RESUMO
Sleep disturbance is common in people with multiple sclerosis and may worsen fatigue; however, the assessment of sleep-fatigue relationships varies across studies. To better understand sleep-fatigue relationships in this population, we conducted a systematic review and random effects meta-analyses for the associations between fatigue and 10 sleep variables: Sleep-disordered breathing, daytime sleepiness, sleep quality, insomnia, restless legs, number of awakenings, sleep efficiency, sleep latency, sleep duration, and wake after sleep onset. Of the 1062 studies screened, 46 met inclusion criteria and provided sufficient data for calculating Hedges' g. Study quality was assessed using the Newcastle-Ottawa Scale. Sample characteristics did not differ between the 10 analyses. Results indicated that sleep quality and insomnia (assessed via self-report or diagnostic criteria) were strongly associated with fatigue (all gs ≥ 0.80 and all ps < .001). In contrast, the number of awakenings and sleep duration (assessed objectively) were not significantly associated with fatigue. Remaining sleep variables yielded moderate, significant effects. Most effects did not vary based on study quality or sample demographics. Results highlight that insomnia and perceptions of poor sleep have a stronger link than objective sleep duration to fatigue in multiple sclerosis and may represent a more effective target for intervention.
RESUMO
OBJECTIVES: The primary aim of this study was to assess the degree to which discrepancies between self-reported and actigraphy-based measures of sleep are associated with specific demographic, disease characteristics, and clinical features in a sample of individuals with multiple sclerosis (MS) reporting clinically significant insomnia symptoms. METHODS: Participants were 90 community-based participants with MS and insomnia. Measures included the Pittsburgh Sleep Quality Index (PSQI), Beck Depression Inventory-Fast Screen (BDI-FS), Modified Fatigue Impact Scale (MFIS), and MS Neuropsychological Screening Questionnaire (MSNQ), and wrist actigraphy-derived sleep parameters. Discrepancy scores were calculated by subtracting actigraphy-derived values from PSQI-derived values for sleep latency (SL), total sleep time (TST), and sleep efficiency (SE). RESULTS: Correlations between PSQI and actigraphy-derived values were weak. Significant discrepancies, with moderate-to-large effect sizes, were observed between PSQI and actigraphy for SL, TST, and SE, whereby the PSQI yielded longer SL, shorter TST, and less SE than actigraphy. MSNQ elevations correlated with greater PSQI-actigraphy discrepancies in SL and TST. MFIS elevations correlated with greater discrepancies in TST. Discrepancies were not significantly related to BDI-FS, gender, race, education level, or MS type. CONCLUSIONS: Results emphasize the importance of assessing fatigue with sleep, and when feasible, inclusion of both self-report and actigraphy measures.
