Clinical utility of neutrophil CD64 count in preterm infants within a tertiary neonatal setting. (7th June 2011)

• Record Type: Journal Article
• Authors: Hearn, R I; Hall, C D; Embleton, N D; Berrington, J E
• Is Part Of: Archives of disease in childhood. Volume 96(2011)Supplement 1
• Page Start: Fa40
• Page End: Fa40
• Publication Date: 2011-06-07
• Subjects: Infants -- Diseases -- Periodicals; Newborn infants -- Diseases -- Periodicals; Fetus -- Diseases -- Periodicals; 618.920105
• DOI: 10.1136/archdischild.2011.300164.78
• Languages: English
• ISSNs: 1359-2998

Abstract

Abstract : Background: CD64 (a neutrophil surface marker) upregulates in infection. How markers function as a point of care test (POCT) is influenced by condition prevalence. Proportionate reduction in uncertainty (PRU) is then the clinically relevant factor. Objective: To show, using PRU curves, how CD64 performs as a POCT in preterm neonates screened for late onset infection (LOI). Methods: CD64 was measured in preterm infants screened for LOI. Ethics and parental consent were obtained. Episodes were retrospectively classified as infected if blood culture (BC) positive (BC+), BC negative but 5 days treatment given (BC-), there was local infection, pneumonia or NEC. Results: 50 screenings were obtained in 38 infants, median gestation 26 weeks, birthweight 825 g. 58% of episodes were infective (BC+ (9), BC- (6), local (4), NEC (11)), falling to 38% if local infections and conservatively managed NEC were excluded. Clinicians at screening felt that 82% were definitely or probably infected, 18% being screened to rule out infection. PRU curves were developed to show how CD64 functions to reduce remaining uncertainty at various cut-off levels. A CD64 value of >3.4 reduced the remaining uncertainty of infection by a further 25%. In contrast a value of <3.4 was poor at ruling out infection, reducing residual uncertainty by only 10%. Conclusions: CD64 may assist decisions, but correct application of this and other POCT depends on clinicians' understanding of residual uncertainty, dependent on an understanding of disease prevalence and test performance.