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Published on: April 2, 2021
[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
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.
Background:
Premature infants are often stressed by the current retinopathy of prematurity (ROP) screening procedure. Additionally, only < 10 % of the screened infants will develop a ROP stadium requiring laser therapy. Therefore the present screening strategy is unsatisfactory. Furthermore, the current guidelines do not take into account postnatal factors. A new method considering postnatal factors is the weight, insulin-like growth factor, neonatal ROP (WINROP) algorithm. This approach is based on the early postnatal weight gain. The aim of this study was to assign the WINROP-algorithm to a preterm population in Switzerland and to analyze its ability for prediction.
Patients And Methods:
In this retrospective study, all preterm infants with a gestational age (GA) < 32 weeks and/or a birth weight (BW) ≤ 1500 g taken care of in the Department of Neonatology at the University Hospital Zurich from January 2003 to December 2008 were included. The weekly postnatal weight gain was analyzed by means of the modified WINROP-algorithm.
Results:
Altogether 376 preterm infants were analyzed. In 58 infants a "high-risk" alarm was released, thereof eight preterms developed a severe ROP and four of them needed laser therapy.
Conclusions:
The high predictive value of the WINROP-algorithm was confirmed in our population of Swiss preterms. This instrument has the potential to simplify the current ROP screening procedure. Accordingly, the amount of ophthalmoscopies could be reduced significantly.
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