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Dataset Information

Development and internal validation of time-to-event risk prediction models for major medical complications within 30 days after elective colectomy.


ABSTRACT:

Background

Patients undergoing colectomy are at risk of numerous major complications. However, existing binary risk stratification models do not predict when a patient may be at highest risks of each complication. Accurate prediction of the timing of complications facilitates targeted, resource-efficient monitoring. We sought to develop and internally validate Cox proportional hazards models to predict time-to-complication of major complications within 30 days after elective colectomy.

Methods

We studied a retrospective cohort from the multicentered American College of Surgeons National Surgical Quality Improvement Program procedure-targeted colectomy dataset. Patients aged 18 years or above, who underwent elective colectomy between January 1, 2014 and December 31, 2019 were

SUBMITTER: Ke JXC 

PROVIDER: S-EPMC11611139 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature