Validity and reliability of ROPScore scoring method to predict the
severity of retinopathy of prematurity in premature infants
Abstract
Abstract Purpose: To assess the accuracy and efficacy of ROPScore
scoring system an ancillary method to predict the severity of
retinopathy of prematurity (ROP) in very low birth weight (VLBW)
premature infants. Methods: The medical records of 131 premature babies
having a birth weight 1500 gram and gestational age (GA) ≤ 30 weeks
were included in this study. The ROPScore was calculated for each baby
at six weeks of life using an Excel spreadsheet (Microsoft®). Area under
curve (AUC) analysis was used in both any stage of ROP and type-1
(severe) ROP to ascertain the cut-off points for the scoring model.
Sensitivity, specificity, positive predictive values (PPV) and negative
predictive values (NPV) of the scoring system with the calibrated
cut-off points were analyzed. Results: The sensitivity of the ROPScore
scoring system was 88.5% ( 95% CI 79-94) and 100% (95% CI 82-100)
was for predicting any stage and type-1 retinopathy of prematurity,
respectively. The PPV and NPV of the models were 62% and 74.1% for any
stage of ROP and those of were 50% and 100% for type-1 ROP,
respectively. In ROC analysis, the mean AUCs of ROPScore model was
statistically significant compared than BW and GA for predicting type -1
ROP (p < 0.001). Conclusion: This study indicated that
ROPScore scoring model with customized cutoff levels might be a useful
method for early prediction of premature retinopathy, particularly in
type-1 (severe) ROP. In addition, this model may also reduce the number
of eye examinations which are essential for detecting the retinopathy of
prematurity