Abstract:

Objective To explore the potential profiles of symptom burden among stroke patients and to analyze the differences in the characteristics of different classes of stroke patients，providing references for clinical nursing practice. Methods A convenience sampling method was used to select 485 stroke patients treated at 4 tertiary-level general hospitals in Anhui Province from July to December 2024 as the study population. The general information questionnaire，Stroke Symptom Cluster Scale，Personal Mastery Scale，and Cognitive Reserve Index questionnaire. Latent profile analysis was employed to explore the categories of symptom burden among stroke patients，and multiple logistic regression was used to assess the influence factors of each category. Results A total of 456 valid questionnaires were collected，with a valid response rate of 94.02%. Symptom burden among stroke patients can be divided into 4 latent profiles：low symptom burden group （69.08%），multiple symptom burden group（8.12%），moderate burden-physical activity impairment group（11.18%），and moderate burden-emotional and cognitive language impairment group（11.62%）. The patient’s age，number of stroke episodes，number of chronic diseases，systemic inflammation response index，personal mastery，and cognitive reserve were the factors influencing the latent profiles of symptom burden in stroke patients（P<0.05）. Conclusion The symptom burden of stroke patients shows significant heterogeneity. Medical staff can develop targeted nursing interventions based on the category characteristics and influencing factors of the symptom burden in stroke patients.

Key words: Stroke, Symptom Burden, Latent Profile Analysis, Root Cause Analysis, Nursing Care

摘要：

目的 探讨脑卒中患者症状负担的潜在剖面并分析不同类别脑卒中患者特征差异，为临床护理实践提供参考。方法 采用便利抽样法，选取2024年7—12月在安徽省4所三级甲等综合医院住院治疗的485例脑卒中患者作为调查对象，采用一般资料调查表、脑卒中症状群评估量表、个人掌控感量表、认知储备指数问卷进行调查。采用潜在剖面分析探索脑卒中患者症状负担的潜在类别，采用多元Logistic回归分析评估各种因素对不同类别的影响。结果 有效回收问卷456份，有效问卷回收率为94.02%。脑卒中患者症状负担分为4个潜在剖面：低症状负担组（69.08%）、多重症状负担组（8.12%）、中负担-躯体活动障碍组（11.18%）、中负担-情绪与认知言语障碍组（11.62%）。患者年龄、脑卒中发生次数、患慢性病数量、全身炎症反应指数、个人掌控感、认知储备是脑卒中患者症状负担潜在剖面的影响因素（P<0.05）。结论 脑卒中患者症状负担存在明显异质性，医护人员可根据脑卒中患者症状负担的类别特征及影响因素，制订精准化的护理干预措施。

关键词: 脑卒中, 症状负担, 潜在剖面分析, 影响因素分析, 护理