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Efficacy of the screening algorithm WINROP in a Korean population of preterm infants
Jung-Han Choi1, Chatarina Löfqvist, Ann Hellström
1Department of Ophthalmology, Chonnam National University Medical School and Hospital, Gwangju, South Korea.
Insights
The WINROP algorithm effectively predicts retinopathy of prematurity (ROP) in Korean preterm infants, showing 90% sensitivity. Adjusting the algorithm may enhance ROP prediction and decrease retinal exams.
Area of Science:
- Neonatal Medicine
- Ophthalmology
- Medical Informatics
Background:
- Retinopathy of prematurity (ROP) is a leading cause of blindness in preterm infants.
- Early detection and treatment of ROP are crucial for preventing vision loss.
- Predictive algorithms can aid in timely ROP management.
Purpose of the Study:
- To evaluate the WINROP algorithm's efficacy in predicting sight-threatening retinopathy of prematurity (ROP) in a Korean cohort.
- To assess the algorithm's sensitivity and specificity in identifying infants requiring treatment for ROP.
Main Methods:
- Retrospective review of 314 preterm infants (gestational age < 32 weeks) from 2006-2010.
- Weekly neonatal body weight measurements were entered into the WINROP surveillance system.
- Infants were categorized into high-risk and low-risk groups based on WINROP alarms.
Main Results:
- WINROP identified 52.9% of infants as high-risk, with 36 developing type 1 ROP requiring treatment.
- The algorithm demonstrated 90% sensitivity in detecting type 1 ROP.
- Low-risk infants rarely developed ROP, with only 4 cases identified, some with comorbidities.
Conclusions:
- The WINROP algorithm shows high sensitivity for predicting type 1 ROP in Korean preterm infants.
- Population-specific adjustments to WINROP may improve its predictive accuracy.
- Optimizing WINROP could reduce the need for frequent retinal examinations, easing clinical burden.
Objective:
To investigate the efficacy of WINROP (https://winrop.com), an algorithm based on serial measurements of neonatal body weight to predict proliferative retinopathy of prematurity (ROP), in a Korean population of preterm infants.
Methods:
The records of preterm infants with gestational age less than 32 weeks who were admitted to the neonatal intensive care unit at Chonnam National University Hospital, Gwangju, South Korea, from October 2006 to November 2010 were reviewed. The body weight of infants was measured weekly and entered into a computer-based surveillance system, WINROP, and the outcome was analyzed.
Results:
A total of 314 preterm infants participated in the study. The mean gestational age was 29 weeks (range, 25-32 weeks). The mean body weight was 1263 g (range, 590-2260 g). For 166 of 314 infants (52.9%), a high-risk alarm was noted. In the high-risk alarm group, 36 infants developed type 1 ROP, according to the Early Treatment for Retinopathy of Prematurity criteria, and they were treated for ROP. The remaining 148 infants (47.1%) had a low-risk alarm. In the low-risk alarm group, 3 infants with bronchopulmonary dysplasia and intraventricular hemorrhage, a risk factor for ROP, and 1 infant without any risk factors for ROP developed type 1 ROP and were treated.
Conclusions:
In a Korean population, the WINROP algorithm had a sensitivity of 90% for identifying infants with type 1 ROP. Although some limitations are present, adjustment to the WINROP algorithm for a specific population may improve the efficacy of predicting proliferative ROP and reduce the frequency of retinal examinations.
