Predictive Value of the CRP/Albumin Ratio in Mortality Prediction in Hip Fracture Surgery Patients Admitted to...

Background: Hip fracture surgery patients admitted to the intensive care unit (ICU) have high postoperative mortality, and early risk stratification remains challenging. This study aimed to evaluate the predictive value of the C-reactive protein/albumin ratio (CAR) for 30-day and 90-day mortality in hip fracture surgery patients admitted to the ICU. Methods: This retrospective cohort study included 134 adult patients who underwent surgery for hip fracture and were admitted to the ICU between June 2021 and June 2023. Demographic characteristics, comorbidities, APACHE II and SAPS II scores, and laboratory parameters measured within the first 24 h of ICU admission were recorded. CAR was calculated by dividing CRP (mg/L) by albumin (g/dL). The primary outcomes were 30-day and 90-day mortality. Cox proportional hazards regression analysis was performed to identify independent predictors of mortality, and receiver operating characteristic (ROC) curve analysis was used to assess the discriminative ability of CAR. Results: The 30-day and 90-day mortality rates were 10.4% and 22.4%, respectively. CAR and serum albumin levels were significantly associated with both 30-day and 90-day mortality (p < 0.01), whereas CRP alone was not. In ROC analysis, CAR demonstrated excellent predictive performance for 30-day mortality (AUC: 0.991; 95% CI: 0.975-1.000; cutoff: 38.46; sensitivity: 92.9%; specificity: 92.5%) and good performance for 90-day mortality (AUC: 0.847; 95% CI: 0.776-0.918; cutoff: 25.43). Cox regression analysis identified CAR as an independent predictor of both 30-day (Exp(B) = 1.048, p < 0.001) and 90-day mortality (Exp(B) = 1.025, p = 0.002). Conclusions: The CRP/albumin ratio is a strong and independent predictor of short- and mid-term mortality in hip fracture surgery patients admitted to the ICU. Due to its simplicity and rapid availability, CAR may serve as a practical adjunctive biomarker for early risk stratification in this high-risk population.