Related Experiment Video
Updated: Oct 4, 2025

Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors
Published on: February 16, 2024
Development and validation of a multivariable prediction model in open abdomen patients for entero-atmospheric
Adam T Cristaudo1,2, Kerry Hitos1,2, Ronny Gunnarsson3,4,5
1Sydney Medical School, The University of Sydney, Sydney, Australia.
Background:
Laparostomy or Open Abdomen (OA) has matured into an effective strategy in the management of abdominal catastrophe. Single prognostic factors have been identified in a previous systematic review regarding entero-atmospheric fistula (EAF). Unfortunately, no prognostic multivariable model for EAF exist. The aim was to develop and validate a multivariable prediction model from a retrospective cohort study involving three hospital's databases.
Methods:
Fifty-seven variables were evaluated to develop a multivariable model. Univariate and multivariable logistic regression analyses were performed for on a developmental data set from two hospitals. Receiver operator characteristics analysis with area under the curve (AUC) and 95% confidence intervals (CI) were performed on the developmental data set (internal validation) as well as on an additional validation data set from another hospital (external validation).
Results:
Five-hundred and forty-eight patients managed with an OA. Two variables remained in the multivariable prediction model for EAF. The AUC for EAF on internal validation were 0.74 (95% CI: 0.58-0.86) and 0.79 (95% CI: 0.67-0.92) on external validation.
Conclusions:
A multivariable prediction model for EAF was externally validated and an easy-to-use probability nomogram was constructed using the two predictor variables.
Level Of Evidence:
III; prognostic.
More Related Videos
06:04Author Spotlight: Establishment and Confirmation of a Postnatal Right Ventricular Volume Overload Mouse Model
Published on: June 9, 2023
08:25A Rat Graft Rejection Model of Intestinal Transplantation with Exteriorized Ileostomy for Longitudinal Prognosis Assessment
Published on: June 10, 2025