脑卒中患者睡眠质量轨迹与神经功能恢复的关系研究及护理启示

doi:10.3761/j.issn.0254-1769.2025.23.010

摘要/Abstract

摘要：

目的探讨脑卒中患者客观睡眠质量轨迹及其与神经功能恢复之间的关系，为临床医护人员针对性开展睡眠干预提供依据。方法采用多中心整群抽样方法，选取2023年11月—2024年7月河南省5所三级甲等医院神经内科362例脑卒中患者为调查对象，通过病历和问卷收集基线资料，三轴加速度计调查不同时间点睡眠质量，使用改良Rankin量表评估后遗症期神经功能恢复情况。采用并行潜类别增长模型识别睡眠质量轨迹，通过二元Logistic回归分析探讨不同轨迹对神经功能的影响。结果共306例患者完成随访。睡眠质量轨迹分为睡眠质量持续良好组（34.31%）、短睡眠延长-效率升高-片段化改善组（49.02%）、长睡眠持续-效率降低-片段化加重组（7.84%）和睡眠质量持续不良组（8.83%）。多因素分析结果显示，工作状态、脑卒中类型、合并症、自理能力、社会支持、疲劳和抑郁是脑卒中患者睡眠质量轨迹的影响因素（P<0.05）。与睡眠质量持续良好组相比，长睡眠持续-效率降低-片段化加重组（OR=5.077）和睡眠质量持续不良组（OR=6.462）患者神经功能恢复不良的风险增加。结论脑卒中患者睡眠质量轨迹存在异质性，不同轨迹对神经功能影响不同，医护人员应实施个性化睡眠管理以改善患者的神经功能。

关键词: 脑卒中, 睡眠, 神经康复, 轨迹, 护理, 影响因素分析

Abstract:

Objective This study examined objective sleep quality trajectories in stroke patients and their impact on neurological recovery to guide targeted interventions. Methods From November 2023 to July 2024，362 stroke patients were recruited from neurology departments 5 tertiary hospitals in Henan Province using multicenter cluster sampling. Baseline data were collected via medical records and questionnaires，while objective sleep quality was longitudinally assessed with triaxial accelerometers. Neurological recovery at convalescent phase was evaluated using the modified Rankin Scale. Parallel-process latent class growth modeling identified sleep quality trajectories，and their impact on neurological recovery was analyzed via binary logistic regression. Results Among 306 stroke patients completing follow-up，4 sleep quality trajectories emerged：consistently good sleep quality group（34.31%），improving short sleep-increased efficiency-reduced fragmentation group（49.02%），sustained long sleep-reduced efficiency-worsened fragmentation group（7.84%），and consistently poor sleep quality group（8.83%）. Employment status，stroke type，comorbidities，activities of daily living，social support，fatigue，and depression significantly influenced trajectory classification（P<0.05）. Sustained long sleep-reduced efficiency-deteriorated fragmented group（OR=5.077） and consistently poor sleep quality group（OR=6.462） had significantly higher odds of poor neurological recovery versus the consistently good sleep quality group. Conclusion Stroke patients’ varied sleep recovery trajectories differentially impact neurological recovery，necessitating personalized sleep interventions to improve outcomes.

Key words: Stroke, Sleep, Neurological Recovery, Trajectory, Nursing Care, Root Cause Analysis

杨范家一, 卫佳宁, 李晨霜, 孙长青, 刘延锦, 董小方. 脑卒中患者睡眠质量轨迹与神经功能恢复的关系研究及护理启示[J]. 中华护理杂志, 2025, 60(23): 2887-2894.

YANG Fanjiayi, WEI Jianing, LI Chenshuang, SUN Changqing, LIU Yanjin, DONG Xiaofang. Study on the relationship between sleep quality trajectories and neurological function recovery in stroke patients and its nursing implications[J]. Chinese Journal of Nursing, 2025, 60(23): 2887-2894.

图/表 6

表1 脑卒中患者的一般资料及客观睡眠质量轨迹的单因素分析结果（n=306）

Table 1 Univariate analysis of general data and objective sleep quality trajectories in stroke patients（n=306）

表2 脑卒中患者客观睡眠质量轨迹并行潜类别增长模型拟合指标（n=306）

Table 2 Objective sleep quality trajectory of stroke patients parallel latent class growth model fitting index（n=306）

图1 脑卒中患者客观睡眠质量潜在类别发展轨迹注：a为类别1：睡眠质量持续良好组。b为类别2：短睡眠延长-效率升高-片段化改善组。c为类别3：长睡眠持续-效率降低-片段化加重组。d为类别4：睡眠质量持续不良组。T0为发病1个月内，T1为发病后3个月，T2为发病后6个月。

Figure 1 The latent class development trajectory map of objective sleep quality in stroke patients

表3 分类变量赋值方式

Table 3 Assignment methods of categorical variables

表4 脑卒中患者客观睡眠质量轨迹多因素分析结果（n=306）

Table 4 Multivariate analysis results of objective sleep quality trajectory in stroke patients（n=306）

表5 脑卒中患者客观睡眠质量轨迹类别与神经功能恢复的二元Logistic回归分析（n=306）

Table 5 Binary logistic regression analysis of objective sleep quality trajectory and neurological recovery（n=306）

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