Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus · 2016
Colorado retinopathy of prematurity model: a multi-institutional validation study.
СтатьяМногоцентровое исследованиеВалидационное исследованиеНазвание и аннотация: Перевод в очереди
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Cao Jennifer H, Wagner Brandie D, Cerda Ashlee, McCourt Emily A, Palestine Alan, Enzenauer Robert W, Braverman Rebecca S, Wong Ryan K, Tsui Irena, Gore Charlotte, Robbins Shira L, Puente Michael A, Kauffman Levi, Kong Lingkun, Morrison David G, Lynch Anne M
Аннотация
PURPOSE: The Colorado retinopathy of prematurity (ROP) prediction model (CO-ROP), developed using a cohort of infants from Colorado, calls for ROP examination of infants meeting all of the following criteria: gestational age of ≤30 weeks, birth weight of ≤1500 g, and a net weight gain of ≤650 g between birth and 4 weeks of age. The purpose of this study was to perform an external validation to assess the sensitivity and specificity of the CO-ROP model in a larger cohort of babies screened for ROP from four academic institutions in the United States.
METHODS: The medical records of neonates screened for ROP according current national guidelines was conducted at 4 US academic centers were retrospectively reviewed. Sensitivity, specificity, and respective 95% confidence intervals in detecting ROP using CO-ROP were calculated for type 1, type 2, and any grade of ROP.
RESULTS: A total of 858 cases were included. The CO-ROP algorithm had a sensitivity of 98.1% (95% CI, 93.3%-99.8%) for type 1 ROP, 95.6% (95% CI 78.0-99.9%) for type 2 ROP, and 95.0% (95% CI, 93.1-97.4%) for all grades of ROP. The CO-ROP model would have reduced the total number of infants screened by 23.9% compared to current 2013 screening guidelines.
CONCLUSIONS: CO-ROP demonstrated high sensitivity in predicting ROP and would have greatly reduced the number of infants needing examination.
METHODS: The medical records of neonates screened for ROP according current national guidelines was conducted at 4 US academic centers were retrospectively reviewed. Sensitivity, specificity, and respective 95% confidence intervals in detecting ROP using CO-ROP were calculated for type 1, type 2, and any grade of ROP.
RESULTS: A total of 858 cases were included. The CO-ROP algorithm had a sensitivity of 98.1% (95% CI, 93.3%-99.8%) for type 1 ROP, 95.6% (95% CI 78.0-99.9%) for type 2 ROP, and 95.0% (95% CI, 93.1-97.4%) for all grades of ROP. The CO-ROP model would have reduced the total number of infants screened by 23.9% compared to current 2013 screening guidelines.
CONCLUSIONS: CO-ROP demonstrated high sensitivity in predicting ROP and would have greatly reduced the number of infants needing examination.
Предметные рубрики MeSH
AlgorithmsBirth WeightCohort StudiesColoradoDiagnostic Techniques, OphthalmologicalFemaleGestational AgeHumansInfantInfant, Extremely Low Birth WeightInfant, NewbornInfant, Very Low Birth WeightMaleModels, StatisticalNeonatal ScreeningRetinopathy of PrematurityRetrospective StudiesRisk FactorsSensitivity and SpecificityWeight Gain