Development and validation of a nomogram for predicting 28-day in-hospital mortality in sepsis patients based on an optimized APACHE II score

The objective of this study is to establish a nomogram that correlates optimized APACHE II score with sepsis-related indicators, aiming to provide a robust model for early prediction of sepsis prognosis in clinical practice and serve as a valuable reference for improved diagnosis and treatment strategies.This retrospective study extracted sepsis patients meeting the inclusion criteria from the MIMIC-IV database to form the training group. An optimized Acute Physiology and Chronic Health Evaluation (APACHE) II score integrated with relevant indicators was developed using a nomogram for predicting the prognosis of sepsis patients. External validation was conducted using data from the Intensive Care Unit at Lanzhou University Second Hospital.The study enrolled 1805 patients in the training cohort and 203 patients in the validation cohort. A multifactor analysis was conducted to identify factors affecting patient mortality within 28 days, resulting in the development of an Optimized Score by simplifying evaluation indicators from APACHE II score. The results showed that the Optimized Score (AUC = 0.715) had a higher area under receiver operating characteristic curve than SOFA Score (AUC = 0.637) but slightly lower than APACHE II score (AUC = 0.720). Significant indicators identified through multifactor analysis included platelet count, total bilirubin level, albumin level, prothrombin time, activated partial thromboplastin time, mechanical ventilation (MV) use and renal replacement therapy (RRT) use. These seven indicators were combined with Optimized Score to construct a nomogram Based on these seven indicators. The nomogram demonstrated good clinical predictive value in both training cohort (AUC = 0.803) and validation cohort (AUC = 0.750). Calibration curves and decision curve analyses also confirmed its good predictive ability, surpassing the APACHE II score and SOFA score in identifying high-risk patients.The Nomogram was established in this study using the MIMIC-IV database and validated with external data, demonstrating its robust discriminability, calibration, and clinical practicability for predicting 28-day mortality in sepsis patients. These findings aim to provide substantial support for clinicians' decision-making.