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Optimizing Mortality Prediction in Critical Care: Synergistic Value of Serum Uric Acid and APACHE II Score Assessment
Yugeng Liu1, Jia Wang2, Junyu Wang2
1Department of Infectious Diseases and Clinical Microbiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Background:
Uric acid (UA) has dual roles as both an antioxidant and pro-oxidant, with its levels linked to either protective or harmful effects depending on concentration and clinical context. While extreme UA levels correlate with poor outcomes in critical care, integrating UA with clinical scores like APACHE II may improve risk stratification for intensive care unit (ICU) patients.
Study Objectives:
This retrospective cohort study investigated the prognostic significance of admission UA levels combined with APACHE II scores in critically ill patients.
Methods:
We analyzed 380 patients admitted to the Emergency Intensive Care Unit (EICU) at our Hospital from 2015 to 2021, tracking 28-day postdischarge mortality. Clinical parameters including APACHE II scores, UA, procalcitonin (PCT), C-reactive protein (CRP), D-dimer, creatinine (Cr), white blood cells (WBC), and platelets (PLT) were recorded within 24 h of admission. Multivariate regression models and receiver operating characteristic (ROC) curve analysis were employed for statistical evaluation.
Results:
The nonsurvival group (n = 72) demonstrated significantly elevated age (68.2 ± 12.1 vs 62.5 ± 15.3 years, p < 0.01), APACHE II scores (24.6 ± 7.2 vs 16.8 ± 6.5), and UA levels (456.3 ± 178.4 vs 342.1 ± 152.6 µmol/L) compared to survivors (n = 308). Multivariate analysis identified APACHE II (OR = 1.32, 95% CI 1.18-1.47, p < 0.001) and UA (OR = 1.01, 95% CI 1.003-1.018, p = 0.007) as independent mortality predictors. The combined UA-APACHE II model achieved superior prognostic accuracy (AUC = 0.788) compared to either parameter alone (UA AUC = 0.627; APACHE II AUC = 0.767).
Conclusions:
Admission UA levels synergistically enhance the prognostic value of APACHE II scores for mortality prediction in EICU patients. This biomarker combination provides a potentially clinically actionable approach for risk stratification in critical care management.
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