Prediction of 30-Day In-Hospital Mortality in Elderly UGIB Patients Using a Simplified Risk Score and Comparison with AIMS65 score

Abstract

Background: Upper gastrointestinal bleeding (UGIB) in elderly patients is associated with substantial in-hospital morbidity and mortality. This study aimed to develop and validate a simplified risk score for predicting 30-day in-hospital mortality in this population. Methods: A retrospective analysis was conducted on data from 1899 UGIB patients aged ≥65 years admitted to a single medical center between January 2010 and December 2019. An additional cohort of 330 patients admitted from January 2020 to October 2021 was used for external validation. Variable selection was performed using five distinct methods, and models were generated using generalized linear models, random forest, support vector machine, and k-nearest neighbors approaches. The developed score, "ABCAP," incorporated Albumin <30 g/L, Blood Urea Nitrogen (BUN) >7.5 mmol/L, Cancer presence, Altered mental status, and Pulse rate >100/min, each assigned a score of 1. Internal and external validation procedures compared the ABCAP score with the AIMS65 score. Results: In internal validation, the ABCAP score demonstrated robust predictive capability with an area under the curve (AUC) of 0.878 (95% CI: 0.824-0.932), comparable to the AIMS65 score (AUC: 0.827, 95% CI: 0.751-0.904). External validation yielded an AUC of 0.799 (95% CI: 0.709-0.889) for the ABCAP score, slightly outperforming the AIMS65 score (AUC: 0.743, 95% CI: 0.647-0.838). The ABCAP score effectively stratified mortality risk into low (0-2 points), moderate (3 points), and high (4-5 points) categories. This score exhibited consistent accuracy across variceal and non-variceal UGIB subgroups. Conclusions: The ABCAP score incorporates easily obtained clinical variables and demonstrates promising predictive ability for 30-day in-hospital mortality in elderly UGIB patients. It allows effective mortality risk stratification and showed slightly better performance than the AIMS65 score. Further cohort validation is required to confirm generalizability.