Addressing common sources of bias in studies of new-onset type 2 diabetes following COVID that use electronic health record data
DIABETES EPIDEMIOLOGY AND MANAGEMENT(2024)
摘要
Observational studies based on cohorts built from electronic health records (EHR) form the backbone of our current understanding of the risk of new -onset diabetes following COVID. EHR-based research is a powerful tool for medical research but is subject to multiple sources of bias. In this viewpoint, we define key sources of bias that threaten the validity of EHR-based research on this topic (namely misclassification, selection, surveillance, immortal time, and confounding biases), describe their implications, and suggest best practices to avoid them in the context of COVID-diabetes research. (c) 2023 The Authors. Published by Elsevier Masson SAS. This is an open access article under the CC BY -NC -ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
更多查看译文
关键词
Diabetes,COVID-19,Epidemiology,Bias,SARS-CoV-2
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要