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Published on: November 29, 2024
Admission Biomarkers as Predictors of Mortality in Comatose Patients in the Intensive Care Unit: A Retrospective
Pompiliu Mircea Bogdan1, Roxana Elena Bogdan-Goroftei1, Alina Plesea-Condratovici1
1Doctoral School of Biomedical Sciences, Faculty of Medicine and Pharmacy, Research Center in the Medical-Pharmaceutical Field, "Dunarea de Jos" University of Galati, 47 Domneasca Str., 800008 Galati, Romania.
Abstract:
Background: Intensive care units (ICUs) provide management of critically ill patients requiring continuous monitoring and complex therapeutic interventions. The aim of this study was to analyze the clinical and biological characteristics associated with mortality in patients admitted to the intensive care unit. Methods: This retrospective observational study included 108 adult patients admitted to the Anesthesia and Intensive Care Unit of the "Sf. Apostol Andrei" Emergency County Clinical Hospital in Galați, who were in a coma at the time of admission. Demographic data, comorbidities, clinical parameters and biological biomarkers determined at admission were analyzed. Statistical analysis was performed using the SPSS program and included non-parametric tests (Mann-Whitney U), Spearman correlation analysis, multivariate logistic regression and ROC curve analysis to evaluate the predictive performance of biomarkers. Results: Hypertension (60.2%) and diabetes mellitus (35.2%) were the most common comorbidities. Comparative analysis revealed significant differences between deceased and surviving patients for several biological parameters, including leukocytes, C-reactive protein, LDH, D-dimers, INR and APTT. In multivariate analysis, LDH (OR = 0.998; p < 0.001) and APTT (OR = 0.951; p = 0.033) remained independently associated with mortality. ROC analysis revealed good discrimination capacity for LDH (AUC ≈ 0.805) and moderate performance for APTT. Conclusions: Determination of LDH and APTT at the time of admission to the ICU may provide useful information for assessing the prognosis of critically ill patients and for early stratification of mortality risk.