title: Efficacy of the screening algorithm WINROP in a Korean population of preterm infants.
abstract: 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.
authors.affiliation: Department of Ophthalmology, Chonnam National University Medical School and Hospital, Gwangju, South Korea.
authors.forename: Jung-Han
authors.initials: JH
authors.lastname: Choi
authors.forename: Chatarina
authors.initials: C
authors.lastname: Löfqvist
authors.forename: Ann
authors.initials: A
authors.lastname: Hellström
authors.forename: Hwan
authors.initials: H
authors.lastname: Heo
mesh_terms: D000465:Algorithms; D044466:Asian People / Q000208:ethnology; D001724:Birth Weight / Q000502:physiology*; D003199:Computer Systems; D005260:Female; D005865:Gestational Age; D006801:Humans; D007231:Infant, Newborn; D007234:Infant, Premature; D007363:Intensive Care Units, Neonatal; D008297:Male; D056910:Republic of Korea / Q000453:epidemiology; D015861:Retinal Neovascularization / Q000145:classification / Q000175:diagnosis* / Q000208:ethnology; D012171:Retinal Vessels / Q000473:pathology; D012178:Retinopathy of Prematurity / Q000145:classification / Q000175:diagnosis* / Q000208:ethnology; D012307:Risk Factors; D012680:Sensitivity and Specificity