摘要
目的 探讨脑卒中患者跌倒相关因素,构建并验证脑卒中患者跌倒风险预测模型。方法 收集2021年1月至2022年12月郴州市中医医院收治的529例脑卒中患者的临床信息,按照比例7∶3将病例资料随机分为建模组和验证组,最终建模组纳入370例,验证组纳入159例。采用单因素分析和多因素logistic回归分析筛选脑卒中患者跌倒的相关因素。利用相关因素构建列线图预测模型并进行内部验证,评价该预测模型预测效能及临床效用。结果 多因素logistic回归结果显示,饮酒史、肌力异常、夜尿>3次/晚、使用利尿剂是脑卒中患者跌倒的危险因素(P<0.05)。列线图预测模型在建模组、验证组的AUC分别为0.830、0.891,敏感度分别为0.843、0.704,特异度分别为0.840、0.947;校准曲线、决策曲线分析曲线证实该模型校准能力、净获益值较高。结论 饮酒史、肌力异常、夜尿>3次/晚、使用利尿剂,是脑卒中患者跌倒的危险因素,本研究建立跌倒预测模型对预测脑卒中患者跌倒风险具有临床应用价值,为预防脑卒中患者跌倒提供参考。
Objective To investigate the factors related to falls in stroke patients,and construct and verify the fall risk prediction model in stroke patients.Methods The clinical information of 529 stroke patients admitted to Chenzhou Municipal Hospital of TCM from January 2021 to December 2022 were collected,and they were randomly divided into the modeling group and the validation group according to a ratio of 7∶3.Finally,370 cases were included in the modeling group and 159 cases were included in the validation group.Univariate analysis and multivariate logistic regression analysis were employed to identify risk factors associated with falls in stroke patients.A nomogram predictive model was developed based on the identified factors and underwent internal validation.The predictive performance and clinical utility of the model were subsequently evaluated.Results The results of multivariate logistic regression showed that history of alcohol consumption,abnormal muscle strength,nocturia>3 times per night,and the use of diuretics were risk factors for falls in stroke patients(P<0.05).The AUC of the nomogram prediction model in the modeling group and the validation group was 0.830 and 0.891 respectively,the sensitivities were 0.843 and 0.704 respectively,and the specificities were 0.840 and 0.947 respectively.The calibration curve and decision curve analysis curves confirm that the calibration ability and net benefit value of this model are relatively high.Conclusion Alcohol consumption,abnormal muscle strength,nocturnal urination>3 times/night,and use of diuretics are risk factors for falls in stroke patients.Establishing a prediction model based on the above risk factors has clinical application value for predicting fall risk,and provides reference for preventing falls in stroke patients.
作者
肖玲
邝巧灵
周滨
吴彦
刘伟萍
XIAO Ling;KUANG Qiaoling;ZHOU Bin;WU Yan;LIU Weiping(Department of Traditional Chinese Medicine Classics,Chenzhou Municipal Hospital of TCM,Hunan Province,Chenzhou 423000,China;Department of Nursing,Chenzhou Municipal Hospital of TCM,Hunan Province,Chenzhou 423000,China)
出处
《中国当代医药》
2025年第19期10-14,23,共6页
China Modern Medicine
基金
湖南省卫生健康委卫生科研课题(D202314016513)
关键词
脑卒中
跌倒
影响因素
预测模型
Stroke
Fall
Influencing factors
Prediction model
