Use of Routine Hematological and Biochemical Parameters to Predict Clinical Outcomes in Community-acquired Pneumonia.

Abstract

Background: Community-acquired pneumonia (CAP) is a major cause of hospitalization and mortality, especially among elderly individuals and those with chronic comorbidities. Identifying reliable prognostic markers at the time of hospital admission remains a clinical challenge.

Objectives: To evaluate the prognostic value of routinely measured hematological and biochemical parameters, specifically lymphocyte count, serum albumin, procalcitonin, neutrophil-to-lymphocyte ratio (NLR), and C-reactive protein (CRP)/albumin ratio (CAR), in predicting in-hospital mortality and length of stay in patients with CAP.

Materials and methods: This retrospective, single-center cohort study included all adult patients hospitalized with radiologically and clinically confirmed CAP between September 2022 and September 2023. Demographic, clinical, and laboratory data were collected. NLR and CAR were calculated based on admission values. Statistical analyses included group comparisons, correlation analysis, and ROC curve analysis to determine prognostic accuracy.

Results: A total of 526 patients were included (mean age: 66.2 years; 53.5% female), of which in-hospital mortality occurred in 9.5%. Non-survivors had significantly lower lymphocyte and albumin levels and higher CRP, procalcitonin, NLR, and CAR values (P < 0.05). ROC analysis showed that lymphocyte count (AUC = 0.794) and albumin (AUC = 0.787) had the highest predictive accuracy, followed by procalcitonin (AUC = 0.774), NLR (AUC = 0.715), and CAR (AUC = 0.710). CRP and WBC showed lower discriminative power. Significant positive correlations were observed between CRP, procalcitonin, NLR, CAR, and length of hospital stay.

Conclusions: Lymphocyte count, serum albumin, procalcitonin, NLR, and CRP/albumin ratio are significant prognostic markers for mortality and prolonged hospitalization in patients with community-acquired pneumonia. These routinely available parameters may aid in early risk stratification and clinical decision making.