Research Article: A laboratory-based selected logistic model for early prediction of 28-day mortality in patients with septic shock
Abstract:
Early risk stratification in septic shock requires transparent models based on variables available soon after clinical diagnosis of septic shock. We reanalysed a retrospective cohort using the original screening strategy: candidate predictors with univariable P <?0.05 were entered into multivariable logistic regression, and variables with multivariable P <?0.05 were retained in the final model.
The analysis included 250 patients with complete 28-day outcome and laboratory data. The outcome was 28-day mortality. Candidate predictors comprised demographics, comorbidities, complete blood count, chemistry, coagulation, inflammatory markers, arterial pH, and PaO2/FiO2. Laboratory values were treated as the first available values within 24?h after clinical diagnosis of septic shock. The final fixed model and the complete model-development pipeline were internally validated using 1,000 bootstrap resamples. Discrimination, calibration, Brier score, ROC-derived cutoff, decision curve analysis, LAR comparison, restricted cubic spline analysis, VIF, and LASSO sensitivity analysis were reported.
Among 250 patients, 73 died by day 28 (29.2%). Univariable screening identified 12 candidate predictors, and multivariable screening retained lactate, D-dimer, and PaO2/FiO2. The final equation was logit( P )?=?0.412145?+?0.250015?×?Lactate?+?0.046852?×?D-dimer - 0.016820?×?PaO2/FiO2. The apparent AUC was 0.902 (95% CI 0.864–0.940), and the optimism-corrected AUC for the fixed final model was 0.897. When the complete model-development pipeline was repeated within 1,000 bootstrap resamples, the optimism-corrected AUC was 0.875. The final model had higher discrimination than LAR alone [0.902 (0.864–0.940) vs. 0.719 (0.645–0.793); DeLong P <?0.001].
A selected logistic model using lactate, D-dimer, and PaO2/FiO2 provided internally validated early risk estimates for 28-day mortality. External validation is required before routine clinical use.
Introduction:
Early risk stratification in septic shock requires transparent models based on variables available soon after clinical diagnosis of septic shock. We reanalysed a retrospective cohort using the original screening strategy: candidate predictors with univariable P <?0.05 were entered into multivariable logistic regression, and variables with multivariable P <?0.05 were retained in the final model.
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