TUESDAY, Feb. 26, 2019 (HealthDay News) -- A new prediction rule can accurately identify febrile infants aged ≤60 days at low risk for serious bacterial infections (SBIs) using urinalysis, absolute neutrophil count (ANC), and procalcitonin levels, according to a study published online Feb. 18 in JAMA Pediatrics.
Nathan Kuppermann, M.D., M.P.H., from the University of California, Davis, School of Medicine, and colleagues developed and validated a prediction rule to identify febrile infants aged 60 days and younger at low risk for SBIs. Infants were seen at 26 emergency departments between March 2011 and May 2013. Clinical and laboratory data from 908 infants were used to derive the prediction rule, which was validated in 913 infants (mean age, 36 days).
The researchers found that serious bacterial infections were present in 9.3 percent of the 1,821 infants (1.4 percent with bacteremia, 8.3 percent with urinary tract infections, 0.5 percent with bacterial meningitis, and 0.9 percent with concurrent SBIs). Using a negative urinalysis result, an ANC of ≤4,090/µL, and serum procalcitonin of ≤1.71 ng/mL, the prediction rule identified infants at low risk for SBI. The rule had sensitivity of 97.7 percent, specificity of 60 percent, a negative predictive value of 99.6 percent, and a negative likelihood ratio of 0.04 in the validation cohort. Misclassification occurred for one infant with bacteremia and two infants with urinary tract infections, but no patients with bacterial meningitis were missed.
"Once further validated on an independent cohort, clinical application of the rule has the potential to decrease unnecessary lumbar punctures, antibiotic administration, and hospitalizations," the authors write.
One author disclosed financial ties to pharmaceutical companies, and another author holds patents for two drug-dosing devices.