Ordinal Prediction Model of 90-Day Modified Rankin Scale in Ischemic Stroke.
Ontology highlight
ABSTRACT: Background and Purpose: Prediction models for functional outcomes after ischemic stroke are useful for statistical analyses in clinical trials and guiding patient expectations. While there are models predicting dichotomous functional outcomes after ischemic stroke, there are no models that predict ordinal mRS outcomes. We aimed to create a model that predicts, at the time of hospital discharge, a patient's modified Rankin Scale (mRS) score on day 90 after ischemic stroke. Methods: We used data from three multi-center prospective studies: CRISP, DEFUSE 2, and DEFUSE 3 to derive and validate an ordinal logistic regression model that predicts the 90-day mRS score based on variables available during the stroke hospitalization. Forward selection was used to retain independent sign
SUBMITTER: Zhang MY
PROVIDER: S-EPMC8569127 | biostudies-literature | 2021
REPOSITORIES: biostudies-literature
ACCESS DATA