Risk factor analysis and nomogram development for predicting 28-day mortality in elderly ICU patients with sepsis and type 2 diabetes mellitus

Abstract

Background: Type 2 diabetes mellitus (T2DM) significantly contributes to sepsis, with patients suffering from both conditions exhibiting greater severity and higher mortality rates compared to those with sepsis alone. Elderly individuals in the intensive care unit (ICU) are particularly prone to these comorbidities. A nomogram prediction model was developed to accurately assess prognosis and guide treatment for elderly patients with sepsis and T2DM. Methods: Data from 1489 patients with sepsis and T2DM in the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were analyzed and categorized into 28-days survival ( n = 1156) and 28-days death groups ( n = 333). The dataset’s clinical characteristics were employed to create a nomogram predicting 28-days mortality in elderly ICU patients with sepsis and T2DM. The least absolute shrinkage and selection operator (LASSO) regression identified candidate predictors, followed by a multivariate logistic regression analysis incorporating variables with p < .05 into the final model. A nomogram was then constructed using these significant risk predictors. The model’s discriminatory power was evaluated through a receiver operating curve (ROC) and the area under the curve (AUC). Additionally, model performance was assessed using a calibration plot and the Hosmer-Lemeshow goodness-of-fit test (HL test), and clinical utility was examined via decision curve analysis (DCA). Results: Risk factors incorporated into the nomogram included age, ICU length of stay, mean blood pressure (MBP), metastatic solid tumor, Sequential Organ Failure Assessment (SOFA) score, Logistic Organ Dysfunction System (LODS) score, blood urea nitrogen (BUN), and vasopressor use. The predictive model demonstrated robust discrimination, with an AUC of 0.802 (95% CI 0.768–0.835) in the training dataset and 0.753 (95% CI 0.697–0.809) in the validation set. Calibration was confirmed with the HL test ( p > .05), and DCA indicated clinical usefulness. Conclusion: This new nomogram serves as a practical tool for predicting 28-days mortality among elderly ICU patients with sepsis and T2DM. Optimizing treatment strategies based on this model could enhance 28-days survival rates for these patients.