title: Algorithms for the prediction of retinopathy of prematurity based on postnatal weight gain.
abstract: Current ROP screening guidelines represent a simple risk model with two dichotomized factors, birth weight and gestational age at birth. Pioneering work has shown that tracking postnatal weight gain, a surrogate for low insulin-like growth factor 1, may capture the influence of many other ROP risk factors and improve risk prediction. Models including weight gain, such as WINROP, ROPScore, and CHOP ROP, have demonstrated accurate ROP risk assessment and a potentially large reduction in ROP examinations, compared to current guidelines. However, there is a need for larger studies, and generalizability is limited in countries with developing neonatal care systems.
authors.affiliation: Division of Ophthalmology, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA. binenbaum@email.chop.edu
authors.forename: Gil
authors.initials: G
authors.lastname: Binenbaum
mesh_terms: D000465:Algorithms; D001724:Birth Weight; D005865:Gestational Age; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007234:Infant, Premature / Q000254:growth & development*; D007334:Insulin-Like Growth Factor I / Q000032:analysis*; D015997:Neonatal Screening / Q000191:economics; D049451:Nomograms; D011237:Predictive Value of Tests; D012178:Retinopathy of Prematurity / Q000175:diagnosis*; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D015430:Weight Gain
chemical_list: D007334:Insulin-Like Growth Factor I