中老年脑卒中患者疲劳发展轨迹及其影响因素的研究

Fatigue development trajectory and its influencing factors in middle-aged and elderly patients with stroke

  • 摘要:
    目的 分析中老年脑卒中患者疲劳发展的轨迹类别并探讨其影响因素。
    方法 采用便利抽样法选取泸州市人民医院2021年1月—2023年1月住院的230例中老年脑卒中患者作为研究对象, 使用研究人员自行编制的一般资料调查表、疲劳严重程度量表(FSS)、匹兹堡睡眠质量指数(PSQI)、Beck抑郁量表(BDI)调查患者入院后2 d及出院后3、6个月的社会人口学资料和临床资料、疲劳、睡眠质量以及抑郁情况。采用潜变量增长模型拟合患者疲劳发展的类别轨迹,采用无序多分类Logistic回归模型分析疲劳发展轨迹类别的影响因素。
    结果 中老年脑卒中患者疲劳发展轨迹共呈现3个潜在类别,即低水平疲劳稳定组(33.04%)、中水平疲劳快速加重组(42.17%)和高水平疲劳缓慢加重组(24.79%)。无序多分类Logistic回归分析结果显示,年龄、婚姻状态、受教育程度、疾病严重程度、日常活动能力(ADL)评分、PSQI评分、BDI评分是中老年脑卒中患者疲劳发展轨迹的影响因素(均P < 0.05)。
    结论 中老年脑卒中患者疲劳发展轨迹具有群体异质性,护理人员应了解不同患者疲劳的演变特征,根据患者症状表现实施针对性的管理措施,改善患者健康结局。

     

    Abstract:
    Objective To analyze the trajectory categories of fatigue development in middle-aged and elderly stroke patients and explore its influencing factors.
    Methods A convenient sampling method was used to select 230 middle-aged and elderly stroke patients in the Luzhou People's Hospital from January 2021 to January 2023 as the research subjects. A self-compiled general information-questionnaire, the Fatigue Severity Scale (FSS), the Pittsburgh Sleep Quality Index (PSQI), and the Beck Depression Inventory (BDI) were used to investigate the sociodemographic and clinical data, fatigue, sleep quality, and depression status of patients at 2 days after admission and 3 and 6 months after discharge. The latent growth curve model was used to fit the categories and trajectories of fatigue development, and the unordered multinomial Logistic regression model was used to analyze the influencing factors of trajectory categories of fatigue development.
    Results The fatigue development trajectory of middle-aged and elderly stroke patients showed three potential categories, namely the low-level fatigue stability group (33.04%), the medium-level fatigue rapid aggravation group (42.17%), and the high-level fatigue slow aggravation group (24.79%). The results of unordered multinomial Logistic regression analysis showed that age, marital status, education level, disease severity, the Activity of Daily Living (ADL) score, PSQI score, and BDI score were the influencing factors of fatigue development trajectory in middle-aged and elderly stroke patients (all P < 0.05).
    Conclusion The fatigue development trajectory of middle-aged and elderly stroke patients is heterogeneous. Nurses should understand the evolution characteristics of fatigue in different patients and implement targeted management measures according to patients'symptoms to improve their health outcomes.

     

/

返回文章
返回