摘要
目的 探讨脑卒中患者发生恐惧疾病进展(FoP)的影响因素,并构建其风险预测模型.方法 采用便利抽样法选取2023年7-12月齐齐哈尔医学院附属第一医院与齐齐哈尔医学院附属第三医院的201例脑卒中患者作为调查对象.采用基线资料调查表、恐惧疾病进展简化量表(FoP-Q-SF)、中文版压力知觉量表、社会支持评定量表、疲劳严重程度量表调查脑卒中患者FoP发生情况、压力知觉、社会支持水平和疲劳水平.探讨脑卒中患者发生FoP的影响因素,并应用R 4.3.2构建脑卒中患者发生FoP的风险预测列线图模型,采用受试者工作特征曲线、校准曲线和临床决策曲线分别从区分度、校准度和临床实用性对模型的性能进行评价.结果 本研究共回收问卷201份,有效问卷199份,问卷有效率99％.199例患者FoP-Q-SF评分为(29.64±9.50)分,其中71例患者发生FoP(35.7％).文化程度、合并症、自理能力、社会支持、压力知觉、疲劳是脑卒中患者发生FoP的影响因素(P＜0.05).基于二项Logistic回归分析结果构建脑卒中患者发生FoP的风险预测列线图模型,Hosmer-Lemeshow结果显示,该列线图模型拟合良好(x2=10.466,P=0.234).受试者工作特征曲线下面积为0.912(95％CI:0.871～0.952),临床决策曲线显示,当阈值概率为4％～99％时,该模型预测FoP发生风险可使脑卒中患者临床获益.结论 文化程度、合并症、自理能力、社会支持、压力知觉、疲劳是脑卒中患者发生FoP的影响因素,基于多评估指标构建的风险列线图模型具备一定的临床价值.
Abstract
Objective To explore influencing factors of the occurrence of fear of disease progression(FoP)in stroke patients and to construct a risk prediction nomogram model.Methods A total of 201 stroke patients of the First Affiliated Hospital of Qiqihar Medical University and the Third Affiliated Hospital of Qiqihar Medical University from July to December 2023 were selected as the survey objects by the convenient sampling method.Baseline data questionnaire,Fear of Progression Questionnaire-Short Form(FoP-Q-SF),Chinese version of Perceived Stress Scale(CPSS),Social Support Rating Scale(SSRS)and Fatigue Severity Scale(FSS)were used to investigate of patients FoP occurrence,stress perception,social support level and fatigue level of stroke patients.The influencing factors of FoP occurrence in stroke patients were explored and R 4.3.2 was used to construct a risk prediction nomogram model for FoP occurrence in stroke patients.The performance of the model was evaluated using receiver operating characteristic curve,calibration curve,and clinical decision curve from the perspectives of discrimination,calibration and clinical practicality.Results In this study,a total of 201 questionnaires were collected,199 were valid,and the effective rate was 99％.The FOP-Q-SF score of 199 patients was(29.64±9.50),of which 71 patients(35.7％)developed FoP.Educational level,complications,self-care ability,social support,stress perception and fatigue were the influencing factors of FoP in stroke patients(P＜0.05).A risk prediction nomogram model for FoP in stroke patients was constructed based on the results of binary Logistic regression analysis.The Hosmer-Lemeshow results showed that the nomogram model fitted well(x2=10.466,P=0.234).The area under ROC curve was 0.912(95％CI:0.871-0.952).The clinical decision curve showed that when the threshold probability ranged from 4％to 99％,choosing this model to predict the risk of FoP could benefit stroke clinically.Conclusions Educational level,complications,self-care ability,social support,stress perception and fatigue are the influencing factors for fear of disease progression in stroke patients.The risk nomogram model based on multiple evaluation indexes has certain clinical value.
基金项目
齐齐哈尔市科技计划联合引导项目(LHYD-2021032)
NETL
NSTL
万方数据