Development and Validation of a Predictive Nomogram for 30-Day Mortality in Sepsis Patients Coexisting with Malignant Tumors ： a Retrospective Cohort Study Using the MIMIC-IV Database

Background Sepsis is the main cause of death for cancer patients, and our study aims to evaluate risk factors and develop a model to predict the 30-Day mortality in sepsis patients coexisting with malignant tumors. Methods We obtained 4196 sepsis patients coexisting with malignant tumors from the MIMIC-IV database and randomly split them into a training set (2937 patients) and a validation set (1259 patients) at a ratio of 7:3. A multivariable logistic regression model was used to identify independent risk factors for predicting mortality, and the model's performance was evaluated. Results Multivariable logistic regression analysis showed that age, gender, CPD, diabetes, AKI, heart rate, APACHE III, cardiovascular system, anion gap, BUN, calcium, creatinine, bilirubin, pH, and PCO2 were independent risk factors. The nomogram achieved optimal performance in discrimination, calibration, and clinical application. Conclusion The nomogram effectively predicts the 30-Day mortality in sepsis patients coexisting with malignant tumors, and internal validation confirms its effectiveness. The study results can help clinical doctors make decisions on the treatment of these patients, thus reducing the risk of sepsis and death for cancer patients.