RESUMO
BACKGROUND: The objective of this study was to construct a model for predicting the risk of serious bacterial infection (SBI) in febrile infants. METHODS: A total of 135 febrile infants younger than 3 months of age who met the inclusion criteria were assessed on the following: physical appearance, complete blood count, serum C-reactive protein (CRP), urinalysis, stool smears for white blood cell (WBC) count if diarrhea was apparent, and blood and urine cultures. Chest X-rays were performed if respiratory symptoms were evident. Cerebrospinal fluid was analyzed if central nervous system infection was suspected. RESULTS: Of the 135 infants, 34 were diagnosed with SBI. Data from 99 infants were used to construct a model for predicting SBI by multivariate logistic regression. Sex (male), spun urine WBC count (>or= 10 per high-powered field [400x]) and CRP (>or= 3.6 mg/L) were significantly related to SBI. A probability cut-off of 0.265 was selected, where values below and above the cut-off reflected low and high SBI risk respectively. Data from the remaining 36 infants were used to test model validity. Both sensitivity and specificity were 77.8% for predicting SBI using this model. CONCLUSION: These findings suggest that sex, serum CRP concentration and spun urine WBC count can be used to accurately predict SBI in febrile infants aged less than 3 months of age.