Nomogram predicts in-hospital mortality in patients with emergency gastrointestinal bleeding: A multicenter retrospective study

Gastrointestinal bleeding (GIB) is frequently encountered in emergency departments and is associated with high morbidity and mortality rates. This study developed and internally validated an emergency department-based nomogram to estimate the risk of in-hospital mortality in patients presenting with emergency GIB. Additionally, risk factors influencing mortality rates were identified to provide emergency clinicians with an accurate prognostic tool. A retrospective cohort analysis was conducted using data from patients with GIB admitted to three branches of Wuhan Central Hospital (Nanjing Road, Houhu, and Yangchunhu) between January and December 2023. Patient data were obtained from the hospital information system. Key predictive variables were selected using least absolute shrinkage and selection operator regression, and a nomogram was constructed via multivariable logistic regression. Model discrimination was assessed by calculating the area under the receiver operating characteristic curve (AUC). Calibration and decision curve analyses were also performed to evaluate model performance. A total of 847 patients were included, with 75 (8.85%) experiencing in-hospital mortality. Non-survivors were older (median age 73 vs. 65.5 years, p < 0.001) and had lower systolic and diastolic blood pressure, higher heart rate, and elevated shock index at presentation (all p < 0.001). Ambulance arrival (p < 0.001), Emergency Severity Index Level 1 classification (p < 0.001), and the presence of malignancy (p < 0.001) were more common among those who died. Fewer non-survivors underwent surgical (p = 0.003) or hemostatic procedures (p < 0.001). Ambulance arrival, shock index > 1, ICU admission, malignancy, and hemostatic procedures were identified as independent predictors of mortality. The nomogram demonstrated good discrimination, with AUC values of 0.862 (95% CI: 0.786-0.939) in the training cohort and 0.846 (95% CI: 0.787-0.904) in the validation cohort. The developed nomogram demonstrated good discrimination and calibration and may have potential clinical utility for risk stratification in ED patients with GIB. Integration of this model into clinical information systems may assist in risk stratification and optimize patient management.