JOURNAL ARTICLE
MULTICENTER STUDY
RESEARCH SUPPORT, N.I.H., EXTRAMURAL
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Neonatal candidiasis: epidemiology, risk factors, and clinical judgment.

Pediatrics 2010 October
OBJECTIVE: Invasive candidiasis is a leading cause of infection-related morbidity and mortality in extremely low birth weight (<1000-g) infants. We quantified risk factors that predict infection in premature infants at high risk and compared clinical judgment with a prediction model of invasive candidiasis.

METHODS: The study involved a prospective observational cohort of infants≤1000 g birth weight at 19 centers of the Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network. At each sepsis evaluation, clinical information was recorded, cultures were obtained, and clinicians prospectively recorded their estimate of the probability of invasive candidiasis. Two models were generated with invasive candidiasis as their outcome: (1) potentially modifiable risk factors; and (2) a clinical model at time of blood culture to predict candidiasis.

RESULTS: Invasive candidiasis occurred in 137 of 1515 (9.0%) infants and was documented by positive culture from ≥1 of these sources: blood (n=96); cerebrospinal fluid (n=9); urine obtained by catheterization (n=52); or other sterile body fluid (n=10). Mortality rate was not different for infants who had positive blood culture compared with those with isolated positive urine culture. Incidence of candida varied from 2% to 28% at the 13 centers that enrolled≥50 infants. Potentially modifiable risk factors included central catheter, broad-spectrum antibiotics (eg, third-generation cephalosporins), intravenous lipid emulsion, endotracheal tube, and antenatal antibiotics. The clinical prediction model had an area under the receiver operating characteristic curve of 0.79 and was superior to clinician judgment (0.70) in predicting subsequent invasive candidiasis.

CONCLUSION: Previous antibiotics, presence of a central catheter or endotracheal tube, and center were strongly associated with invasive candidiasis. Modeling was more accurate in predicting invasive candidiasis than clinical judgment.

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