| Literature DB >> 31418042 |
Hendrik-Jan Mijderwijk1, Ewout W Steyerberg2,3, Hans-Jakob Steiger1, Igor Fischer4, Marcel A Kamp1.
Abstract
Clinical prediction models in neurosurgery are increasingly reported. These models aim to provide an evidence-based approach to the estimation of the probability of a neurosurgical outcome by combining 2 or more prognostic variables. Model development and model reporting are often suboptimal. A basic understanding of the methodology of clinical prediction modeling is needed when interpreting these models. We address basic statistical background, 7 modeling steps, and requirements of these models such that they may fulfill their potential for major impact for our daily clinical practice and for future scientific work.Keywords: Aneurysmal subarachnoid hemorrhage; Clinical prediction; Model development; Neurosurgery; Outcome; Risk assessment
Mesh:
Year: 2019 PMID: 31418042 DOI: 10.1093/neuros/nyz282
Source DB: PubMed Journal: Neurosurgery ISSN: 0148-396X Impact factor: 4.654