Importance Clinicians, patients, and policy makers rely on published results from clinical
trials to help make evidence-informed decisions. To critically evaluate and use trial results …

Background Homelessness continues to be a pressing public health concern in many
countries, and mental disorders in homeless persons contribute to their high rates of …

Abstract The coronavirus disease 2019 (COVID-19) pandemic has overwhelmed healthcare
services, faced with the twin challenges in acutely meeting the medical needs of patients …

Background Missing data are unavoidable in epidemiological research, potentially leading
to bias and loss of precision. Multiple imputation (MI) is widely advocated as an …

Background Among patients with heart failure who have mitral regurgitation due to left
ventricular dysfunction, the prognosis is poor. Transcatheter mitral-valve repair may improve …

Missing data are ubiquitous in medical research. Although there is increasing guidance on
how to handle missing data, practice is changing slowly and misapprehensions abound …

Background Missing data may seriously compromise inferences from randomised clinical
trials, especially if missing data are not handled appropriately. The potential bias due to …

Objectives Missing data is a common problem during the development, evaluation, and
implementation of prediction models. Although machine learning (ML) methods are often …

Background Long-term outcomes after percutaneous coronary intervention (PCI) with
contemporary drug-eluting stents, as compared with coronary-artery bypass grafting …

Because missing data are present in almost every study, it is important to handle missing
data properly. First of all, the missing data mechanism should be considered. Missing data …