;14:63–70. doi:10.1007/s11325-009-0281-3.

6. Norman SE, Chediak AD, Freeman C, et al.. Sleep disturbances in men with asymptomatic human immunodeficiency (HIV) infection. Sleep. 1992;15:150–155.

7. Norman SE, Chediak AD, Kiel M, Cohn MA. Sleep disturbances in HIV-infected homosexual men. AIDS. 1990;4:775–781.

8. Cruess DG, Antoni MH, Gonzalez J, et al.. Sleep disturbance mediates the association between psychological distress and immune status among HIV-positive men and women on combination antiretroviral therapy. J Psychosom Res. 2003;54:185–189.

9. Banks S, Dinges DF. Behavioral and physiological consequences of sleep restriction. J Clin Sleep Med. 2007;3:519–528.

10. Jones K, Harrison Y. Frontal lobe function, sleep loss and fragmented sleep. Sleep Med Rev. 2001;5:463–475.

11. Durmer JS, Dinges DF. Neurocognitive consequences of sleep deprivation. Semin Neurol. 2005;25:117–129.

12. Killgore WD, Balkin TJ, Wesensten NJ. Impaired decision making following 49 h of sleep deprivation. J Sleep Res. 2006;15:7–13.

13. Drummond SP, Paulus MP, Tapert SF. Effects of two nights sleep deprivation and two nights recovery sleep on response inhibition. J Sleep Res. 2006;15:261–265.

14. Harrison Y, Jones K, Waterhouse J. The influence of time awake and circadian rhythm upon performance on a frontal lobe task. Neuropsychologia. 2007;45:1966–1972.

15. Bolla KI, Lesage SR, Gamaldo CE, et al.. Polysomnogram changes in marijuana users who report sleep disturbances during prior abstinence. Sleep Med. 2010;11:882–889. doi: 10.1016/j.sleep.2010.02.013.

16. Van Dongen HP, Baynard MD, Maislin G, et al.. Systematic interindividual differences in neurobehavioral impairment from sleep loss: evidence of trait-like differential vulnerability. Sleep. 2004;27:423–433.

17. Moyle G, Fletcher C, Brown H, et al.. Changes in sleep quality and brain wave patterns following initiation of an efavirenz-containing triple antiretroviral regimen. HIV Med. 2006;7:243–247.

18. Bastien CH, Vallieres A, Morin CM. Validation of the insomnia severity index as an outcome measure for insomnia research. Sleep Med. 2001;2:297–307.

19. Johns MW. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep. 1991;14:540–545.

20. Spielberger CD, Gorsuch RL, Lushene RE. Manual for State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologist Press; 1970.

21. Krupp LB, LaRocca NG, Muir-Nash J, et al.. The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol. 1989;46:1121–1123.

22. Horne JA, Ostberg O. A self-assessment questionnaire to determine morningness-eveningness in human circadian rhythms. Int J Chronobiol. 1976;4:97–110.

23. Grossman HA, Sullivan PS, Wu AW. Quality of life and HIV: current assessment tools and future directions for clinical practice. AIDS Read. 2003;13:583–590, 595–597.

24. Buysse DJ, Reynolds CF III, Monk TH, et al.. The pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28:193–213.

25. Gamaldo CE, Spira AP, Hock RS, et al.. Sleep, function and HIV: a multi-method assessment. AIDS Behav. 2013 [epub ahead of print].

26. Wechsler D. Wechsler Adult Intelligence Scale—Revised Manual. New York, NY: The Psycholgical Corporation; 1981.

27. Reitan RM, Wolfson D. The Halstead—Reitan Neuropsychological Test Battery. Tucson, AZ: Neuropsychology Press; 1985.

28. Brandt J, Benedict R. HVLT-R. Lutz, FL: Psychological Assessment Resources, Inc; 2001.

29. Benedict R. Brief Visuospatial Memory Test-Revised. Odessa, FL: Psychological Assessment Resources, Inc; 2006.

30. Heaton RK, PAR staff. WCST-64:CV2. Research Edition. Lutz, FL: Psychological Assessments Resources, Inc; 2000.

31. Benton AL, Hamsher K. Multilingual Aphasia Examination. Iowa City, IA: University of Iowa; 1976.

32. Grooved Pegboard Test. Lafayette, IN: Lafayette Instruments; 1989.

33. Blair JR, Spreen O. Predicting premorbid IQ: a revision of the national adult reading test. Clin Neuropsychol. 1989;3:129–136.

34. Marder K, Albert SM, McDermott MP, et al.. Inter-rater reliability of a clinical staging of HIV-associated cognitive impairment. Neurology. 2003;60:1467–1473.

35. Concha M, Selnes OA, McArthur JC, et al.. Normative data for a brief neuropsychologic test battery in a cohort of injecting drug users. Int J Addict. 1995;30:823–841.

36. Selnes OA, Jacobson L, Machado AM, et al.. Normative data for a brief neuropsychological screening battery. Multicenter AIDS Cohort Study. Percept Mot Skills. 1991;73:539–550.

