CURB-65 and Long-Term Mortality of Community-Acquired Pneumonia: A Retrospective Study on Hospitalized Patients.

Abstract

Background Community-acquired pneumonia remains a significant factor in global mortality. Several clinical scoring models are used for predicting pneumonia severity and mortality, aiding in the clinical decision relative to the therapeutic approach, including the CURB-65 score. However, currently, no models exist to identify high-risk patients relative to long-term prognosis when recent evidence reveals a significantly higher mortality rate in the first year after community-acquired pneumonia (CAP) hospitalization. Purpose of the study The purpose of this study is to evaluate the application of the CURB-65 scoring model in our population and examine its potential to predict prognosis and subsequent mortality 6 months after hospitalization. Other potential factors influencing mortality during and after hospitalization were characterized: patient demographics, nosocomial infections, readmissions, and identified pathogens. Study design We conducted a retrospective observational study, enrolling 130 patients admitted with a diagnosis of CAP in the department of internal medicine of Centro Hospitalar Universitário Cova da Beira between January and December of 2018. Consultation of electronic medical records was used to calculate the CURB-65 score on admission at the first hospitalization by CAP, categorizing patients into five risk groups. Mortality and readmission were evaluated after 30, 90, and 180 days. Key results High-risk patients (CURB>2) accounted for 96.9% of our study population. Inpatient mortality of 13%, increasing to 21.5% after six months, was similar to previous studies and was correlated to the CURB-65 score on admission. A microbiologic agent was identified in 37% of cases, with 53% isolates of Streptococcus (S.) pneumoniae. Conclusions Identifying high-risk patients is important for more individualized healthcare and management. The CURB-65 score, only validated for ashort-term (30 days) prediction, demonstrates a potential to also predict mortality and rehospitalization in the six-month period after hospitalization, as supported by our findings and previous studies.