Abstract

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 (CPAP). 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.

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).

Rationale for Current Study

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.

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 1.

Cognitive function categories and tests assessing skills within those categories that were used in the studies included in this meta-analysis

Cognitive domain Tests 
Attention WAIS Digit Span forward, Letter Cancellation, Corsi, PASAT, TMT A, N-Back, Double Encoding Task, CANTAB Spatial Span test, Repeated Psychometric Measures (visualization subtest) 
Concept formation WAIS-R Picture Arrangement, similarities, picture completion, Raven's Advanced Progressive Matrices 
Construction Rey Complex Figure (copy), WAIS-R Block Design, Object Assembly, Bender Visual Motor Test, Corsi supraspan learning ability 
Executive function Mazes, Stroop, WCST, Tower of Toronto, Intra-Extra Dimensional set-shifting, Stockings of Cambridge, Porteus Maze, Five-point test 
Motor control/ performance Purdue Pegboard, Mirror Tracing Task 
Non-verbal memory Rey Complex Figure (recall), WMS Figural Memory, CANTAB Self-Ordered Spatial Memory Task 
Perception Digit Cancellation Task 
Psychomotor speed DSST, Symbol Digit Modalities Test 
Speed of processing TMT B, Critical Flicker Fusion test, Zimmermann-Fimm Test battery for Attentional Performance (Flexibility Test subtest) 
Verbal function/ language WAIS-R Vocabulary, Information, Boston Naming Test 
Verbal memory WMS Logical Memory, Rey List, RAVLT, serial verbal learning tast, verbal learning test (using selective reminding procedure of Buschke), CVLT 
Verbal reasoning COWAT, verbal fluency task 
Working memory WAIS Digit Span backwards, WAIS Arithmetic CANTAB spatial Working memory 
Cognitive domain Tests 
Attention WAIS Digit Span forward, Letter Cancellation, Corsi, PASAT, TMT A, N-Back, Double Encoding Task, CANTAB Spatial Span test, Repeated Psychometric Measures (visualization subtest) 
Concept formation WAIS-R Picture Arrangement, similarities, picture completion, Raven's Advanced Progressive Matrices 
Construction Rey Complex Figure (copy), WAIS-R Block Design, Object Assembly, Bender Visual Motor Test, Corsi supraspan learning ability 
Executive function Mazes, Stroop, WCST, Tower of Toronto, Intra-Extra Dimensional set-shifting, Stockings of Cambridge, Porteus Maze, Five-point test 
Motor control/ performance Purdue Pegboard, Mirror Tracing Task 
Non-verbal memory Rey Complex Figure (recall), WMS Figural Memory, CANTAB Self-Ordered Spatial Memory Task 
Perception Digit Cancellation Task 
Psychomotor speed DSST, Symbol Digit Modalities Test 
Speed of processing TMT B, Critical Flicker Fusion test, Zimmermann-Fimm Test battery for Attentional Performance (Flexibility Test subtest) 
Verbal function/ language WAIS-R Vocabulary, Information, Boston Naming Test 
Verbal memory WMS Logical Memory, Rey List, RAVLT, serial verbal learning tast, verbal learning test (using selective reminding procedure of Buschke), CVLT 
Verbal reasoning COWAT, verbal fluency task 
Working memory WAIS Digit Span backwards, WAIS Arithmetic CANTAB spatial Working memory 

Notes: WAIS = Wechsler Adult Intelligence Scale, PASAT = Paced Auditory Serial Attention Test, TMT = Trail Making Test, CANTAB = Cambridge Neuropsychological Test Automated Battery, WCST = Wisconsin Card Sorting Test, WMS = Wechsler Memory Scale, RAVLT = Rey Auditory Verbal Learning Test, CVLT = California Verbal Learning Test, COWAT = Controlled Oral Word Association Test.

Table 2.

Summary descriptive statistics

Variable NStudies Nparticipants Mean (SDRange 
No. of participants 19 811 42.7 (21.8) 20–108 
Patient, N 19 430 22.6 (13) 10–54 
Control, N 19 381 20.1 (9.8) 10–54 
Patient age 19 430 48.9 (6.2) 41.4–66.70 
Control age 19 381 47.2 (8.2) 27.6–68.70 
Patient education (years) 16 353 12.3 (1.1) 10.6–14.5 
Control education (years) 16 329 13.1 (1.1) 11.2–15.6 
Patient BMI 13 270 31.1 (2.4) 24.4–34.3 
Control BMI 11 211 25.0 (1.5) 22.3–27.3 
No. of male 17 596 35.1 (17.5) 10–75 
No. of female 17 143 8.4 (9.7) 0–33 
Variable NStudies Nparticipants Mean (SDRange 
No. of participants 19 811 42.7 (21.8) 20–108 
Patient, N 19 430 22.6 (13) 10–54 
Control, N 19 381 20.1 (9.8) 10–54 
Patient age 19 430 48.9 (6.2) 41.4–66.70 
Control age 19 381 47.2 (8.2) 27.6–68.70 
Patient education (years) 16 353 12.3 (1.1) 10.6–14.5 
Control education (years) 16 329 13.1 (1.1) 11.2–15.6 
Patient BMI 13 270 31.1 (2.4) 24.4–34.3 
Control BMI 11 211 25.0 (1.5) 22.3–27.3 
No. of male 17 596 35.1 (17.5) 10–75 
No. of female 17 143 8.4 (9.7) 0–33 

Notes: SD = standard deviation; BMI = body mass index.