37. Heaton R, Miler SW, Taylor MJ, et al.. A Professional Manual of the Revised Comprehensive Norms for an Expanded Halstead-Reitan Battery: Demographically Adjusted Neuropsychological Norms for African American and Caucasian Adults. Lutz, FL: Psychological Assessement Resources, Inc; 2004.

38. Stewart AL, Ware JE. Measuring Function and Well-being: The Medical Outcomes Study Approach. Durham, NC: Duke University Press; 1993.

39. Antinori A, Arendt G, Becker JT, et al.. Updated research nosology for HIV-associated neurocognitive disorders. Neurology. 2007;69:1789–1799.

40. Rothman KJ. No adjustments are needed for multiple comparisons. Epidemiology. 1990;1:43–46.

41. Hohagen F, Rink K, Kappler C, et al.. Prevalence and treatment of insomnia in general practice. A longitudinal study. Eur Arch Psychiatry Clin Neurosci. 1993;242:329–336.

42. American Sleep Disorders Association. The International Classification of Sleep Disorders: Diagnostic and Coding Manual. Vol 2. Westchester, IL: American Academy of Sleep Medicine; 2005.

43. Pearson VE, Allen RP, Dean T, et al.. Cognitive deficits associated with restless legs syndrome (RLS). Sleep Med. 2006;7:25–30.

44. Darko DF, Miller JC, Gallen C, et al.. Sleep electroencephalogram delta-frequency amplitude, night plasma levels of tumor necrosis factor alpha, and human immunodeficiency virus infection. Proc Natl Acad Sci U S A. 1995;92:12080–12084.

45. Kraft-Terry SD, Stothert AR, Buch S, et al.. HIV-1 neuroimmunity in the era of antiretroviral therapy. Neurobiol Dis. 2010;37:542–548. doi:10.1016/j.nbd.2009.12.015.

46. Sevigny JJ, Albert SM, McDermott MP, et al.. Evaluation of HIV RNA and markers of immune activation as predictors of HIV-associated dementia. Neurology. 2004;63:2084–2090.

47. Ragin AB, Wu Y, Ochs R, et al.. Biomarkers of neurological status in HIV infection: a 3-year study. Proteomics Clin Appl. 2010;4:295–303. doi:10.1002/prca.200900083.

48. Clinton JM, Davis CJ, Zielinski MR, et al.. Biochemical regulation of sleep and sleep biomarkers. J Clin Sleep Med. 2011;7(5 suppl):S38–S42. doi: 10.5664/JCSM.1360.

49. Born J, Lange T, Hansen K, et al.. Effects of sleep and circadian rhythm on human circulating immune cells. J Immunol. 1997;158:4454–4464.

50. Mayhan WG. Cellular mechanisms by which tumor necrosis factor-alpha produces disruption of the blood-brain barrier. Brain Res. 2002;927:144–152.

51. Wang W, Lv S, Zhou Y, et al.. Tumor necrosis factor-alpha affects blood-brain barrier permeability in acetaminophen-induced acute liver failure. Eur J Gastroenterol Hepatol. 2011;23:552–558. doi: 10.1097/MEG.0b013e3283470212.

52. Yarlagadda A, Alfson E, Clayton AH. The blood brain barrier and the role of cytokines in neuropsychiatry. Psychiatry (Edgmont). 2009;6:18–22.

53. Centers for Disease Control and Prevention (CDC). HIV prevalence estimates–United States, 2006. MMWR Morb Mortal Wkly Rep. 2008;57:1073–1076.

54. Jena A, Sachdeva RK, Sharma A, et al.. Adverse drug reactions to nonnucleoside reverse transcriptase inhibitor-based antiretroviral regimen: a 24-week prospective study. J Int Assoc Physicians AIDS Care (Chic). 2009;8:318–322.

55. Kenedi CA, Goforth HW. A systematic review of the psychiatric side-effects of efavirenz. AIDS Behav. 2011;15:1803–1818.

56. Nguyen A, Calmy A, Delhumeau C, et al.. A randomized crossover study to compare efavirenz and etravirine treatment. AIDS. 2011;25:57–63.

57. Rihs TA, Begley K, Smith DE, et al.. Efavirenz and chronic neuropsychiatric symptoms: a cross-sectional case control study. HIV Med. 2006;7:544–548.

58. Clifford DB, Evans S, Yang Y, et al.. Long-term impact of efavirenz on neuropsychological performance and symptoms in HIV-infected individuals (ACTG 5097s). HIV Clin Trials. 2009;10:343–355.

59. Simioni S, Cavassini M, Annoni JM, et al.. Cognitive dysfunction in HIV patients despite long-standing suppression of viremia. AIDS. 2010;24:1243–1250. doi:10.1097/QAD.0b013e3283354a7b.

60. Ettenhofer ML, Hinkin CH, Castellon SA, et al.. Aging, neurocognition, and medication adherence in HIV infection. Am J Geriatr Psychiatry. 2009;17:281–290.

Keywords:

HIV; sleep; sleep disorders; cognition; quality of life

© 2013 by Lippincott Williams & Wilkins

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