脑卒中患者症状负担潜在剖面及影响因素分析

doi:10.3761/j.issn.0254-1769.2025.17.010

摘要/Abstract

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

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

张世晴, 徐雪君, 邓曼, 杨玥, 李敏, 杨秀木. 脑卒中患者症状负担潜在剖面及影响因素分析[J]. 中华护理杂志, 2025, 60(17): 2110-2117.

ZHANG Shiqing, XU Xuejun, DENG Man, YANG Yue, LI Min, YANG Xiumu. Latent profile analysis and influencing factors of symptom burden among stroke patients[J]. Chinese Journal of Nursing, 2025, 60(17): 2110-2117.

图/表 7

注：SIRI为全身炎症反应指数。 1）χ2 值；2）H值。

表2 脑卒中患者症状负担潜在剖面模型拟合指标（n=456）

Table 2 Model fitting information for the latent profile of symptom burden in stroke patients（n=456）

图1 脑卒中患者症状负担4个潜在剖面的特征分布

Figure 1 Characteristics of 4 potential profiles of symptom burden in stroke patients

表3 脑卒中患者的个人掌控感、认知储备得分在不同潜在剖面间的比较（n=456，分，$\bar{x}±s$）

Table 3 Comparison of the PMS and CRIq scores in stroke patients across different latent profiles（n=456，scores，$\bar{x}±s$）

表4 自变量赋值方式

Table 4 Variable assignment method

表5 脑卒中患者症状负担潜在剖面的多元Logistic回归分析（n=456）

Table 5 Multivariate logistic regression analysis of potential profiles of symptom burden among stroke patients（n=456）