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 (CPAP)], 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.

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) Consecutively submitted to PSG between October 2009 and January 2010 NS None 
Bédard, Montplaisir, Malo, Richer, & Rouleau (1993) Sleep apnea index >10
SaO2 < 80% 
Duration NS
moderate-to-severe OSA 
CPAP 
Canessa et al. (2011) AHI > 30 Duration NS
Severe OSA 
CPAP 
Castronovo et al. (2009) AHI > 30 Duration NS
Severe OSA 
PAP 
Castronovo et al. (2014) AHI ≥ 30 Duration NS
Severe OSA 
CPAP 
Ferini-Strambi et al. (2003) PSG Duration NS
Severe OSA 
CPAP 
Greenberg, Watson, and Deptula (1987) Patients were referred by physicians who had evaluated them at a fully 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 SaO2 were included 
NS None 
Ju et al. (2012) PSG
AHI ≥ 15 (mild-to-moderate OSA patient group data were utilized) 
Duration NS
Mild-to-moderate OSA 
None 
Kloepfer et al. (2009) International Classification of Sleep Disorders criteria of OSA Syndrome (AHI > 5 per hour)
Diagnosis made by a sleep specialist (MD, Respiratory Physician)
ESS
PSQI
SFA, SQ 
Duration NS
Moderate OSA 
None 
Naëgelé et al. (2006) PSG (threshold RDI ≥ 10 per hour; investigations conducted by trained PSG technicians)
ESS 
NS None 
Naëgelé et al. (1995) PSG (threshold RDI ≥ 10 per hour; investigations conducted by trained PSG technicians)
SaO2 < 85% 
Duration NS
7 patients with moderate OSA
10 patients with severe OSA 
None 
Salorio et al. (2002) Overnight Polygraphic sleep studies utilized to determine severity of OSA Duration NS
10 patients with mild OSA
6 patients with moderate OSA
12 patients with severe OSA 
None 
Saunamäki, Himanen, et al. (2009) Patients diagnosed on the basis of a clinical picture and subjective complaints (ESS)
PSG (AHI > 10 per hour) 
Duration NS
Severity ranged from mild to severe 
None 
Saunamäki et al. (2010) Patients diagnosed on the basis of a clinical picture and subjective complaints (ESS)
PSG (AHI > 10 per hour) 
Duration NS
Severity ranged from mild to severe 
None 
Saunamäki, Jehkonen, et al. (2009) Patients diagnosed on the basis of a clinical interview and subjective complaints (ESS)
PSG (AHI > 10 per hour) 
Duration NS
moderate-to-severe OSA 
CPAP 
Schneider, Fulda, and Schulz (2004) Medical examinations and neurological examinations in sleep disorders clinic
MSLT
ESS
PSG
Patients had to meet the criteria as outlined in the ICSD 
NS None 
Sharma et al. (2010) PSG (AHI ≥ 5)
ESS 
Duration NS
Severe OSA 
None 
Torelli et al. (2011) Detailed clinical interview, physical examination, and questionnaires
ESS
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 
Duration NS
moderate-to-severe OSA 
None 
Verstraeten et al. (2004) PSG (AHI ≥ 15)
PSQI 
Duration NS
moderate-to-severe OSA 
None investigated 
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) Consecutively submitted to PSG between October 2009 and January 2010 NS None 
Bédard, Montplaisir, Malo, Richer, & Rouleau (1993) Sleep apnea index >10
SaO2 < 80% 
Duration NS
moderate-to-severe OSA 
CPAP 
Canessa et al. (2011) AHI > 30 Duration NS
Severe OSA 
CPAP 
Castronovo et al. (2009) AHI > 30 Duration NS
Severe OSA 
PAP 
Castronovo et al. (2014) AHI ≥ 30 Duration NS
Severe OSA 
CPAP 
Ferini-Strambi et al. (2003) PSG Duration NS
Severe OSA 
CPAP 
Greenberg, Watson, and Deptula (1987) Patients were referred by physicians who had evaluated them at a fully 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 SaO2 were included 
NS None 
Ju et al. (2012) PSG
AHI ≥ 15 (mild-to-moderate OSA patient group data were utilized) 
Duration NS
Mild-to-moderate OSA 
None 
Kloepfer et al. (2009) International Classification of Sleep Disorders criteria of OSA Syndrome (AHI > 5 per hour)
Diagnosis made by a sleep specialist (MD, Respiratory Physician)
ESS
PSQI
SFA, SQ 
Duration NS
Moderate OSA 
None 
Naëgelé et al. (2006) PSG (threshold RDI ≥ 10 per hour; investigations conducted by trained PSG technicians)
ESS 
NS None 
Naëgelé et al. (1995) PSG (threshold RDI ≥ 10 per hour; investigations conducted by trained PSG technicians)
SaO2 < 85% 
Duration NS
7 patients with moderate OSA
10 patients with severe OSA 
None 
Salorio et al. (2002) Overnight Polygraphic sleep studies utilized to determine severity of OSA Duration NS
10 patients with mild OSA
6 patients with moderate OSA
12 patients with severe OSA 
None 
Saunamäki, Himanen, et al. (2009) Patients diagnosed on the basis of a clinical picture and subjective complaints (ESS)
PSG (AHI > 10 per hour) 
Duration NS
Severity ranged from mild to severe 
None 
Saunamäki et al. (2010) Patients diagnosed on the basis of a clinical picture and subjective complaints (ESS)
PSG (AHI > 10 per hour) 
Duration NS
Severity ranged from mild to severe 
None 
Saunamäki, Jehkonen, et al. (2009) Patients diagnosed on the basis of a clinical interview and subjective complaints (ESS)
PSG (AHI > 10 per hour) 
Duration NS
moderate-to-severe OSA 
CPAP 
Schneider, Fulda, and Schulz (2004) Medical examinations and neurological examinations in sleep disorders clinic
MSLT
ESS
PSG
Patients had to meet the criteria as outlined in the ICSD 
NS None 
Sharma et al. (2010) PSG (AHI ≥ 5)
ESS 
Duration NS
Severe OSA 
None 
Torelli et al. (2011) Detailed clinical interview, physical examination, and questionnaires
ESS
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 
Duration NS
moderate-to-severe OSA 
None 
Verstraeten et al. (2004) PSG (AHI ≥ 15)
PSQI 
Duration NS
moderate-to-severe OSA 
None investigated 

