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A Novel Scoring System for Coronary Care Unit Patients: Merging SAPS 2 and Troponin I for Improved Prognostication

Alam, M. S.; Zafar, K. S.; Amir, S. H.; Haque, S. F.

2025-01-16 intensive care and critical care medicine
10.1101/2025.01.15.25320621 medRxiv
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AimsThis study aimed to develop a novel prognostic scoring system for coronary care unit (CCU) patients by integrating the Simplified Acute Physiology Score II (SAPS II) with cardiac-specific biomarkers, including Troponin I (Trop I), NT-proBNP, lactate, AST, and ALT. The objective was to enhance the prediction of in-hospital mortality by addressing limitations of existing scoring systems. MethodsThis prospective observational study included 25 adult patients admitted to a tertiary care hospitals CCU with acute coronary syndrome (ACS) and acute decompensated heart failure (ADHF). Clinical and laboratory parameters, including Troponin I (Trop I), NT-proBNP, lactate, AST, ALT, and SAPS II scores, were collected upon admission. Logistic regression analysis identified independent predictors of mortality, and a new scoring system was developed. The predictive accuracy of the system was evaluated using receiver operating characteristic (ROC) analysis. ResultsThe novel scoring system demonstrated superior discriminatory performance with an area under the ROC curve (AUC) of 0.8897 compared to SAPS II alone (AUC: 0.8493). Troponin I emerged as the most significant predictor of mortality (p < 0.05), while SAPS II showed a trend toward significance. The optimal cutoff score for the new system was determined to be 4.716, achieving a sensitivity of 75% and specificity of 94.12%. Elevated lactate, Trop I and SAPS 2 score levels were strongly associated with mortality. DiscussionThe new scoring system integrates systemic and cardiac-specific parameters, enhancing the predictive accuracy of in-hospital mortality in CCU patients compared to SAPS II alone. While Trop I proved highly predictive, other biomarkers (NT-proBNP, AST, ALT, lactate) did not achieve statistical significance in multivariate analysis, likely due to the limited sample size. Future validation in larger cohorts is required to confirm its generalizability and clinical utility. This study underscores the potential of combining systemic and cardiac-specific biomarkers to refine risk stratification in CCU settings, offering a robust tool for guiding clinical decision-making.

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