Global prevalence of post-COVID-19 sleep disturbances in adults at different follow-up time points: A systematic review and meta-analysis.

Our systematic review and meta-analysis estimated the prevalence of post-COVID sleep disturbances in adult population. We systematically searched relevant studies from four databases that reported post-COVID sleep disturbances prevalence with a mean or median follow-up duration of ≥28 days. We identified 153 eligible papers, with a total COVID-19 population of 252437. Employing multilevel mixed-effects meta-analyses, we estimated the overall pooled prevalence of post-COVID sleep disturbances being 28.98% (25.73-32.34), with the highest prevalence reported in Europe and the lowest in Southeast Asia. Poor sleep quality was the most prevalent definition of sleep disturbances, followed by excessive daytime sleepiness, insomnia, sleep apnea. Prevalence estimates were notably higher when measured with Epworth sleepiness scale, or Pittsburgh sleep quality index compared to symptom questionnaires, self-reports, or personal interviews. Female sex (Odds ratio, OR = 1.59, 1.38-1.83) and severe/critical acute COVID-19 (OR = 1.36, 1.09-1.69) emerged as substantial risk factors. Our review underscore the persistent prevalence of sleep disturbances among COVID-19 survivors, and the importance of factors such as geography, definition, measures of sleep disorders, sex, and severity of acute COVID-19 infection. These findings highlight the urgent need for further investigation into the underlying molecular mechanisms driving these sleep disturbances to develop effective therapeutic strategies.

Detection of preceding sleep apnea using ECG spectrogram during CPAP titration night: A novel machine-learning and bag-of-features framework.

Obstructive sleep apnea (OSA) has a heavy health-related burden on patients and the healthcare system. Continuous positive airway pressure (CPAP) is effective in treating OSA, but adherence to it is often inadequate. A promising solution is to detect sleep apnea events in advance, and to adjust the pressure accordingly, which could improve the long-term use of CPAP treatment. The use of CPAP titration data may reflect a similar response of patients to therapy at home. Our study aimed to develop a machine-learning algorithm using retrospective electrocardiogram (ECG) data and CPAP titration to forecast sleep apnea events before they happen. We employed a support vector machine (SVM), k-nearest neighbour (KNN), decision tree (DT), and linear discriminative analysis (LDA) to detect sleep apnea events 30-90 s in advance. Preprocessed 30 s segments were time-frequency transformed to spectrograms using continuous wavelet transform, followed by feature generation using the bag-of-features technique. Specific frequency bands of 0.5-50 Hz, 0.8-10 Hz, and 8-50 Hz were also extracted to detect the most detected band. Our results indicated that SVM outperformed KNN, LDA, and DT across frequency bands and leading time segments. The 8-50 Hz frequency band gave the best accuracy of 98.2%, and a F1-score of 0.93. Segments 60 s before sleep events seemed to exhibit better performance than other pre-OSA segments. Our findings demonstrate the feasibility of detecting sleep apnea events in advance using only a single-lead ECG signal at CPAP titration, making our proposed framework a novel and promising approach to managing obstructive sleep apnea at home.

Clinical Trials of New Drugs for Vascular Cognitive Impairment and Vascular Dementia.

Population aging has challenged the treatment of cognitive impairment or dementia. Vascular dementia is the second leading cause of dementia after Alzheimer's disease. Cognitive consequences after ischemic brain injury have been recognized as a preferred target for therapeutic strategies, prompting the search for potential agents. The keyword "vascular dementia" was used to search ClinicalTrials.gov to determine agents represented in phases I, II, III, and IV. The agents were classified on the basis of their mechanisms. Of the 17 randomized controlled trials meeting our inclusion criteria, 9 were completed in the past 10 years, and 8 are ongoing or in the planning stages. We also identified one trial in phase I, nine in phase II, six in phase III, and one in phase IV. Fewer trials of new drugs for improving cognition or ameliorating the behavioral and psychological symptoms of dementia target vascular dementia than Alzheimer's dementia. Drug trials on vascular dementia overlap with drug trials targeting functional outcomes in cerebrovascular disease. International pharmaceutical companies' investment in new drugs targeting VCI and vascular dementia remains insufficient.