In-hospital mortality risk factors in community acquired pneumonia: evaluation of immunocompetent adult patients without comorbidities

• Main Author: Vicco,Miguel Hernan
• Publication Date: 2015
• Other Authors: Ferini,Franco, Rodeles,Luz, Scholtus,Patricia, Long,Ana Karina, Musacchio,Héctor Mario
• Format: Article
• Language: eng
• Source: Revista da Associação Médica Brasileira (Online)
• Download full: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-42302015000200144
• topic: pneumonia; in-hospital mortality; risk factors

Summary Objective: several scores were developed in order to improve the determination of community acquired pneumonia (CAP) severity and its management, mainly CURB-65 and SACP score. However, none of them were evaluated for risk assessment of in-hospital mortality, particularly in individuals who were non-immunosuppressed and/or without any comorbidity. In this regard, the present study was carried out. Methods: we performed a cross-sectional study in 272 immunocompetent patients without comorbidities and with a diagnosis of CAP. Performance of CURB- 65 and SCAP scores in predicting in-hospital mortality was evaluated. Also, variables related to death were assessed. Furthermore, in order to design a model of in-hospital mortality prediction, sampled individuals were randomly divided in two groups. The association of the variables with mortality was weighed and, by multiple binary regression, a model was constructed in one of the subgroups. Then, it was validated in the other subgroup. Results: both scores yielded a fair strength of agreement, and CURB-65 showed a better performance in predicting in-hospital mortality. In our casuistry, age, white blood cell counts, serum urea and diastolic blood pressure were related to death. The model constructed with these variables showed a good performance in predicting in-hospital mortality; moreover, only one patient with fatal outcome was not correctly classified in the group where the model was constructed and in the group where it was validated. Conclusion: our findings suggest that a simple model that uses only 4 variables, which are easily accessible and interpretable, can identify seriously ill patients with CAP