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Predictive Factors for Pneumonia Onset After Cardiac Surgery in Rio de Janeiro, Brazil

  • Marisa Santos (a1) (a2), José Ueleres Braga (a1), Renato Vieira Gomes (a2) and Guilherme L. Werneck (a1)

To develop a predictive system for the occurrence of nosocomial pneumonia in patients who had cardiac surgery performed.


Retrospective cohort study.


Two cardiologic tertiary care hospitals in Rio de Janeiro, Brazil.


Between June 2000 and August 2002, there were 1,158 consecutive patients who had complex heart surgery performed. Patients older than 18 years who survived the first 48 postoperative hours were included in the study. The occurrence of pneumonia was diagnosed through active surveillance by an infectious diseases specialist according to the following criteria: the presence of new infiltrate on a radiograph in association with purulent sputum and either fever or leukocytosis until day 10 after cardiac surgery. Predictive models were built on the basis of logistic regression analysis and classification and regression tree (CART) analysis. The original data set was divided randomly into 2 parts, one used to construct the models (ie, “test sample”) and the other used for validation (ie, “validation sample”).


The area under the receiver–operating characteristic (ROC) curve was 69% for the logistic regression model and 76% for the CART model. Considering a probability greater than 7% to be predictive of pneumonia for both models, sensitivity was higher for the logistic regression models, compared with the CART models (64% vs 56%). However, the CART models had a higher specificity (92% vs 70%) and global accuracy (90% vs 70%) than the logistic regression models. Both models showed good performance, based on the 2-graph ROC, considering that 84.6% and 84.3% of the predictions obtained by regression and CART analyses were regarded as valid.


Although our findings are preliminary, the predictive models we created showed fairly good specificity and fair sensitivity.

Corresponding author
Dsc, Institute de Medicina Social/IMS, Departamento de Epidemiologia, Universidade do Estado do Rio de Janeiro (UERJ), Rua São Francisco Xavier 524, 7° andar, Bloco D, Maracanã, Rio de Janeiro, RJ, Brazil, 20559-900 (
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Infection Control & Hospital Epidemiology
  • ISSN: 0899-823X
  • EISSN: 1559-6834
  • URL: /core/journals/infection-control-and-hospital-epidemiology
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