2026-10-14T17:19:16Z https://www.scidb.cn/oai

10.57760/sciencedb.zhwzzyxzz.00243 2026-09-08T09:47:47Z

2026-09-08 Development and Validation of a Nomogram Model for Predicting 28-Day Mortality in Emergency Surgery Patients doi:10.57760/sciencedb.zhwzzyxzz.00243 en Objective Emergency surgery patients often face significantly increased risks of postoperative complications and mortality due to complex conditions and urgent surgical timing. This study aimed to develop and validate a nomogram based on multivariate analysis to predict 28-day survival in emergency surgery patients, thereby improving perioperative risk assessment and clinical decision-making.Methods Clinical data of adult patients who underwent emergency surgery under general anesthesia at Sir Run Run Shaw Hospital between January 2020 and June 2024 were retrospectively collected. Inclusion criteria were age ≥18 years and surgery duration >1 hour. Patients with previous emergency surgery or missing data >50% were excluded. All eligible cases were randomly divided into a training set（80%） and a validation set（20%）. Predictor variables were selected using least absolute shrinkage and selection operator（LASSO） regression, followed by multivariate logistic regression to construct the predictive model and develop the nomogram. Model discrimination was assessed by the area under the receiver operating characteristic curve（AUC）, calibration was evaluated using 1000-bootstrap resampling, and clinical utility was examined through decision curve analysis（DCA）.Results A total of 1,956 patients were included, with 1,369 in the training set and 587 in the validation set. Seven independent prognostic factors were identified: sex, Charlson Comorbidity Index（CCI）, neutrophil count, lymphocyte count, fibrinogen, blood urea nitrogen（BUN）, and uric acid（UA）. The nomogram achieved AUC values of 0.759 in the training set and 0.725 in the validation set, indicating good discrimination. Calibration curves demonstrated excellent agreement between predicted and observed outcomes. DCA showed substantial net clinical benefit across a risk threshold range of 5%–80%.Conclusion The developed nomogram model effectively predicts 28-day survival in emergency surgery patients and provides a reliable tool for preoperative risk assessment and individualized management, offering significant potential for clinical application. Emergency surgery; Nomogram; Risk prediction; Survival rate; Multivariate analysis Jinmin.Chen Yuanqiang.Lu PUBLIC https://creativecommons.org/publicdomain/zero/1.0/ dataset Science Data Bank