The Cognitive Effects of Obstructive Sleep Apnea: An Updated Meta-analysis

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1 Archives of Clinical Neuropsychology 31 (2016) Literature Review The Cognitive Effects of Obstructive Sleep Apnea: An Updated Meta-analysis Abstract Elizabeth K. Stranks, Simon F. Crowe* Department of Psychology and Counselling, La Trobe University, Melbourne, VIC 3086, Australia *Corresponding author at: Department of Psychology and Counselling, La Trobe University, VIC 3086, Australia. Tel.: ; fax: address: Accepted 20 November 2015 This meta-analysis set out to ascertain the cognitive function of obstructive sleep apnea (OSA) patients as measured through objective neuropsychological tests. The meta-analysis investigated the cognitive functioning of these patients prior to them receiving any treatment such as continuous positive airway pressure (). A total of 19 studies met the study inclusion criteria. Results revealed statistically significant negative effect sizes in the cognitive domains of non-verbal memory, concept formation, psychomotor speed, construction, executive functioning, perception, motor control and performance, attention, speed of processing, working and verbal memory, verbal functioning and verbal reasoning. The clinical implication of these results, the possible causal mechanisms of the cognitive impairments and the implication of these for future research were each discussed. Despite a number of important limitations, the analysis highlights the need for clinicians to comprehensively explore complaints about sleep disturbance, particularly OSA, in all clinical assessments to ensure control for this important confounder in order to ensure appropriate attribution of the source of any observed cognitive compromise. Keywords: Meta-analysis; Cognitive effects; Obstructive sleep apnea; OSA Introduction Obstructive sleep apnea (OSA) is characterized by repeated complete (apnea) or partial (i.e. hypopnea) cessations of breathing during sleep caused by narrowing at various sites along the upper airway (Aloia, Arnedt, Davis, Riggs, & Byrd, 2004, p. 772). Whilst affecting between 2% and 5% of middle-aged individuals, OSA is more common among individuals aged over 65, with estimates ranging between 19% and 57% (Aloia et al., 2004; Castronovo et al., 2009; Ju et al., 2012; Young, Peppard, & Gottlieb, 2002). OSA has become a significant public health issue as it is often associated with serious and adverse consequences including excessive daytime sleepiness, mood swings, and self-reported cognitive difficulties in addition to hypertension and vascular disease (Aloia et al., 2004; Castronovo et al., 2009; Ju et al., 2012). OSA-related hypoxemia has been demonstrated to change the structure and function of blood vessels, adversely affecting cognition in addition to culminating in mortality and morbidity (Aloia et al., 2004; Lanfranchi & Somers, 2001), and having significant consequences for occupational and educational functioning and automobile safety (Aloia et al., 2004). Several studies have shown that OSA sufferers consistently show deficits in the cognitive domains of attention, episodic and verbal memory, and executive functions (Gagnon et al., 2014). A recent meta-review of the neurocognitive function in OSA indicated that the majority of the articles reviewed cited deficits in attention/vigilance, delayed long-term visual and verbal memory, constructional abilities, and executive functions (Bucks, Olaithe, & Eastwood, 2013). However, a limiting factor of the existing analysis is that most studies have focused on how OSA affects specific cognitive domains. Decary, Rouleau, and Montplaisir (2000) have proposed that using a neuropsychological battery approach to investigate cognitive function in this patient group would ensure that comparisons between cognitive domains and, by extension functional brain regions, would allow for a more comprehensive neurofunctional theory of OSA (Aloia et al., 2004). # The Author Published by Oxford University Press. All rights reserved. For permissions, please journals.permissions@oup.com. doi: /arclin/acv087 Advance Access publication on 6 January 2016

