title: Prediction of severe retinopathy of prematurity using the WINROP algorithm in a birth cohort in South East Scotland.
abstract: OBJECTIVE
  We tested the ability of the 'Weight, IGF-1, Neonatal Retinopathy of Prematurity (WINROP)' clinical algorithm to detect preterm infants at risk of severe Retinopathy of Prematurity (ROP) in a birth cohort in the South East of Scotland. In particular, we asked the question: 'are weekly weight measurements essential when using the WINROP algorithm?'
  
  
  METHODS
  This was a retrospective cohort study. Anonymised clinical data were uploaded to the online WINROP site, and infants at risk of developing severe ROP were identified. The results using WINROP were compared with the actual ROP screening outcomes. Infants with incomplete weight data were included in the whole group, but were excluded from a subgroup analysis of infants with complete weight data. In addition, data were manipulated to test whether missing weight data points in the early neonatal period would lead to loss of sensitivity of the algorithm.
  
  
  RESULTS
  The WINROP algorithm had 73% sensitivity for detecting infants at risk of severe ROP when all infants were included and 87% when the complete weight data subgroup was analysed. Manipulation of data from the complete weight data subgroup demonstrated that one or two missing weight data points in the early postnatal period lead to loss of sensitivity performance by WINROP.
  
  
  CONCLUSIONS
  The WINROP program offers a non-invasive method of identifying infants at high risk of severe ROP and also identifying those not at risk. However, for WINROP to function optimally, it has to be used as recommended and designed, namely weekly body weight measurements are required.
authors.affiliation: Neonatal Unit, Simpson Centre for Reproductive Health, Royal Infirmary of Edinburgh, , Edinburgh, UK.
authors.forename: Chinthika
authors.initials: C
authors.lastname: Piyasena
authors.forename: Catherine
authors.initials: C
authors.lastname: Dhaliwal
authors.forename: Heather
authors.initials: H
authors.lastname: Russell
authors.forename: Ann
authors.initials: A
authors.lastname: Hellstrom
authors.forename: Chatarina
authors.initials: C
authors.lastname: Löfqvist
authors.forename: Ben J
authors.initials: BJ
authors.lastname: Stenson
authors.forename: Brian W
authors.initials: BW
authors.lastname: Fleck
mesh_terms: D000465:Algorithms; D001724:Birth Weight / Q000502:physiology*; D015331:Cohort Studies; D005260:Female; D005865:Gestational Age; D006801:Humans; D007231:Infant, Newborn; D007234:Infant, Premature; D007334:Insulin-Like Growth Factor I / Q000378:metabolism*; D007363:Intensive Care Units, Neonatal; D008297:Male; D008403:Mass Screening / Q000379:methods*; D015861:Retinal Neovascularization / Q000097:blood / Q000175:diagnosis; D012178:Retinopathy of Prematurity / Q000097:blood / Q000175:diagnosis*; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D012606:Scotland; D012680:Sensitivity and Specificity
chemical_list: D007334:Insulin-Like Growth Factor I
keywords: Clinical Algorithm; Neonatology; Ophthalmology; Retinopathy of Prematurity; Weight