| Literature DB >> 33216849 |
Sabri Soussi, Gary S Collins, Peter Jüni, Alexandre Mebazaa, Etienne Gayat, Yannick Le Manach.
Abstract
Interest in developing and using novel biomarkers in critical care and perioperative medicine is increasing. Biomarkers studies are often presented with flaws in the statistical analysis that preclude them from providing a scientifically valid and clinically relevant message for clinicians. To improve scientific rigor, the proper application and reporting of traditional and emerging statistical methods (e.g., machine learning) of biomarker studies is required. This Readers' Toolbox article aims to be a starting point to nonexpert readers and investigators to understand traditional and emerging research methods to assess biomarkers in critical care and perioperative medicine.Year: 2021 PMID: 33216849 DOI: 10.1097/ALN.0000000000003600
Source DB: PubMed Journal: Anesthesiology ISSN: 0003-3022 Impact factor: 7.892