2 Rationale for Current Study E.K. Stranks, S.F. Crowe / Archives of Clinical Neuropsychology 31 (2016); There have already been several meta-analytic reviews investigating the cognitive effects of OSA (Aloia et al., 2004; Beebe, Groesz, Wells, Nichols, & McGee, 2003; Kilpinen, Saunamäki, & Jehkonen, 2014; Vaessen, Overeem, & Sitskoorn, 2015). The earlier meta-analytic reviews produced inconsistent results with regards to the cognitive effects of OSA (Aloia et al., 2004; Beebe et al., 2003). More recent meta-analyses have chosen to focus to focus either on a specific domain of cognitive functioning (Kilpinen et al., 2014) or subjective measures of cognition in OSA (Vaessen et al., 2015). It is clear that a more contemporary and comprehensive analysis of the cognitive functioning of sleep apnea patients as measured by objective neuropsychological tests is warranted. This meta-analysis set out to fill this gap. Methods Literature Search and Inclusion Criteria A search of the computerized databases Medline and PsycINFO was conducted to identify studies that assessed the cognitive effects of OSA published up until 26 of August 2015 (the date of the last update). The neuropsychological search terms were as follows: cognition, cognitive, neuropsychology, neuropsychological, cognitive impairment, cognitive ability, executive function, and daytime. The search terms related to impairment were as follows: deficit, effect, impairment, sequelae and function. The search terms for OSA were obstructive sleep apnea and sleep apnea. Searches were conducted using all possible combinations of these terms and were limited to papers written in the English language. For a study to be included in the meta-analysis, it was necessary for the following criteria to be met; the studies had to: (i) be published in a peer-reviewed journal between 1980 and 2015; (ii) be written in the English language; (iii) include both healthy controls and OSA patients; (iv) include a control group consisting of healthy adults with no pre-existing sleep disorders, mental health, substance abuse, or other disorder that may have affected cognition; (v) incorporate objective neuropsychological and cognitive tests which are widely used and for which norms have been published, and (vi) report results that were sufficient to allow the calculation of effect sizes. The initial search yielded 4061 search results. Of these, a total of 60 papers were chosen on the basis of their title and abstract as potentially meeting the inclusion criteria. Of these, 41 papers were excluded from the study for the following reasons: 28 did not provide sufficient data for the calculation of effect sizes, 11 did not incorporate a healthy control group, and 2 did not incorporate a group of patients suffering from OSA. Coded Variables For all included studies, a number of variables were coded; these were further divided into three categories: participant variables, test information, and outcome measures: Participant variables: (i) study N, (ii) age, (iii) gender, (iv) method of participant recruitment, (v) method of participant recruitment, (vii) customary alcohol and drug use, (vii) smoking status, and (viii) customary caffeine consumption. Test information: (i) neuropsychological test used and (ii) cognitive domain tested. Outcome variables: (i) means and standard deviations and (ii) results of statistical analyses. Statistical Analyses A random effects model was employed, as the distribution of effect sizes is often heterogeneous due to the use of different participants, designs, and cognitive measures (Harvey & Taylor, 2010). Cohen s d effect sizes were calculated for each cognitive domain and were used as the principal summary measure. These values were calculated in a multi-stage process. The first stage involved calculating effect sizes for each score for every test used by each individual study. The effect sizes were calculated according to the methods outlined by Rosenthal (1995). These represent the difference between the patient group and control group data divided by the pooled standard deviation. Thus a positive effect size indicated better performance of the patient group and a negative effect size indicated that the control group performed better than did the patient group. However, in cases where a higher score indicated greater impairment than a lower score (e.g., level of error or reaction time), the direction of the effect sizes for these scores was transformed so that a negative effect size still indicated greater impairment in the patient group.

3 188 E.K. Stranks, S.F. Crowe / Archives of Clinical Neuropsychology 31 (2016); The majority of the included studies used multiple outcome measures. As with other meta-analyses (Anderson-Hanley, Sherman, Riggs, Agocha, & Compas, 2003; Harvey & Taylor, 2010; Hutchinson & Mathias, 2007; Stewart, Bielajew, Collins, Parkinson, & Tomiak, 2006; Stranks & Crowe, 2014), effect sizes were averaged for measures within the same cognitive domain to produce a single effect size per study for each cognitive domain. An analysis of homogeneity, publication bias, and moderator analysis was also undertaken. In order to examine the extent of homogeneity, Q statistics were calculated for each effect size for each cognitive domain