The ROPScore as a screening algorithm for predicting retinopathy of prematurity in a Brazilian population
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Data
2018-01-01
Autores
Do Vale Lucio, Kellen Cristiane [UNESP]
Bentlin, Maria Regina [UNESP]
de Lima Augusto, Ana Carolina [UNESP]
Corrente, José Eduardo [UNESP]
Carregal Toscano, Taísa Bertoco [UNESP]
El Dib, Regina [UNESP]
Jorge, Eliane Chaves [UNESP]
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Resumo
OBJECTIVES: To evaluate the accuracy of the ROPScore algorithm as a predictor of retinopathy of prematurity (ROP). METHODS: A prospective cohort of 220 preterm infants with a birth weight ≤1500 g and/or gestational age ≤32 weeks was included. The ROPScore was determined in the sixth week of life in 181 infants who then survived until a corrected gestational age of 45 weeks. The sensitivity, specificity, and positive (PPV) and negative predictive values (NPV) of the algorithm were analyzed. RESULTS: ROP was found in 17.6% of the preterm infants. The sensitivity of this test for any stage of ROP was 87.5%, while that for severe ROP was 95.4% (21/22 cases). The PPV and NPV were 59.6% and 97%, respectively, for any stage of ROP and 44.7% and 99.25%, respectively, for severe ROP. The ROPScore could therefore hypothetically reduce the number of ophthalmologic examinations required to detect ROP by 71.8%. CONCLUSION: The ROPScore is a useful screening tool for ROP and may optimize examinations and especially the identification of severe ROP.
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Algorithm, Preterm infants, Retinopathy of prematurity
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Clinics, v. 73.