Background: The prognosis of critically ill patients is closely linked to their gastrointestinal (GI) function. The acute GI injury (AGI) grading system, established in 2012, is extensively utilized to evaluate GI dysfunction and forecast outcomes in clinical settings. In 2021, the GI dysfunction score (GIDS) was developed, building on the AGI grading system, to enhance the accuracy of GI dysfunction severity assessment, improve prognostic predictions, reduce subjectivity, and increase reproducibility.
Aim: To compare the predictive capabilities of GIDS and the AGI grading system for 28-day mortality in critically ill patients.
Methods: A retrospective study was conducted at the general intensive care unit (ICU) of a regional university hospital. All data were collected during the first week of ICU admission. The primary outcome was 28-day mortality. Multivariable logistic regression analyzed whether GIDS and AGI grade were independent risk factors for 28-day mortality. The predictive abilities of GIDS and AGI grade were compared using the receiver operating characteristic curve, with DeLong's test assessing differences between the curves' areas.
Results: The incidence of AGI in the first week of ICU admission was 92.13%. There were 85 deaths (47.75%) within 28 days of ICU admission. There was no initial 24-hour difference in GIDS between the non-survival and survival groups. Both GIDS (OR 2.01, 95%CI: 1.25-3.24; P = 0.004) and AGI grade (OR 1.94, 95%CI: 1.12-3.38; P = 0.019) were independent predictors of 28-day mortality. No significant difference was found between the predictive accuracy of GIDS and AGI grade for 28-day mortality during the first week of ICU admission (Z = -0.26, P = 0.794).
Conclusion: GIDS within the first 24 hours was an unreliable predictor of 28-day mortality. The predictive accuracy for 28-day mortality from both systems during the first week was comparable.
Keywords: Acute gastrointestinal injury; Critical illness; Gastrointestinal dysfunction; Intensive care unit outcomes; Mortality prediction; Predictive modeling; Prognostic indicators; Risk stratification.
©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.