• Pediatric Ophth/Strabismus

    This study found that a new ROP screening model from the Children's Hospital of Philadelphia accurately assesses risk while significantly reducing the number of ROP examinations.

    The model builds off of the Premature Infants in Need of Transfusion ROP model and was developed using a cohort that included larger, more mature infants. The authors found that over a six-year period at one hospital, the model demonstrated accurate ROP risk assessment and resulted in a large reduction in the number of ROP examinations compared with current screening guidelines.

    They applied multivariate logistic regression retrospectively to data from infants born with birth weight less than 1501 g or gestational age of 30 weeks or less at a Philadelphia hospital between 2004 and 2009. In the model, birth weight, gestational age and daily weight gain rate were used repeatedly each week to predict risk of Early Treatment of Retinopathy of Prematurity type 1 or 2 ROP. If the risk was above a cut-point level, examinations would be indicated.

    Of 524 infants, 4 percent had type 1 ROP and received laser treatment; 5 percent had type 2 ROP. The model accurately predicted all infants with type 1 ROP, missed one infant with type 2 ROP who did not require laser treatment, and would have reduced the number of infants requiring examinations by 49 percent.

    Raising the cut point to miss one type 1 ROP case would have reduced the need for examinations by 79 percent. Using daily weight measurements to calculate weight gain rate resulted in a slightly higher examination reduction than weekly measurements.

    The authors say that a consensus will need to be reached to determine which trade-offs are most acceptable to physicians, and those decisions may require further consideration as more treatment modalities are developed.

    As a simple logistic equation, this ROP screening model can be calculated by hand or represented as a nomogram for easy clinical use. However, larger studies are needed to achieve a highly precise estimate of sensitivity prior to clinical application.