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Prediction of severe retinopathy of prematurity using the screening algorithm WINROP in preterm infants
Nurullah Koçak1, Leyla Niyaz2, Nursen Ariturk2
1Samsun Training and Research Hospital Ophthalmology Department, Ilkadim, Samsun, Turkey.
Insights
The WINROP algorithm effectively predicts retinopathy of prematurity (ROP) in preterm infants, potentially reducing necessary eye examinations by 40%. This system offers a valuable, easy-to-use monitoring tool for neonatal care.
Area of Science:
- Neonatal Medicine
- Ophthalmology
- Pediatric Research
Background:
- Retinopathy of prematurity (ROP) is a significant cause of visual impairment in preterm infants.
- Early detection and treatment are crucial for preventing severe visual outcomes.
- Current screening methods can be resource-intensive.
Purpose of the Study:
- To evaluate the sensitivity and specificity of the Weight gain, Insulin-like growth factor 1, and Neonatal retinopathy of prematurity (WINROP) algorithm.
- To assess WINROP's predictive accuracy for proliferative retinopathy of prematurity (ROP) in Turkish preterm infants.
- To determine if WINROP can optimize ROP screening protocols.
Main Methods:
- Retrospective analysis of medical records for infants screened for ROP between 2007 and 2014.
- Weekly monitoring of birth weights until postmenstrual week 36 using the WINROP online database.
- Calculation of sensitivity, specificity, and predictive values for the WINROP algorithm.
Main Results:
- The study included 223 preterm infants; 53% received a high-risk WINROP alert.
- WINROP demonstrated a sensitivity of 84.3% and a specificity of 52.8% for predicting ROP.
- Implementing WINROP could potentially reduce the total number of infant eye examinations by 40%.
Conclusions:
- The WINROP online system is a practical and effective tool for monitoring ROP risk in preterm infants.
- This algorithm can help streamline ROP screening, reducing the burden on healthcare resources.
- WINROP facilitates easier and potentially more efficient management of ROP surveillance.
Purpose:
To assess the sensitivity and specificity of weight gain, insulin-like growth factor 1 (IGF-1), and neonatal retinopathy of prematurity (WINROP) algorithm to predict proliferative retinopathy of prematurity (ROP), in a Turkish population of preterm infants.
Methods:
The medical records of infants screened and monitored for ROP from 2007 to 2014 were analyzed retrospectively. Birth weights of infants born before 32 weeks' gestation were recorded on the WINROP online database system weekly until postmenstrual week 36. The sensitivity, specificity, and positive and negative predictive values of the WINROP algorithm were analyzed.
Results:
A total of 223 infants were included. WINROP yielded a low-risk result in 106 infants (48%) and a high-risk result (red alarm) in the remaining 117 infants (53%). The sensitivity of the WINROP online system was found to be 84.3% (27/32), whereas its specificity was found to be 52.8% (101/191). The time between the first alarm and treatment was 8.59 ± 3.92 (2-15) weeks. Using this algorithm, 106 infants would not have needed eye examinations, possibly resulting in a 40% decrease in the total number of examinations.
Conclusions:
The WINROP online system is a valuable and easy-to-use monitoring system that could decrease the number of infant ROP examinations.
