Enhancing early mortality prediction for sepsis-associated acute respiratory distress syndrome patients via optimized machine learning algorithm: development and multiple databases’ validation of the SAFE-Mo

This study utilized the MIMIC-IV, eICU CRD, and NWICU databases to construct and validate a ML model, SAFE-Mo, which predicts early mortality in patients with sepsis-associated ARDS and outperforms traditional prediction models across all metrics. SAFE-Mo can guide clinicians to focus on critical indicators such as lactate, urine output, anion gap, and others, enabling appropriate measures to improve clinical outcomes for high-risk patients.