Evaluating Outcome Prediction Models in Endovascular Stroke Treatment Using Baseline, Treatment, and Posttreatment Variables.

ABSTRACT:

Background

Statistical models to predict outcomes after endovascular therapy for acute ischemic stroke often incorporate baseline (pretreatment) variables only. We assessed the performance of stroke outcome prediction models for endovascular therapy in stroke in an iterative fashion using baseline, treatment-related, and posttreatment variables.

Methods

Data from the ESCAPE-NA1 (Safety and Efficacy of Nerinetide [NA-1] in Subjects Undergoing Endovascular Thrombectomy for Stroke) trial were used to build 4 outcome prediction models using multivariable logistic regression: model 1 included baseline variables available before treatment decision making, model 2 included additional treatment-related variables, model 3 additional posttreatment variables that become available early

SUBMITTER: Ospel JM 

PROVIDER: S-EPMC12512352 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature