A functional outcome prediction model of acute traumatic spinal cord injury based on extreme gradient boost.

ABSTRACT:

Objective

We aimed to construct a nonlinear regression model through Extreme Gradient Boost (XGBoost) to predict functional outcome 1 year after surgical decompression for patients with acute spinal cord injury (SCI) and explored the importance of predictors in predicting the functional outcome.

Methods

We prospectively enrolled 249 patients with acute SCI from 5 primary orthopedic centers from June 1, 2016, to June 1, 2020. We identified a total of 6 predictors with three aspects: (1) clinical characteristics, including age, American Spinal Injury Association (ASIA) Impairment Scale (AIS) at admission, level of injury and baseline ASIA motor score (AMS); (2) MR imaging, mainly including Brain and Spinal Injury Center (BASIC) score; (3) surgical timing, specifically comparin

SUBMITTER: Sizheng Z 

PROVIDER: S-EPMC9559032 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature