摘要
目的系统评价脑卒中患者30 d内非计划再入院风险预测模型,为临床医护人员在选择模型时提供参考依据。方法检索中国知网、PubMed、Embase、CINAHL等数据库,搜集与脑卒中患者30 d内非计划再入院风险预测模型的相关研究,检索时限为各数据库建库至2024年4月15日。由2名研究者根据预测模型研究的偏倚风险评估工具对纳入研究进行进行偏倚风险评价和适用性评价。结果共纳入17项研究包含32个模型,样本量为108~803124例,结局事件发生率为2.01%~24.1%;其受试者工作特征曲线下面积介于0.43~0.989之间,5项研究报告校准度,6项进行内部验证、1项进行外部验证、1项进行内部验证和外部验证。15项研究整体适用性评价较好,1项低适用性,1项不清楚,但均呈现较高偏倚风险,高频因子包括年龄、心血管共病、住院时间。结论目前模型尚存在不足,未来模型构建应完善研究设计和报告流程,并对现有模型进行重新校准和外部验证以提高模型泛化性能,重点关注可干预预测因子。
Objective To systematically evaluate risk prediction models for unplanned 30-day readmission in stroke patients,and to provide a reference for clinical healthcare providers in model selection.Methods Databases including CNKI,PubMed,Embase,and CINAHL were retrieved to collect relevant studies on the risk prediction models of unplanned 30-day readmission in stroke patients.The retrieval period was from the inception to April 15,2024.Two researchers conducted bias risk assessment and applicability evaluation on the included studies based on the bias risk assessment tool of the predictive model study.Results A total of 17 studies(32 models)with 108 to 803,124 patients and an outcome incidence of 2.01%to 24.1%were included.Area under the ROC curve ranged from 0.43 to 0.989.Five studies reported calibration,six underwent internal validation,one underwent external validation,and one underwent both internal and external validation.The overall applicability evaluation of 15 studies was relatively good,with 1 having low applicability and 1 being unclear.However,all of them presented a relatively high risk of bias.The high-frequency factors included age,cardiovascular comorbidities,and length of hospital stay.Conclusions Current models are still with deficiencies.Future research should improve research design and reporting process,recalibrate and externally validate existing models to enhance generalization,focusing on modifiable predictors.
作者
张琪
黄海超
吴明珠
吕浩文
姜惟馨
刘姝含
ZHANG Qi;HUANG Haichao;WU Mingzhu;LV Haowen;JIANG Weixin;LIU Shuhan(Graduate School,Tianjin University of Traditional Chinese Medicine,Tianjin 301617,China;School of Nursing,Tianjin University of Traditional Chinese Medicine,Tianjin 301617,China)
出处
《军事护理》
北大核心
2025年第10期108-112,共5页
MILITARY NURSING
基金
天津中医药大学第十四届大学生科技创新基金(ZX23)。
关键词
脑卒中
非计划再入院
预测模型
系统评价
stroke
unplanned readmission
predictive model
systematic review
