Association between Chronic kidney disease and restless leg syndrome (RLS): a systematic review and meta-analysis.

Restless leg syndrome (RLS) is characterized by unpleasant nocturnal sensations in the lower limbs, and it has emerged as the fourth leading cause of insomnia and is often an underdiagnosed medical condition among sleep disorders. The symptoms of RLS are more common in chronic kidney disease patients than in the general population. Therefore, we performed the first meta-analysis to estimate the risk of RLS among chronic kidney disease patients. We conducted a comprehensive search in Embase, Ovid-MEDLINE, PubMed, Scopus, Web of Science, and CINAHL databases. Data were analyzed with the random-effects model using Comprehensive Meta-Analysis (CMA) software to find the odds ratio (OR). The heterogeneity was checked with the I2 test and Cochran's Q-statistic, and we performed the moderator analysis to find potential sources of heterogeneity. The study quality was assessed using the Newcastle-Ottawa Scale. Of 1175 studies, we found nine studies, with a total of 18,983 participants. The pooled OR of RLS among chronic kidney disease was 5.64 (95%CI 2.70-11.78). Regarding moderator analysis results, it was observed that higher body mass index and abnormal laboratory results would increase the risk of RLS; however, the statistical test was not significant in the current study. The findings reveal a substantial sixfold increase in the likelihood of RLS when compared to the general population. Therefore, health professionals should encourage patients to adhere to the treatment and practice a healthy lifestyle to manage their condition and reduce the risk of RLS. Moreover, future research can develop an intervention to reduce RLS symptoms. Supplementary Information: The online version contains supplementary material available at 10.1007/s41105-024-00513-4.

Psychometric properties of Indonesian version of sleep condition indicator for screening poststroke insomnia.

BACKGROUND: No study has examined the psychometric properties of the sleep condition indicator (SCI) for screening poststroke insomnia in the Indonesian population. We aimed to develop the Indonesian version of the sleep condition indicator (ISCI) and to examine its psychometric properties for screening adult patients in late sub-acute and chronic periods after stroke. METHODS: This was a cross-sectional study with two stages. In the first stage, the English version of the SCI was translated into the ISCI using standard procedures. The psychometric properties of the ISCI were tested in the second stage. Internal consistency and test-retest reliability of ISCI were used to evaluate reliability. A confirmatory factor analysis (CFA) was performed to test construct validity. To test concurrent and convergent validity, the Indonesian version of the insomnia severity index (ISI-INA), generalized anxiety disorder questionnaire (IGAD-7), and patient health questionnaire (IPHQ-9) were used. A receiver operating characteristic (ROC) analysis was conducted to calculate the optimal cutoff score of the ISCI on the basis of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) diagnostic criteria for insomnia. RESULTS: A total of 160 adults with a diagnosis of stroke for more than 3 months were included (median age of 58.5 years, 31% met the DSM-5 criteria for insomnia). The ISCI had a satisfactory Cronbach's alpha of 0.89 and test-retest reliability of 0.78. The CFA revealed that the ISCI exhibited a satisfactory model fit and was associated with the ISI-INA, IGAD-7, and IPHQ-9 (r = -0.81, -0.32, and -0.52, respectively; all P < .001). The ROC test revealed that the optimal cutoff point of ≤23 yielded the highest sensitivity (94%) and specificity (97%). CONCLUSION: The study results revealed that the 8-item ISCI is a reliable and valid screening tool for detecting insomnia symptoms according to the DSM-5 criteria in the chronic period after stroke.

Dynamic Prevalence of Sleep Disorders Following Stroke or Transient Ischemic Attack: Systematic Review and Meta-Analysis.

BACKGROUND AND PURPOSE: The exact prevalence of sleep disorders following stroke or transient ischemic attack (TIA) remains unclear. We aimed to determine the prevalence of sleep-disordered breathing, insomnia, periodic leg movement during sleep, and restless leg syndrome following stroke or TIA in acute, subacute, and chronic phases and examine the moderating effects of patient characteristics (eg, age) and methodological features (eg, study quality) on the prevalence. METHODS: We performed a systematic review and meta-analysis. Embase and PubMed were searched from inception to December 18, 2019. We included 64 047 adults in 169 studies (prospective, retrospective, case-control, and cross-sectional study designs) reporting the prevalence of sleep disorders following stroke or TIA. RESULTS: In the acute phase, the overall prevalence of mild, moderate, and severe sleep-disordered breathing was 66.8%, 50.3%, and 31.6% (95% CIs, 63.8-69.7, 41.9-58.7, and 24.9-39.1). In the subacute phase, the prevalence of mild, moderate, and severe sleep-disordered breathing was 65.5%, 44.3%, and 36.1% (95% CIs, 58.9-71.5, 36.1-52.8, and 22.2-52.8). In the chronic phase, the summary prevalence of mild, moderate, and severe sleep-disordered breathing was 66.2%, 33.1%, and 25.1% (95% CIs, 58.6-73.1, 24.8-42.6, and 10.9-47.6). The prevalence rates of insomnia in the acute, subacute, and chronic phases were 40.7%, 42.6%, and 35.9% (95% CIs, 31.8-50.3, 31.7-54.1, and 28.6-44.0). The pooled prevalence of periodic leg movement during sleep in the acute, subacute, and chronic phases was 32.0%, 27.3%, and 48.2% (95% CIs, 7.4-73.5, 11.6-51.7, and 33.1-63.5). The summary prevalence of restless leg syndrome in the acute and chronic phases was 10.4% and 13.7% (95 CIs, 6.4-16.4 and 2.3-51.8). Age, sex, comorbidities, smoking history, and study region had significant moderating effects on the prevalence of sleep disorders. CONCLUSIONS: Sleep disorders following stroke or TIA are highly prevalent over time. Our findings indicate the importance of early screening and treating sleep disorders following stroke or TIA.

Gender differences in the relationships between sleep disturbances and academic performance among nursing students: A cross-sectional study.

BACKGROUND: Sleep disturbances, such as insomnia, excessive daytime sleepiness, and poor-quality sleep, are common among nursing students and are closely linked with academic performance. OBJECTIVES: To examine the prevalence of sleep disturbances and academic performances in male and female nursing students and to determine gender-specific effects on the relationship between sleep disturbances and academic performance. DESIGN: A cross-sectional study design was adopted. SETTINGS: This study was conducted in a school of nursing in Indonesia. PARTICIPANTS: A total of 492 undergraduate students (103 males and 389 females) were included. METHODS: Data pertaining to the biosociodemographic characteristics, Pittsburgh Sleep Quality Index, Insomnia Severity Index, Epworth Sleepiness Scale, Morningness-Eveningness Questionnaire, and Beck Depression Inventory were collected from July 1, 2018 to September 30, 2018. Academic performance was measured using grade point average of the academic year 2017-2018. A multivariate logistic regression model was used for data analyses. RESULTS: The prevalence of poor sleep quality, insomnia, and daytime sleepiness was 66.0%, 45.6%, and 24.3%, respectively, in male nursing students and 71.5%, 52.4%, and 28.8%, respectively, in female nursing students. For circadian rhythm preferences, 66% male and 51.7% female nursing students were categorized as intermediate- and morning-type people, respectively. Insomnia was the only variable among sleep disturbances that significantly correlated with the risk of poor academic performance in female nursing students even after adjustment of covariates. CONCLUSIONS: Sleep disturbances were highly prevalent among female and male nursing students, and insomnia was substantially associated with poor academic performance in female nursing students. Identifying sleep disturbances among nursing students and designing effective interventions to specifically target them are required to improve academic performance of female nursing students.