A Novel Composite Bioscore Integrating Biomarkers, Clinical Scores, and Comorbidity Indices for Prognostic Stratification in Sepsis
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background: Risk stratification in sepsis remains a major clinical challenge in hospital settings, where timely recognition of disease progression can critically influence outcomes. Traditional scoring systems, such as SOFA and APACHE II, are frequently applied but are limited by their complexity and inconsistent predictive accuracy. Integrating biological markers with clinical scores may enhance the early identification of patients with an unfavorable prognosis. Objective: The objective of this investigation was to determine the prognostic performance of two composite scoring systems, BIO-S and BIO-SC, in predicting 28-day mortality among patients with sepsis or septic shock. Methods: We conducted a retrospective single-center study including 125 adult surgical patients with sepsis or septic shock. BIO-S was calculated using procalcitonin (PCT), neutrophil-to-lymphocyte ratio (NLR), INR, and SOFA score, whereas BIO-SC extended this model by incorporating the Charlson Comorbidity Index (CCI). Both bioscores were calculated at admission and analyzed in relation to 28-day mortality and discharge status. Results: Among the 125 patients included, 28-day all-cause mortality was 36% (n = 45). The BIO-SC score achieved the highest predictive accuracy for 28-day mortality (AUC = 0.942), surpassing BIO-S (AUC = 0.930), SOFA (AUC = 0.928), and APACHE II (AUC = 0.918). Both bioscores correlated strongly with discharge outcomes and were independent predictors of 28-day mortality (p < 0.001). Conclusion: Integrating inflammatory biomarkers, organ dysfunction, and comorbidity burden into composite prognostic models such as BIO-S and BIO-SC significantly improves early mortality risk assessment and outcome prediction in sepsis, although external validation remains necessary.
Source: Journal of Inflammation Research
DOI: 10.2147/jir.s579172
Institution: "Dunarea de Jos" University of Galati
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,836
OpenAlex ID: W7131121258
