A New Prediction Model for Prolonged Hospitalization in Adult Community-Acquired Pneumonia (CAP) Patients.

ABSTRACT

BACKGROUND: As a serious and common out-of-hospital infectious disease, community-acquired pneumonia (CAP) ranks among the leading causes of death in both developing and developed countries. In recent years, the increasing incidence of CAP has led to an increase in the number of hospitalizations. Although CURB-65 (or CRB-65) and pneumonia severity Index (PSI) scoring systems are widely used in CAP prognostic scoring systems, each score had some limitations in predicting whether patients with CAP would require prolonged hospitalization. The aim of this study was to analyze serum inflammatory biomarkers combined with age to establish a novel predictive model for predicting prolonged hospitalization in patients with CAP. METHODS: In a retrospective study, serum inflammatory biomarkers were collected from all enrolled CAP patients, including white blood cell count (WBC), high-sensitivity C-reactive protein (hs-CRP), erythrocyte sedimentation rate (ESR), D-dimer, procalcitonin (PCT), fibrinogen (FIB), and ICU treatment. Length of hospital stay and age were also recorded. The 75th percentile of length of stay in the enrolled population was defined as long hospitalization over time, and the primary predictor of outcome was prolonged hospitalization. Univariate analysis and binary logistic regression analysis were used to explore the independent risk factors which could be components of a new predicting model for prolonged hospitalization in CAP patients. ROC curves were used to evaluate the sensitivity and specificity of the new model, which consisted of the combination of all independent risk factors in predicting the main outcomes. RESULTS: The results showed that among 364 patients with CAP, 85 had extended hospitalization (85/364). Further analysis showed that age, white blood cell, fibrinogen, and high-sensitivity C-reactive protein were independent risk factors for extended hospitalization in patients with CAP. Finally, the AUC of the ROC curve of the new prediction model (the joint model consists of age, WBC, FIB, and hs-CRP) was 0.93 (95% CI 0.90 - 0.96), and the sensitivity and specificity were 87.1% and 87.8%, respectively. CONCLUSIONS: Serum inflammatory biomarkers combined age have high specificity and sensitivity in predicting prolonged hospitalization in adult CAP patients.