Prediction of Retinopathy of Prematurity Using the Screening Algorithm WINROP in a Mexican Population of Preterm Infants

Archives of ophthalmology (Impact Factor: 4.4). 06/2012; 130(6):720-3. DOI: 10.1001/archophthalmol.2012.215
Source: PubMed


To retrospectively validate the WINROP (weight, insulin-like growth factor I, neonatal, retinopathy of prematurity [ROP]) algorithm in identification of type 1 ROP in a Mexican population of preterm infants.
In infants admitted to the neonatal intensive care unit at Hospital Civil de Guadalajara from 2005 to 2010, weight measurements had been recorded once weekly for 192 very preterm infants (gestational age [GA] <32 weeks) and for 160 moderately preterm infants (GA ≥32 weeks). Repeated eye examinations had been performed and maximal ROP stage had been recorded. Data are part of a case-control database for severe ROP risk factors.
Type 1 ROP was found in 51.0% of very preterm and 35.6% of moderately preterm infants. The WINROP algorithm correctly identified type 1 ROP in 84.7% of very preterm infants but in only 5.3% of moderately preterm infants. For infants with GA less than 32 weeks, the specificity was 26.6%, and for those with GA 32 weeks or more, it was 88.3%.
In this Mexican population of preterm infants, WINROP detected type 1 ROP early in 84.7% of very preterm infants and correctly identified 26.6% of infants who did not develop type 1 ROP. Uncertainties in dating of pregnancies and differences in postnatal conditions may be factors explaining the different outcomes of WINROP in this population.

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    ABSTRACT: Objective: To develop a birth weight (BW), gestational age (GA), and postnatal-weight gain retinopathy of prematurity (ROP) prediction model in a cohort of infants meeting current screening guidelines. Methods: Multivariate logistic regression was applied retrospectively to data from infants born with BW less than 1501 g or GA of 30 weeks or less at a single Philadelphia hospital between January 1, 2004, and December 31, 2009. In the model, BW, GA, and daily weight gain rate were used repeatedly each week to predict risk of Early Treatment of Retinopathy of Prematurity type 1 or 2 ROP. If risk was above a cut-point level, examinations would be indicated. Results: Of 524 infants, 20 (4%) had type 1 ROP and received laser treatment; 28 (5%) had type 2 ROP. The model (Children's Hospital of Philadelphia [CHOP]) accurately predicted all infants with type 1 ROP; missed 1 infant with type 2 ROP, who did not require laser treatment; and would have reduced the number of infants requiring examinations by 49%. Raising the cut point to miss one type 1 ROP case would have reduced the need for examinations by 79%. Using daily weight measurements to calculate weight gain rate resulted in slightly higher examination reduction than weekly measurements. Conclusions: The BW-GA-weight gain CHOP ROP model demonstrated accurate ROP risk assessment and a large reduction in the number of ROP examinations compared with current screening guidelines. As a simple logistic equation, it can be calculated by hand or represented as a nomogram for easy clinical use. However, larger studies are needed to achieve a highly precise estimate of sensitivity prior to clinical application.
    No preview · Article · Dec 2012 · Archives of ophthalmology
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    No preview · Article · Dec 2012 · New England Journal of Medicine
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