摘要
目的 系统评价心血管疾病患者院内心脏骤停风险预测模型,为临床实践和科学研究提供参考。方法 计算机检索CBM、CNKI、WanFang Data、PubMed、ScienceDirect、Web of Science、The Cochrane Library、Wiley Online Journals和Scopus数据库,搜集关于心血管疾病患者院内心脏骤停风险预测模型的研究,检索时限均从2010年1月至2022年7月。由2名研究员独立筛选文献、提取资料并评价纳入研究的偏倚风险。结果 共纳入5个研究,其中4个为回顾性研究,研究对象主要是急性冠脉综合征患者,有2个模型采用决策树建模。5个模型的受试者工作特征曲线下面积或C统计量为0.720~0.896,仅1个模型进行外部验证和时间验证。纳入预测模型中最常见的心血管疾病患者院内心脏骤停易感因素和速发因素分别为年龄、糖尿病和Killip分级、心肌肌钙蛋白水平。偏倚风险评价发现,4个模型为高风险,1个模型为不清楚,不同领域存在偏倚风险问题较多,存在样本量不足(n=4)、变量处理不当(n=4)、未提供缺失数据如何处理(n=3)和模型表现评价不完整(n=5)等问题。结论 心血管疾病患者院内心搏骤停风险预测模型的预测效能较好,但是模型质量均有待提高,需在数据来源、预测因素的选择和测量及缺失数据处理和模型评价等方面提高研究质量。此外,应对现有模型进行外部验证,以更好地指导临床。
Objective To systematically review risk prediction models of in-hospital cardiac arrest in patients with cardiovascular disease, and to provide references for related clinical practice and scientific research for medical professionals in China. Methods Databases including CBM, CNKI, WanFang Data, PubMed, ScienceDirect, Web of Science, The Cochrane Library, Wiley Online Journals and Scopus were searched to collect studies on risk prediction models for in-hospital cardiac arrest in patients with cardiovascular disease from January 2010 to July 2022. Two researchers independently screened the literature, extracted data, and evaluated the risk of bias of the included studies.Results A total of 5 studies(4 of which were retrospective studies) were included. Study populations encompassed mainly patients with acute coronary syndrome. Two models were modeled using decision trees. The area under the receiver operating characteristic curve or C statistic of the five models ranged from 0.720 to 0.896, and only one model was verified externally and for time. The most common risk factors and immediate onset factors of in-hospital cardiac arrest in patients with cardiovascular disease included in the prediction model were age, diabetes, Killip class, and cardiac troponin.There were many problems in analysis fields, such as insufficient sample size(n=4), improper handling of variables(n=4),no methodology for dealing with missing data(n=3), and incomplete evaluation of model performance(n=5).Conclusion The prediction efficiency of risk prediction models for in-hospital cardiac arrest in patients with cardiovascular disease was good;however, the model quality could be improved. Additionally, the methodology needs to be improved in terms of data sources, selection and measurement of predictors, handling of missing data, and model evaluations. External validation of existing models is required to better guide clinical practice.
作者
蔡真真
陈媛
林碧霞
CAI Zhenzhen;CHEN Yuan;LIN Bixia(Department of Nursing,Xiamen Cardiovascular Hospital,Xiamen University,Xiamen 361006,P.R.China)
出处
《中国循证医学杂志》
CSCD
北大核心
2022年第10期1175-1181,共7页
Chinese Journal of Evidence-based Medicine
基金
2020年厦门市医疗卫生指导性项目(编号:3502Z20209137)
2021年厦门市临床重点专科建设项目(编号:厦卫科教[2021]215号)。
关键词
心脏骤停
院内
心血管
风险预测
模型
系统评价
Cardiac arrest
In-hospital
Cardiovascular
Risk prediction
Model
Systematic review