in order to assess whether the variance exhibited by the effect sizes was due to sampling error alone (Cooper, 2010). Statistically significant values indicate that the variation in effect sizes was too great to be explained by sampling error alone; that is, some other factor was likely to be contributing to the variance in effect sizes (Cooper, 2010). Publication bias was assessed through the calculation of Fail-safe Ns, which indicate the number of unpublished studies with non-significant results that would need to exist in order to call the observed significant findings into question. The formula developed by Orwin (1983) was used to calculate these values. As different tests were used with varying frequency, it was decided that the Fail-safe Ns should be greater than the number of published studies that had used the test (Hutchinson & Mathias, 2007). Finally, a moderator analysis using Pearson s correlations investigated the relationships between certain coded study characteristics and effect sizes for each study. The variables included in this moderator analysis were: total number of study participants, number of participants in the patient and control groups, mean age of the participants, mean number of years of education, and mean body mass index (BMI). Results A total of 19 studies were included in the meta-analysis. Analysis of the reference lists of the included studies yielded no further studies appropriate for inclusion. Each neuropsychological test was classified into 1 of 13 categories corresponding to the broad cognitive ability that each test was considered to measure, as indicated by two standard neuropsychology assessment texts (Lezak, Howieson, Bigler, & Tranel, 2012; Strauss, Sherman, & Spreen, 2006). The cognitive domains assessed and the specific neuropsychological tests employed in each study are listed in Table 1. Table 2 includes the summary statistics for all studies. Table 3 presents a number of participant characteristics employed in the studies, including the method of the diagnosis of OSA, the duration, and the severity of the sleep disorder and whether the participants were treated either pharmacologically or otherwise. It is also important to note that for the studies in which the participants received treatment for their sleep disorder [e.g., Continuous Positive Airway Pressure ()], the results of the cognitive testing pre-treatment commencement was used. Moreover, where possible, the researchers used the data of participants who were not taking medication at the time of the study. As can be seen in Table 4, statistically significant negative effect sizes were found for all cognitive domains with the exception of the cognitive domain of perception. OSA patients were most impaired on tests measuring non-verbal memory, concept formation, and psychomotor speed. Table 1. Cognitive function categories and tests assessing skills within those categories that were used in the studies included in this meta-analysis Cognitive domain Attention Concept formation Construction Executive function Motor control/ performance Non-verbal memory Perception Psychomotor speed Speed of processing Verbal function/ language Verbal memory Verbal reasoning Working memory Tests WAIS Digit Span forward, Letter Cancellation, Corsi, PASAT, TMT A, N-Back, Double Encoding Task, CANTAB Spatial Span test, Repeated Psychometric Measures (visualization subtest) WAIS-R Picture Arrangement, similarities, picture completion, Raven s Advanced Progressive Matrices Rey Complex Figure (copy), WAIS-R Block Design, Object Assembly, Bender Visual Motor Test, Corsi supraspan learning ability Mazes, Stroop, WCST, Tower of Toronto, Intra-Extra Dimensional set-shifting, Stockings of Cambridge, Porteus Maze, Five-point test Purdue Pegboard, Mirror Tracing Task Rey Complex Figure (recall), WMS Figural Memory, CANTAB Self-Ordered Spatial Memory Task Digit Cancellation Task DSST, Symbol Digit Modalities Test TMT B, Critical Flicker Fusion test, Zimmermann-Fimm Test battery for Attentional Performance (Flexibility Test subtest) WAIS-R Vocabulary, Information, Boston Naming Test WMS Logical Memory, Rey List, RAVLT, serial verbal learning tast, verbal learning test (using selective reminding procedure of Buschke), CVLT COWAT, verbal fluency task WAIS Digit Span backwards, WAIS Arithmetic CANTAB spatial Working memory Notes: WAIS ¼ Wechsler Adult Intelligence Scale, PASAT ¼ Paced Auditory Serial Attention Test, TMT ¼ Trail Making Test, CANTAB ¼ Cambridge Neuropsychological Test Automated Battery, WCST ¼ Wisconsin Card Sorting Test, WMS ¼ Wechsler Memory Scale, RAVLT ¼ Rey Auditory Verbal Learning Test, CVLT ¼ California Verbal Learning Test, COWAT ¼ Controlled Oral Word Association Test.

