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Assessment of the Children's Hospital of Philadelphia Score Algorithm for Screening Retinopathy of Prematurity in
L H Raffa1,2, N Bawajeeh1, R A Alothman1
1Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Insights
The Children's Hospital of Philadelphia-Retinopathy of Prematurity (CHOP-ROP) model shows good accuracy for screening retinopathy of prematurity (ROP) in Saudi infants, but its lower sensitivity may miss cases. Further validation is needed for this ROP screening tool.
Area of Science:
- Ophthalmology
- Neonatology
- Pediatric Medicine
Background:
- Retinopathy of prematurity (ROP) is a leading cause of childhood blindness, particularly in preterm infants.
- Existing ROP screening models lack established performance data in developing countries.
- This study evaluated the CHOP-ROP model's accuracy in Saudi Arabia.
Purpose of the Study:
- To assess the diagnostic performance of the CHOP-ROP model in Saudi preterm infants.
- To compare the CHOP-ROP model with other ROP screening tools in the region.
Main Methods:
- Retrospective analysis of 524 preterm infants from two tertiary hospitals in Jeddah.
- Evaluation of CHOP-ROP model against four other ROP risk models.
- Analysis of predictive values, sensitivity, specificity, and ROC curves; logistic regression for Type 1 ROP predictors.
Main Results:
- Any-stage ROP detected in 22.3% of infants; 9.1% required treatment.
- CHOP-ROP demonstrated the highest specificity (62.5%) and accuracy (64.2%) with an AUC of 0.71.
- CHOP-ROP sensitivity (81.4%) was lower than other models; lower birth weight, longer NICU stay, and early blood transfusion predicted Type 1 ROP.
Conclusions:
- CHOP-ROP shows strong specificity and accuracy but lower sensitivity, raising concerns about missed ROP cases requiring treatment.
- The model's performance was suboptimal compared to more sensitive local tools.
- Region-specific validation and threshold adjustments are recommended to improve ROP screening accuracy and minimize false negatives.
Background:
Retinopathy of prematurity (ROP) causes blindness among children, particularly preterm infants. While several screening models exist, their performance in developing countries is not well established. This study assessed the accuracy of Children's Hospital of Philadelphia-Retinopathy of Prematurity (CHOP-ROP) in Saudi Arabia and compared it with other models.
Objective:
To assess the diagnostic performance of the CHOP-ROP model in Saudi preterm infants and compare it with other ROP screening tools.
Methods:
This retrospective study involving 524 preterm infants was conducted in two tertiary hospitals in Jeddah. ROP risk was assessed using the CHOP-ROP and compared with four ROP risk models. Predictive values, specificity, sensitivity, and receiver operating characteristic curves were analyzed. Logistic regression identified type 1 ROP predictors.
Results:
Any-stage ROP was detected in 22.3% of infants; 9.1% required treatment. CHOP-ROP had the highest specificity (62.5%), accuracy (64.2%), and area under the curve (AUC) (0.71), indicating better ability to distinguish infants needing treatment, though its sensitivity was lower (81.4%) than other models. Lower birth weight, longer neonatal intensive care unit stay, and early blood transfusion were significant type 1 ROP predictors (all, P < 0.05).
Conclusion:
Although CHOP-ROP demonstrated strong specificity and accuracy, its lower sensitivity raises concerns about missed cases requiring treatment. Compared to more sensitive local tools, its performance was suboptimal. Region-specific model validation and threshold adjustments are needed to enhance its predictive value while minimizing false negatives.
