A laboratory-based selected logistic model for early prediction of 28-day mortality in patients with septic shock.
5 affiliations
- 1The Blood Transfusion Department, the First People's Hospital of Yibin City, Yibin, China.
- 2The Laboratory Department, the Third People's Hospital of Yibin City, Yibin, China.
- 3The Intensive Care Unit, the First People's Hospital of Yibin City, Yibin, China.
- 4The Laboratory Department, the First People's Hospital of Yibin City, Yibin, China.
- 5School of Laboratory Medicine, North Sichuan Medical College, Nanchong, China.
Abstract
Background
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.Methods
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.Results
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].Conclusions
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.
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BibTeX
@article{zhang2026laboratorybased,
title = {{A laboratory-based selected logistic model for early prediction of 28-day mortality in patients with septic shock.}},
author = {Liying Zhang and Pu Chen and Jie Li and Weilei Xiao and Wentao Zhou},
journal = {Frontiers in medicine},
year = {2026},
month = oct,
doi = {10.3389/fmed.2026.1864043},
url = {https://europepmc.org/article/MED/42948084},
note = {CC BY},
}
RIS
TY - JOUR
TI - A laboratory-based selected logistic model for early prediction of 28-day mortality in patients with septic shock.
AU - Liying Zhang
AU - Pu Chen
AU - Jie Li
AU - Weilei Xiao
AU - Wentao Zhou
PY - 2026
DA - 2026/10/13
JO - Frontiers in medicine
DO - 10.3389/fmed.2026.1864043
UR - https://europepmc.org/article/MED/42948084
AB - Background 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.Methods 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.Results 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].Conclusions 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.
SN - 2296-858X
ER -