Development and internal validation of a Septic Shock Clinical Score System (SCSS) for predicting 28-day mortality in pediatric patients: a single-center retrospective study

Predicting short-term mortality in pediatric septic shock is difficult due to the variability of the condition and the restricted practicality of current severity scoring frameworks. This study was conducted to determine predictors of 28-day mortality in children with septic shock. The study developed the Septic Shock Clinical Score System (SCSS) and performed internal validation of the score. This single-center retrospective observational study included pediatric patients (0–16 years) with septic shock admitted to the pediatric intensive care unit of Shanxi Children’s Hospital between January 2020 and December 2024. Clinical variables, including mechanical ventilation and vasoactive medication use, and laboratory parameters obtained within the first 24 h after PICU admission were collected. Univariable logistic regression and least absolute shrinkage and selection operator (LASSO) regression were used for predictor selection. A multivariable logistic regression model was constructed, and a point-based Septic Shock Clinical Score System (SCSS) was derived. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots with bootstrap resampling, and decision curve analysis. The primary outcome was 28-day mortality. A total of 123 children with septic shock were included, of whom 83 (67.5%) died within 28 days. Four variables were independently associated with mortality: mechanical ventilation (OR 23.95, 95% CI 6.97-100.54), use of ≥ 2 vasoactive agents (OR 6.95, 95% CI 2.08–26.59), prolonged prothrombin time (PT > 18 s; OR 5.33, 95% CI 1.82–17.05), and elevated troponin T (TnT > 40 ng/L; OR 6.70, 95% CI 1.93–28.69). SCSS scores ranged from 0 to 5 points, with higher scores associated with an increased risk of 28-day mortality. The model demonstrated favorable apparent discrimination within the study population (AUC 0.902, 95% CI 0.839–0.965) and apparent calibration based on internal bootstrap validation with 1,000 resamples. SCSS-based risk stratification demonstrated significant differences in 28-day mortality across low-, intermediate-, and high-risk groups (23.8%, 90.0%, and 90.9%, respectively; log-rank P < 0.001). Decision curve analysis demonstrated considerable clinical utility across a wide range of threshold probabilities. The SCSS may represent a simple tool for early risk stratification in pediatric septic shock using variables available within the first 24 h of Pediatric Intensive Care Unit (PICU) admission. Although the model demonstrated encouraging apparent predictive performance in this single-center study population, the internal validation was performed on the final fitted model after predictor selection and may therefore provide optimistic performance estimates. Accordingly, the results should be interpreted with caution, and external validation in larger multicenter studies is required to confirm model performance and further optimize clinically meaningful risk stratification before broader clinical application.