Integrating dynamic SOFA changes and age to predict 28-day mortality in ICU patients: a nomogram and machine learning validation study

Dynamic changes in SOFA scores (ΔSOFA 3-1), especially in patients with moderate baseline SOFA 1 scores (4-11), significantly improve prognostic accuracy when combined with age. The nomogram provides an intuitive bedside tool for early risk stratification, whereas the XGBoost model demonstrates the potential value of machine learning. External validation highlights the need for further multicenter studies to enhance model generalizability.