Ontology highlight
ABSTRACT: Background
Surgical risk prediction models traditionally use patient attributes and measures of physiology to generate predictions about postoperative outcomes. However, the surgeon's assessment of the patient may be a valuable predictor, given the surgeon's ability to detect and incorporate factors that existing models cannot capture. We compare the predictive utility of surgeon intuition and a risk calculator derived from the American College of Surgeons (ACS) NSQIP.Study design
From January 10, 2021 to January 9, 2022, surgeons were surveyed immediately before performing surgery to assess their perception of a patient's risk of developing any postoperative complication. Clinical data were abstracted from ACS NSQIP. Both sources of data were independently used to build mo
SUBMITTER: Marwaha JS
PROVIDER: S-EPMC10192014 | biostudies-literature | 2023 Jun
REPOSITORIES: biostudies-literature