4 Table 2. Summary descriptive statistics E.K. Stranks, S.F. Crowe / Archives of Clinical Neuropsychology 31 (2016); Variable N Studies N participants Mean (SD) Range No. of participants (21.8) Patient, N (13) Control, N (9.8) Patient age (6.2) Control age (8.2) Patient education (years) (1.1) Control education (years) (1.1) Patient BMI (2.4) Control BMI (1.5) No. of male (17.5) No. of female (9.7) 0 33 Notes: SD ¼ standard deviation; BMI ¼ body mass index. An analysis of homogeneity was undertaken to test the assumption that sampling error alone could account for the variation between the study effect sizes. Q was used as the measure of the extent of heterogeneity, or variability between study effect sizes. The majority of the Q-statistics were statistically significant, indicating that the variation in effect sizes was not due to sampling error alone. Furthermore, as the Fail-safe N values for the cognitive domains were for the most part greater than the number of studies that measured a particular cognitive domain, it was determined that relative confidence could be placed in the results obtained. Finally, the moderator analysis revealed no significant correlations between the effect sizes obtained for each study and number of study participants, number of participants in the patient and control groups, participant age, mean number of years of education, and participant BMI. Discussion This is the first meta-analysis in the last decade which has comprehensively evaluated the cognitive effects of OSA as measured through objective neuropsychological measures. The greatest deficits were found in the areas of psychomotor speed and executive function, while memory functions, motor control, construction, attention, and speed of processing abilities were affected to a lesser extent. These findings largely support the previous work (Bawden, Oliveira, & Caramelli, 2011; Bédard, Montplaisir, Malo, Richer, & Rouleau, 1993; Canessa et al., 2011; Castronovo et al., 2009; Greenberg, Watson, and Deptula, 1987; Ju et al., 2012; Kloepfer et al., 2009; Naëgelé et al., 2006, 1995; Salorio, White, Piccirillo, Duntley, & Uhles, 2002; Saunamaki, Himanen, Polo, & Jehkonen, 2009; Saunamaki, Himanen, Polo, & Jehkonen, 2010; Saunamaki, Jehkonen, Huupponen, Polo, & Himanen, 2009; Sharma et al., 2010; Torelli et al., 2011; Verstraeten, Cluydts, Pevernagie, & Hoffmann, 2004). Moreover, the results are largely consistent with the earlier meta-analysis conducted by Beebe and colleagues, as it corroborates the finding that there is a substantial impact of the condition on vigilance and executive functioning abilities (2003). The more recent results clearly indicate that there are also deficits in memory functions in OSA patients, whereas the previous meta-analyses concluded that data were mixed regarding memory functioning (Aloia et al., 2004; Beebe et al., 2003). The causal mechanism of the relationship between OSA and cognitive impairment is not yet known, but it has been proposed that they are associated with chemical and structural brain cell injury (Alchanatis et al., 2004; Lim & Pack, 2014). Lim and Pack (2014) have suggested that regular intermittent hypoxia is a stressor that could disrupt the blood brain barrier (BBB) via molecular responses already known to occur in...osa patients (p. 35). However, while the BBB response is initially adaptive, this can have long-term consequences that disrupt the brain s microenvironment and alter synaptic plasticity leading to cognitive impairment (Lim & Pack 2014, p. 15). However, such research is in its infancy, thus no definitive conclusion of the mechanism of this relationship is currently available. The moderator analysis revealed no statistically significant relationships. However, it must be noted that only a small number of studies met the inclusion criteria for this analysis, thus it may be the case that some or all of these factors may significantly impact the effect sizes but were undetectable given the relatively small number of studies included in the analysis. The results of this meta-analysis must be interpreted with a consideration of a number of important limitations. After careful scrutiny of the studies that met the inclusion criteria as outlined in the methods section, only 19 studies were included after the evaluation and exclusion procedure. The authors recognize that this limits the ability of the study to evaluate potential covariates including participant demographics and co-morbid diagnoses. It is also noted that many of the studies did not perform comprehensive neuropsychological examinations; with the majority using neuropsychological tests which indexed only a limited number of cognitive domains. It is also the case that none of the studies reported whether the patients were active at the time of

