Abstract: Objective To investigate the risk factors for multiple organ dysfunction syndrome (MODS) in elderly patients with upper gastrointestinal bleeding (UGIB) and to develop a nomogram prediction model for early clinical identification of the high-risk patients. Methods A retrospective cohort study was conducted involving 365 elderly UGIB patients admitted to 986th Hospital of Xijing Hospital, Air Force Medical University from March 2022 to March 2025. All the patients were divided into a MODS group (n=55) and a non-MODS group (n=310). LASSO regression was used to select variables, and multivariate logistic regression analysis was applied to identify risk factors for MODS in elderly UGIB patients. Based on these results, a nomogram prediction model was constructed. Results Six variables [blood loss, hemorrhagic shock, hemoglobin level, systemic inflammatory response syndrome (SIRS), cardiovascular disease, and Sequential Organ Failure Assessment (SOFA) score] were selected through LASSO regression and incorporated into a multivariate logistic regression analysis, which showed that hemorrhagic shock, SIRS, and cardiovascular disease were independent risk factors for MODS in elderly UGIB patients (P<0.05), while high hemoglobin level was a protective factor (P<0.05). The nomogram prediction model constructed based on these factors showed good fit (Hosmer-Lemeshow test:χ²=4.544,P=0.631), high discriminative ability (C-index=0.972), excellent predictive performance (AUC=0.972), and strong clinical applicability. Conclusions Hemorrhagic shock, SIRS, cardiovascular disease and low hemoglobin level were independent risk factors for MODS in elderly UGIB patients. The nomogram model, developed from these factors, demonstrated good performance in predicting MODS risk among elderly UGIB patients, potentially enabling timely intervention for high-risk individuals.

Key words: upper gastrointestinal bleeding, multiple organ dysfunction syndrome, risk factors, prediction model, aged