MySurgeryRisk: Development and Validation of a Machine-learning Risk Algorithm for Major Complications and Death After Surgery.

ABSTRACT:

Objective

To accurately calculate the risk for postoperative complications and death after surgery in the preoperative period using machine-learning modeling of clinical data.

Background

Postoperative complications cause a 2-fold increase in the 30-day mortality and cost, and are associated with long-term consequences. The ability to precisely forecast the risk for major complications before surgery is limited.

Methods

In a single-center cohort of 51,457 surgical patients undergoing major inpatient surgery, we have developed and validated an automated analytics framework for a preoperative risk algorithm (MySurgeryRisk) that uses existing clinical data in electronic health records to forecast patient-level probabilistic risk scores for 8 major postoperative complicati

SUBMITTER: Bihorac A 

PROVIDER: S-EPMC6110979 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature