医学
支气管肺发育不良
荟萃分析
梅德林
批判性评价
数据提取
系统回顾
统计的
研究异质性
重症监护医学
儿科
统计
内科学
怀孕
胎龄
病理
替代医学
遗传学
数学
政治学
法学
生物
作者
Michelle Romijn,Paula Dhiman,Martijn J J Finken,Anton H. van Kaam,Trixie A Katz,Joost Rotteveel,Ewoud Schuit,Gary S. Collins,Wes Onland,Héloïse Torchin
标识
DOI:10.1016/j.jpeds.2023.01.024
摘要
To review systematically and assess the accuracy of prediction models for bronchopulmonary dysplasia (BPD) at 36 weeks of postmenstrual age.Searches were conducted in MEDLINE and EMBASE. Studies published between 1990 and 2022 were included if they developed or validated a prediction model for BPD or the combined outcome death/BPD at 36 weeks in the first 14 days of life in infants born preterm. Data were extracted independently by 2 authors following the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (ie, CHARMS) and PRISMA guidelines. Risk of bias was assessed using the Prediction model Risk Of Bias ASsessment Tool (ie, PROBAST).Sixty-five studies were reviewed, including 158 development and 108 externally validated models. Median c-statistic of 0.84 (range 0.43-1.00) was reported at model development, and 0.77 (range 0.41-0.97) at external validation. All models were rated at high risk of bias, due to limitations in the analysis part. Meta-analysis of the validated models revealed increased c-statistics after the first week of life for both the BPD and death/BPD outcome.Although BPD prediction models perform satisfactorily, they were all at high risk of bias. Methodologic improvement and complete reporting are needed before they can be considered for use in clinical practice. Future research should aim to validate and update existing models.
科研通智能强力驱动
Strongly Powered by AbleSci AI