Effect of interventions for the management of sleep disturbances in patients with long COVID: a systematic review and meta-analysis of randomized controlled trials.

STUDY OBJECTIVES: Long COVID presents with symptoms that persist for weeks or months post-infection, with sleep disturbances significantly affecting quality of life. The diverse approaches to managing sleep disturbances highlight the need for comparing treatment effectiveness to improve patient outcomes. This study systematically reviews and conducts a meta-analysis of randomized controlled trials to assess the effectiveness of current interventions for sleep disturbances in long COVID patients, and explores the underlying mechanisms and promising treatments. METHODS: Relevant studies were identified through a comprehensive literature search across Embase, Web of Science, PubMed, Cochrane Library, China National Knowledge Infrastructure, and Wanfang Data databases. The included studies focused on interventions aimed at managing long COVID patients with sleep disturbances. Data extraction and analysis were performed, followed by a meta-analysis of comparable studies. The quality of evidence was assessed using the Cochrane risk-of-bias tool (RoB 2.0) and the GRADE system. RESULTS: Out of 3,352 retrieved studies, 14 were included in the systematic review, and two in the meta-analysis. Interventions were categorized as pharmacological and non-pharmacological. While most studies indicated improved sleep quality measured by standardized scales, some did not demonstrate significant benefits. The quality of evidence varied from low to moderate. CONCLUSIONS: The results suggest that sleep disturbances in long COVID result from a complex interplay of physiological, psychological, and neurological factors. Both pharmacological and non-pharmacological interventions show potential in managing these disturbances, with non-pharmacological approaches showing particular promise. To establish more robust evidence, more high-quality, large-scale randomized controlled trials are necessary in future research.