METHODS AND STUDY DESIGN: A cross-sectional study was conducted among 184 Malaysian HD patients. Anthropometric measurements and handgrip strength (HGS) were obtained using standardized protocols. Relevant biochemical indicators were retrieved from patients' medical records. Nutritional status was assessed using the dialysis malnutrition score. The sleep quality of patients was determined using the Pittsburgh Sleep Quality Index questionnaire on both dialysis and non-dialysis days.
RESULTS: Slightly more than half of the HD patients were poor sleepers, with approximately two-third of them having a sleep duration of <7 hours per day. Sleep latency (1.5±1.2) had the highest sleep component score, whereas sleep medicine use (0.1±0.6) had the lowest score. Significantly longer sleep latency and shorter sleep duration were observed in the poor sleepers, regardless of whether it was a dialysis day or not (p<0.001). Poor sleep quality was associated with male sex, old age, small triceps skinfold, hypoproteinemia, hyperkalemia, hyperphosphatemia, and poorer nutritional status. In a multivariate analysis model, serum potassium (β=1.41, p=0.010), male sex (β=2.15, p=0.003), and HGS (β=-0.088, p=0.021) were found as independent predictors of sleep quality.
CONCLUSIONS: Poor sleep quality was evident among the HD patients in Malaysia. The sleep quality of the HD patients was associated with nutritional parameters. Routine assessment of sleep quality and nutritional parameters indicated that poor sleepers have a risk of malnutrition and may benefit from appropriate interventions.
Methods: This double-blind, randomized, placebo-controlled trial involved fifty subjects with sleep complaints. Subjects with a Pittsburgh Sleep Quality Index (PSQI) score between 6 and 15 were randomized to receive either IQP-AO-101 or placebo for 6 weeks, following a run-in period of one week. Sleep parameters were assessed at baseline and after 1, 4, and 6 weeks using the modified Athens Insomnia Scale (mAIS). Subjects were also instructed to wear an activity tracker and keep a sleep diary during the study. Other questionnaires administered were the Frankfurt Attention Inventory (FAIR-2) and the Profile of Mood States (POMS-65). Blood samples for safety laboratory parameters were taken before and at the end of the study.
Results: After 6 weeks, subjects who consumed IQP-AO-101 reported significant improvements in mAIS scores compared with placebo, including mAIS total score (11.76 ± 6.85 vs 4.00 ± 4.80; p < 0.001); night parameters composite score (5.20 ± 3.80 vs 2.04 ± 3.16; p = 0.001); and day parameters composite score (6.56 ± 4.10 vs 1.96 ± 2.65; p < 0.001). All individual parameters (Items 1 to 8) were also significantly improved from baseline after 6 weeks of IQP-AO-101 intake. Analysis of variance with baseline values as covariates showed statistically significant improvements across all individual parameters for IQP-AO-101 when compared to placebo. The measurements using the activity tracker, sleep diary, FAIR-2, and POMS did not reveal any significant differences between groups. No adverse effects related to the intake of IQP-AO-101 were reported. Tolerability was rated as very good by all the subjects and by the investigator for all cases.
Conclusions: In this study, IQP-AO-101 was well tolerated and efficacious for promoting sleep and enhancing daytime performance in subjects with moderate sleep disturbances.
Clinical Trial Registration: This trial is registered with ClinicalTrials.gov, no. NCT03114696.
METHOD: A systematic review and metanalysis was conducted in accordance with the PRISMA criteria. The PubMed, Scopus, Science direct, Web of science, CINHAL, Medline, and Google Scholar databases were searched with no lower time-limt and until 24 June 2020. The heterogeneity of the studies was measured using I2 test and the publication bias was assessed by the Egger's test at the significance level of 0.05.
RESULTS: The I2 test was used to evaluate the heterogeneity of the selected studies, based on the results of I2 test, the prevalence of sleep disturbances in nurses and physicians is I2: 97.4% and I2: 97.3% respectively. After following the systematic review processes, 7 cross-sectional studies were selected for meta-analysis. Six studies with the sample size of 3745 nurses were examined in and the prevalence of sleep disturbances was approximated to be 34.8% (95% CI: 24.8-46.4%). The prevalence of sleep disturbances in physicians was also measured in 5 studies with the sample size of 2123 physicians. According to the results, the prevalence of sleep disturbances in physicians caring for the COVID-19 patients was reported to be 41.6% (95% CI: 27.7-57%).
CONCLUSION: Healthcare workers, as the front line of the fight against COVID-19, are more vulnerable to the harmful effects of this disease than other groups in society. Increasing workplace stress increases sleep disturbances in the medical staff, especially nurses and physicians. In other words, increased stress due to the exposure to COVID-19 increases the prevalence of sleep disturbances in nurses and physicians. Therefore, it is important for health policymakers to provide solutions and interventions to reduce the workplace stress and pressures on medical staff.
METHODS: The study protocol was registered with PROSPERO (CRD42022325505). MEDLINE (PubMed), Embase, and the Cochrane Library were used as information sources. Eligible studies included original articles of cohort studies, case-control studies, cross-sectional studies, and case series with ≥5 subjects that reported the prevalence and type of neurological manifestations, with a minimum follow-up of 3 months after the acute phase of COVID-19 disease. Two independent reviewers screened studies from January 1, 2020, to June 16, 2022. The following manifestations were assessed: neuromuscular disorders, encephalopathy/altered mental status/delirium, movement disorders, dysautonomia, cerebrovascular disorders, cognitive impairment/dementia, sleep disorders, seizures, syncope/transient loss of consciousness, fatigue, gait disturbances, anosmia/hyposmia, and headache. The pooled prevalence and their 95% confidence intervals were calculated at the six pre-specified times.
RESULTS: 126 of 6,565 screened studies fulfilled the eligibility criteria, accounting for 1,542,300 subjects with COVID-19 disease. Of these, four studies only reported data on neurological conditions other than the 13 selected. The neurological disorders with the highest pooled prevalence estimates (per 100 subjects) during the acute phase of COVID-19 were anosmia/hyposmia, fatigue, headache, encephalopathy, cognitive impairment, and cerebrovascular disease. At 3-month follow-up, the pooled prevalence of fatigue, cognitive impairment, and sleep disorders was still 20% and higher. At six- and 9-month follow-up, there was a tendency for fatigue, cognitive impairment, sleep disorders, anosmia/hyposmia, and headache to further increase in prevalence. At 12-month follow-up, prevalence estimates decreased but remained high for some disorders, such as fatigue and anosmia/hyposmia. Other neurological disorders had a more fluctuating occurrence.
DISCUSSION: Neurological manifestations were prevalent during the acute phase of COVID-19 and over the 1-year follow-up period, with the highest overall prevalence estimates for fatigue, cognitive impairment, sleep disorders, anosmia/hyposmia, and headache. There was a downward trend over time, suggesting that neurological manifestations in the early post-COVID-19 phase may be long-lasting but not permanent. However, especially for the 12-month follow-up time point, more robust data are needed to confirm this trend.