C-Reactive Protein to Albumin Ratio Predicts Early Mortality in Hospitalized Older Patients, Independent of the Admission Diagnosis

Background: Malnutrition and systemic inflammation are prevalent among older hospitalized patients and are associated with increased morbidity and mortality. The C-reactive protein to albumin (CRP/Alb) ratio reflects inflammatory and nutritional status and may serve as a useful prognostic biomarker. Objective: To evaluate the prognostic value of the CRP/Alb ratio in predicting early in-hospital mortality in a large cohort of elderly patients, independent of the admission diagnosis. Methods: This retrospective observational study examined the clinical data and serum values of serum C-reactive protein (CRP), albumin, and the CRP/Alb ratio, detected at the time of admission, in a cohort of 2780 patients over sixty-five admitted to the Internal Medicine and Aging Department of the “Policlinico Riuniti” University Hospital Trust in Foggia, between 2019 and 2024. The predictive power of the CRP/Alb ratio for 7- and 30-day hospital mortality was evaluated by ROC curve analysis, Cox regression, and Kaplan–Meier survival analysis. Results: In total, 444 patients died (16%) during their in-hospital stay. The CRP/Alb ratio was significantly higher among deceased subjects (p < 0.001) than in non-deceased patients. The CRP/Alb ratio was strongly associated with mortality, particularly during the first 7 days from admission (AUC = 0.888). A CRP/Alb ratio >8 was an independent and significant predictor of mortality within 30 days (HR = 3.82, 95% CI: 2.91–5.01), but particularly within the first 7 days from hospitalization (HR = 10.17, 95% CI: 6.05–17.08). Similar results were observed among re-hospitalized patients. Conclusions: The CRP/Alb ratio is a significant and independent predictor of early in-hospital mortality in elderly patients, regardless of admission diagnosis. A threshold value >8 identifies individuals at high risk, particularly within the first week of hospitalization. This simple, cost-effective biomarker