Authors
Zhiyang Wang, Tao You, Yujie Liu, Shifeng Li, Xin Xiao, Bin Shao, Yunnan Yao, Yanpeng Zhang, Yajing Lu, Fang Huang, Jun Wang
Published in
BMC infectious diseases. Jul 14, 2026. Epub Jul 14, 2026.
Abstract
Fast risk stratification is essential for patients with sepsis, a life-threatening condition associated with high mortality, as it guides clinical decision-making and management. In this study, we aimed to evaluate the predictive performance of a novel model-termed SOLAR-which integrates the lactate dehydrogenase-to-albumin ratio (LAR) with the Sequential Organ Failure Assessment (SOFA) score and lactate for 28-day mortality in sepsis.
Data for the derivation cohort were collected from the Medical Information Mart for Intensive Care IV database. The validation cohort was from the Department of Critical Care Medicine at the First Affiliated Hospital of Soochow University. Patients admitted to ICU for sepsis were enrolled. Model performance was analyzed by using multivariable logistic regression and Harrell's c-index. Reclassification ability of the model was evaluated by using net reclassification index (NRI) and Integrated discrimination improvement (IDI). Benefits in clinical decision making was estimated by using decision curve analysis. Super learner analysis was used to identify the optimal machine learning algorithm for model construction. Nomograms and an online calculator were used to deploy the model for point-of-care utilization.
The derivation cohort comprised 4936 patients with sepsis and sufficient SOFA, LAR, and lactate data were obtained from MIMIC database. The validation cohort contained 371 patients with sepsis admitted to the First Affiliated Hospital of Soochow University. In both cohorts, an increasing trend of 28-day mortality was observed with elevating SOFA scores, lactate levels, and LAR quartiles. Compared to the SOFA-lactate score, the SOLAR score demonstrated improved 28-day mortality discrimination, reflected by an increase in c-index (Derivation cohort: 0.695 [0.680-0.711] vs. 0.660 [0.644-0.676], P < 0.001), Validation cohort: 0.706 [0.651-0.761] vs. 0.638 [0.581-0.695], P < 0.001). The SOLAR score also displayed a superior reclassification ability over the SOFA-lactate score (NRI: Derivation cohort: 0.393 [0.335-0.451], P < 0.001), Validation cohort: 0.506 [0.302-0.709], P < 0.001, IDI: Derivation cohort: 0.034 [0.029-0.039], P < 0.001), Validation cohort: 0.044 [0.026-0.062], P < 0.001). Super learner analysis showed that the logistic regression model achieved the highest c-index (0.749 [0.694-0.803]) based on the SOLAR score. A simplified online calculator of the SOLAR score was deployed for point-of-care risk stratification.
The SOLAR score combining LAR, SOFA score and lactate provides improved accuracy and sensitivity over the SOFA-lactate score for 28-day mortality prediction in sepsis.
PMID:
42443791
Bibliographic data and abstract were imported from PubMed on 14 Jul 2026.
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