5 190 E.K. Stranks, S.F. Crowe / Archives of Clinical Neuropsychology 31 (2016); Table 3. Participant clinical characteristics Study Method of diagnosis and/or investigations criteria for inclusion in patient group Duration and severity of sleep disorder Pharmacological and/or other treatments investigated Bawden et al. (2011) Consecutivelysubmitted to PSG between October 2009 and January 2010 NS Bédard, Montplaisir, Malo, Sleep apnea index.10 Richer, & Rouleau (1993) SaO 2, 80% moderate-to-severe OSA Canessa et al. (2011) AHI. 30 Castronovo et al. (2009) AHI. 30 PAP Castronovo et al. (2014) AHI 30 Ferini-Strambi et al. (2003) PSG Greenberg, Watson, and Patients were referred by physicians who had evaluated them at a fully NS Deptula (1987) accredited sleep disorders center Patients were evaluated against the diagnostic criteria for sleep apnea DOES syndrome according to the Diagnostic Classification of Sleep and Arousal Disorders manual after polysomnographic evaluation Only sleep apnea patients with normal awake SaO 2 were included Ju et al. (2012) PSG AHI 15 (mild-to-moderate OSA patient group data were utilized) Mild-to-moderate OSA Kloepfer et al. (2009) Naëgelé et al. (2006) Naëgelé et al. (1995) Salorio et al. (2002) Saunamäki, Himanen, et al. (2009) Saunamäki et al. (2010) Saunamäki, Jehkonen, et al. (2009) Schneider, Fulda, and Schulz (2004) Sharma et al. (2010) PSG (AHI 5) International Classification of Sleep Disorders criteria of OSA Syndrome (AHI. 5 per hour) Diagnosis made by a sleep specialist (MD, Respiratory Physician) PSQI SFA, SQ PSG (threshold RDI 10 per hour; investigations conducted by trained PSG technicians) PSG (threshold RDI 10 per hour; investigations conducted by trained PSG technicians) SaO 2, 85% Overnight Polygraphic sleep studies utilized to determine severity of OSA Patients diagnosed on the basis of a clinical picture and subjective complaints () PSG (AHI. 10 per hour) Patients diagnosed on the basis of a clinical picture and subjective complaints () PSG (AHI. 10 per hour) Patients diagnosed on the basis of a clinical interview and subjective complaints () PSG (AHI. 10 per hour) Medical examinations and neurological examinations in sleep disorders clinic MSLT PSG Patients had to meet the criteria as outlined in the ICSD Moderate OSA NS 7 patients with moderate OSA 10 patients with severe OSA 10 patients with mild OSA 6 patients with moderate OSA 12 patients with severe OSA Severity ranged from mild to severe Severity ranged from mild to severe moderate-to-severe OSA NS (Continued)

6 E.K. Stranks, S.F. Crowe / Archives of Clinical Neuropsychology 31 (2016); Table 3. (Continued) Study Method of diagnosis and/or investigations criteria for inclusion in patient group Duration and severity of sleep disorder Pharmacological and/or other treatments investigated Torelli et al. (2011) Detailed clinical interview, physical examination, and questionnaires Overnight monitoring: cardiorespiratory monitoring, Thoraco-abdominal respiratory movement recordings, Nasal and oral airflow, snoring, respiratory function tests, and blood gas analysis Used American Academy of Sleep Medicine guidelines for diagnosis (reduction in airflow.90% lasting at least 10 s and associated with continued or increased inspiratory effort Verstraeten et al. (2004) PSG (AHI 15) PSQI moderate-to-severe OSA moderate-to-severe OSA testing nor were there any details of any performance validity testing and the test scores were treated as valid without further scrutiny. Due to the fact that these measures are rarely reported in this literature it is impossible in the context of a meta-analytic review to control for these effects, but this does not diminish the degree to which such factors may distort the effects noted which should necessarily be cautiously interpreted. There were many studies (41 in total) which could not be included in the analysis as they did not report sufficient data for effect sizes to be calculated. This reinforces the need to ensure that such information is included in future research investigating the cognitive effects of sleep disorders so that these studies can be included in future meta-analyses. In conclusion, the results of this meta-analytic study are important in that they corroborate the mounting evidence that a range of neuropsychological functions are impaired in OSA. However, further research in this area is needed. An interesting question rising from this research is to what extent do the cognitive impairments noted improve following treatment in patients with OSA? Are there specific domains that are more susceptible to improvement with these treatments than are other domains? Another area of future research could investigate whether sleep apnea severity and task complexity might be mediating factors in regards to the cognitive impairments commonly observed in this patient group (Fulda & Schulz, 2001). Finally, it should be investigated whether there is a relationship between subjective complaints in OSA patients and their performance on objective neuropsychological tests. With regards to the clinical implications of these results, it is clear that daytime neuropsychological sequelae must be considered when making treatment decisions for these patients (Beebe et al., 2003). In some instances, a full neuropsychological assessment may be required, particularly if the person demonstrates, or is distressed by cognitive impairment (Olaithe & Bucks, 2013). Moreover, it is important to assess cognitive reserve, for it has been reported that increased intelligence may have a protective effect against OSA-related cognitive decline, perhaps due to increased cognitive reserve (Alchanatis et al., 2005, p. 69). Non-sleep-focused clinicians, especially primary care physicians and psychologists, should also be vigilant in assessing patients investigated Table 4. Summary statistics for the effects of OSA (listed in order of decreasing weighted negative effect size) on each domain of cognitive functioning Cognitive domain N studies Cohen s d 95% CI lower 95% CI upper Q-statistic Nfs Non-verbal memory * * 35 Concept formation * * 20 Psychomotor speed * * 32 Construction * * 31 Executive function * * 50 Perception N/A 4 Motor control/performance * Attention * * 57 Speed of processing * * 40 Working memory * * 25 Verbal memory * * 30 Verbal functions/language * Verbal reasoning * * 31 Notes: Nfs ¼ Fail safe N values. *Significance at the.05 level.

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