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 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 Nstudies Cohen's d 95% CI lower 95% CI upper Q-statistic Nfs 
Non-verbal memory −0.79* −0.97 −0.60 261.1* 35 
Concept formation −0.78* −1.12 −0.45 20.1* 20 
Psychomotor speed −0.70* −0.92 −0.49 81.7* 32 
Construction −0.69* −0.86 −0.51 394.9* 31 
Executive function 12 −0.64* −0.70 −0.48 2564.5* 50 
Perception −0.61 −1.30 0.07 N/A 
Motor control/performance −0.60* −0.74 −0.46 902.8 24 
Attention 14 −0.57* −0.66 −0.47 4459.1* 57 
Speed of processing 11 −0.52* −0.69 −0.35 97.4* 40 
Working memory −0.41* −0.61 −0.22 29.1* 25 
Verbal memory 10 −0.39* −0.50 −0.28 1230.7* 30 
Verbal functions/language −0.38* −0.73 −0.03 6.3 
Verbal reasoning 11 −0.36* −0.51 −0.22 90.4* 31 
Cognitive domain Nstudies Cohen's d 95% CI lower 95% CI upper Q-statistic Nfs 
Non-verbal memory −0.79* −0.97 −0.60 261.1* 35 
Concept formation −0.78* −1.12 −0.45 20.1* 20 
Psychomotor speed −0.70* −0.92 −0.49 81.7* 32 
Construction −0.69* −0.86 −0.51 394.9* 31 
Executive function 12 −0.64* −0.70 −0.48 2564.5* 50 
Perception −0.61 −1.30 0.07 N/A 
Motor control/performance −0.60* −0.74 −0.46 902.8 24 
Attention 14 −0.57* −0.66 −0.47 4459.1* 57 
Speed of processing 11 −0.52* −0.69 −0.35 97.4* 40 
Working memory −0.41* −0.61 −0.22 29.1* 25 
Verbal memory 10 −0.39* −0.50 −0.28 1230.7* 30 
Verbal functions/language −0.38* −0.73 −0.03 6.3 
Verbal reasoning 11 −0.36* −0.51 −0.22 90.4* 31 

Notes: Nfs = Fail safe N values.

*

Significance at the .05 level.

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 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 CPAP 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 with OSA who appear to have cognitive deficits and referring them to specialists who can conduct a more thorough evaluation (Beebe et al., 2003), not to mention the implication of these deficits to the possibility of false attribution of the source of the impairment in the context of other possible neuropsychological presentations.

Conflict of Interest

None declared.

References

References denoted with * were included in the meta-analysis.

Alchanatis
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