[The early postnatal weight gain as a predictor of retinopathy of prematurity]

S Flückiger1, H U Bucher, A Hellström

  • 1Klinik für Neonatologie, UniversitätsSpital Zürich, Schweiz. sarah_flk@hotmail.com

Klinische Monatsblatter Fur Augenheilkunde
|April 13, 2011
PubMed

Insights

The WINROP algorithm effectively predicts retinopathy of prematurity (ROP) in Swiss preterm infants, potentially reducing unnecessary eye exams. This method uses early postnatal weight gain to identify high-risk infants.

Area of Science:

  • Neonatology
  • Ophthalmology
  • Pediatrics

Context:

  • Current retinopathy of prematurity (ROP) screening is stressful for premature infants.
  • Less than 10% of screened infants require ROP treatment, indicating an inefficient screening process.
  • Existing guidelines for ROP screening do not incorporate crucial postnatal factors.

Purpose:

  • To evaluate the predictive accuracy of the WINROP algorithm in a Swiss preterm infant population.
  • To assess the WINROP algorithm's ability to identify infants at high risk for severe ROP.
  • To determine if the WINROP algorithm can optimize ROP screening protocols.

Summary:

  • A retrospective study analyzed 376 preterm infants (GA < 32 weeks or BW ≤ 1500 g) using a modified WINROP algorithm based on weekly postnatal weight gain.
  • The WINROP algorithm issued a "high-risk" alarm for 58 infants.
  • Of those flagged, eight developed severe ROP, and four required laser therapy.

Impact:

  • The WINROP algorithm demonstrated high predictive value in Swiss preterm infants, confirming its clinical utility.
  • Implementing the WINROP algorithm could significantly simplify current ROP screening procedures.
  • This approach has the potential to substantially decrease the number of required ophthalmoscopies, reducing healthcare costs and infant stress.
Abstract

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