Predicting Sepsis Mortality: An Elastic-Net Regression Model versus the Sequential Organ Failure Assessment Score

Introduction: The Sequential Organ Failure Assessment version 1 (SOFA-1) score defines organ dysfunction in Sepsis-3. However, this score describes illness severity rather than predicts mortality. This study evaluated whether routine continuous admission variables improve mortality prediction. Methods: This retrospective cohort included 465 adults with sepsis admitted to intensive care units between March 2022 and March 2024. Overall, 114 patients died in hospital. Candidate predictor sets included six continuous SOFA-1 proxies and 14 additional routine admission variables. Models were evaluated using 20 repeats of stratified 10-fold cross-validation. The primary model was an elastic-net penalised logistic regression. Discrimination was compared using the paired DeLong test. Results: On held-out folds, the elastic-net model achieved an area under the curve (AUC) of 0.846. In comparison, SOFA-1 achieved an AUC of 0.711 (difference 0.134, 95% confidence interval (CI) 0.074 to 0.195; p < 0.001). The six-proxy model improved AUC by 0.089 (95% CI 0.033 to 0.144). The Glasgow Coma Scale alone matched SOFA-1 discrimination (difference in AUC 0.035, 95% CI − 0.025 to 0.096; p = 0.240). Adding age and sex to SOFA-1 yielded no significant change (difference in AUC 0.000, 95% CI − 0.017 to 0.018). Conclusions: Routinely recorded continuous admission variables predicted in-hospital mortality better than SOFA-1 in this cohort. Prospective external validation is required before clinical use.