脳卒中後の神経学的機能回復における客観的睡眠の質の軌跡とその関連：前向き縦断研究

ObjectiveTo explore the latent trajectory classes of objective sleep quality in stroke patients and their impact on neurological functional recovery.MethodsA multicenter cluster sampling method was used to recruit 362 stroke patients from the neurology departments of 5 tertiary hospitals in China between November 2023 and July 2024. Baseline data were collected using a general information questionnaire and related scales. Objective sleep data were obtained using ActiGraph GT3X triaxial accelerometers during the acute (T0), recovery (T1), and chronic (T2) phases of stroke. Neurological recovery was assessed at 12 months post-onset (T3) using the modified Rankin Scale. Parallel-process latent class growth modeling was used to identify trajectory classes. Binary logistic regression examined the association between sleep trajectories and neurological recovery.ResultsA total of 306 patients were followed up. Four distinct trajectory classes were identified: Consistently good sleep quality group (34.31%), Short sleep-increased efficiency-improved fragmentation group (49.02%), Long sleep-reduced efficiency-deteriorated fragmentation group (7.84%), and Consistently poor sleep quality group (8.82%). Compared to the consistently good sleep quality group, patients in the Long sleep-reduced efficiency-deteriorated fragmentation group and Consistently poor sleep quality group had 5.728 (95% confidence interval [CI]: 2.124-15.444) and 6.769 (95% CI: 2.580-17.758) times higher risks of poor neurological recovery, respectively.ConclusionStroke patients exhibit heterogeneous sleep quality trajectories, with differential impacts on neurological recovery. Healthcare providers should implement personalized sleep management strategies to optimize both sleep quality and functional outcomes.