参考文献 23

[1]	GBD 2019 Stroke Collaborators. Global,regional,and national burden of stroke and its risk factors,1990-2019:a systematic analysis for the Global Burden of Disease Study 2019[J]. Lancet Neurol, 2021, 20(10):795-820.
[2]	邓曼, 于卫华, 张世晴, 等. 老年脑卒中患者症状群与健康行为的相关性研究[J]. 护理学杂志, 2025, 40(5):26-32.
	Deng M, Yu WH, Zhang SQ, et al. A study on the relationship between symptom clusters and health behavior in elderly patients with stroke[J]. J Nurs Sci, 2025, 40(5):26-32.
[3]	Davis MP, Kirkova J. Lifting symptom burden:how far off the ground are we?[J]. Support Care Cancer, 2008, 16(7):757-761.
[4]	Thapa A, Chung ML, Wu JR, et al. Mediation by fatalism of the association between symptom burden and self-care management in patients with heart failure[J]. J Cardiovasc Nurs, 2024, 39(3):229-236.
[5]	李佳祺, 赵彤, 杨琨, 等. 脑卒中患者恢复期症状负担及其影响因素调查[J]. 护理学杂志, 2021, 36(14):1-3.
	Li JQ, Zhao T, Yang K, et al. Symptom burden and the associated factors among convalescent stroke patients[J]. J Nurs Sci, 2021, 36(14):1-3.
[6]	罗曦, 唐姗姗. 脑卒中患者症状负担、日常感知歧视现状及其影响因素[J]. 中国社会医学杂志, 2024, 41(2):185-190.
	Luo X, Tang SS. Current status and influencing factors of symptom burden and daily perceived discrimination in patients with stroke[J]. Chin J Soc Med, 2024, 41(2):185-190.
[7]	Mori M, Krumholz HM, Allore HG. Using Latent Class Analysis to Identify Hidden Clinical Phenotypes[J]. JAMA, 2020, 324(7):700-701. DOI PMID
[8]	Schwartz CE, Quaranto BR, Healy BC, et al. Cognitive reserve and symptom experience in multiple sclerosis:a buffer to disability progression over time?[J]. Arch Phys Med Rehabil, 2013, 94(10):1971-1981.
[9]	Lin CY, Miller JL, Lennie TA, et al. Perceived control predicts symptom status in patients with heart failure[J]. J Cardiovasc Nurs, 2020, 35(6):530-537.
[10]	中华医学会神经病学分会, 中华医学会神经病学分会脑血管病学组. 中国各类主要脑血管病诊断要点2019[J]. 中华神经科杂志, 2019, 52(9):710-715.
	Chinese Medical Association Neurology Branch, Chinese Medi-cal Association Neurology Branch Cerebrovascular Disease Group. Diagnostic criteria of cerebrovascular diseases in Chi-na(version 2019)[J]. Chin J Neurol, 2019, 52(9):710-715.
[11]	倪平, 陈京立, 刘娜. 护理研究中量性研究的样本量估计[J]. 中华护理杂志, 2010, 45(4):378-380.
	Ni P, Chen JL, Liu N. The sample size estimation in quantitative nursing research[J]. Chin J Nurs, 2010, 45(4):378-380.
[12]	Chen YF, Qi S, Yu ZJ, et al. Systemic inflammation response index predicts clinical outcomes in patients with acute ischemic stroke(AIS) after the treatment of intravenous thrombolysis[J]. Neurologist, 2023, 28(6):355-361.
[13]	吴蒙, 袁竺方, 游旅, 等. 脑卒中症状群评估量表的编制及信效度检验[J]. 护理学杂志, 2024, 39(3):10-13.
	Wu M, Yuan ZF, You L, et al. Development and validation of the Stroke Symptom Cluster Scale[J]. J Nurs Sci, 2024, 39(3):10-13.
[14]	Pearlin LI, Schooler C. The structure of coping[J]. J Health Soc Behav, 1978, 19(1):2-21. PMID
[15]	余益兵, 邹泓. 流动儿童积极心理品质的发展特点研究[J]. 中国特殊教育, 2008(4):78-83.
	Yu YB, Zou H. A study on the development characteristics of the positive psychological qualities in migrant children[J]. Chin J Spec Educ, 2008(4):78-83.
[16]	Nucci M, Mapelli D, Mondini S. Cognitive Reserve Index ques-tionnaire(CRIq):a new instrument for measuring cognitive reserve[J]. Aging Clin Exp Res, 2012, 24(3):218-226.
[17]	卫婉蕊. 认知衰弱老年人认知储备评估的研究[D]. 北京: 北京协和医学院, 2023.
	Wei WR. Assessment of cognitive reserve in the older adults with cognitive frailty[D]. Beijing: Peking Union Medical College, 2023.
[18]	周柯冰, 黄晓娇, 闫凤侠. 首发脑卒中恢复期患者症状负担及其影响因素的网络分析[J]. 中华护理杂志, 2025, 60(7):792-798. DOI
	Zhou KB, Huang XJ, Yan FX. Network analysis of symptom burden and its influencing factors in first-ever subacute stroke patients[J]. Chin J Nurs, 2025, 60(7):792-798. DOI
[19]	Nutakki A, Chomba M, Chishimba L, et al. Characteristics of adults with first-ever stroke vs. recurrent stroke at the university teaching hospital in Lusaka,Zambia[J]. J Neurol Sci, 2025, 472:123473.
[20]	潘晶雪, 陈利群, 王敬丽, 等. 社区老年慢性病患者认知功能的现状调查[J]. 中华护理杂志, 2021, 56(1):109-115. DOI
	Pan JX, Chen LQ, Wang JL, et al. Study on the status of cognitive function in community elderly adults with chronic diseases[J]. Chin J Nurs, 2021, 56(1):109-115. DOI
[21]	Zhang Y, Xing Z, Zhou K, et al. The predictive role of systemic inflammation response index(SIRI) in the prognosis of stroke patients[J]. Clin Inter Aging, 2021, 16:1997-2007.
[22]	van ‘t Klooster CC, van der Graaf Y, Ridker PM, et al. The relation between healthy lifestyle changes and decrease in systemic inflammation in patients with stable cardiovascular disease[J]. Atherosclerosis, 2020, 301:37-43. DOI PMID
[23]	赵继明, 房晓, 孟俏, 等. 肾移植患者个人生活掌控感现状及其影响因素研究[J]. 中华护理杂志, 2022, 57(10):1213-1218. DOI
	Zhao JM, Fang X, Meng Q, et al. Status and influencing factors of personal mastery in kidney transplant patients[J]. Chin J Nurs, 2022, 57(10):1213-1218. DOI