Raffa L H, Bawajeeh N, Alothman R A, Siddiqui M, Almarzouki H S
Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Department of Ophthalmology, King Abdulaziz University Hospital, Jeddah, Saudi Arabia.
Niger J Clin Pract. 2025 Jul 1;28(7):783-789. doi: 10.4103/njcp.njcp_138_25. Epub 2025 Jul 28.
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.
To assess the diagnostic performance of the CHOP-ROP model in Saudi preterm infants and compare it with other ROP screening tools.
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.
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).
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.
早产儿视网膜病变(ROP)可导致儿童失明,尤其是早产婴儿。虽然存在几种筛查模型,但它们在发展中国家的表现尚未得到充分证实。本研究评估了费城儿童医院早产儿视网膜病变(CHOP-ROP)模型在沙特阿拉伯的准确性,并将其与其他模型进行比较。
评估CHOP-ROP模型在沙特早产婴儿中的诊断性能,并将其与其他ROP筛查工具进行比较。
这项涉及524名早产婴儿的回顾性研究在吉达的两家三级医院进行。使用CHOP-ROP评估ROP风险,并与四种ROP风险模型进行比较。分析预测值、特异性、敏感性和受试者工作特征曲线。逻辑回归确定1型ROP预测因素。
22.3%的婴儿检测到任何阶段的ROP;9.1%需要治疗。CHOP-ROP具有最高的特异性(62.5%)、准确性(64.2%)和曲线下面积(AUC)(0.71),表明其区分需要治疗婴儿的能力更强,尽管其敏感性(81.4%)低于其他模型。较低的出生体重、较长的新生儿重症监护病房住院时间和早期输血是1型ROP的重要预测因素(均P<0.05)。
尽管CHOP-ROP显示出较强的特异性和准确性,但其较低的敏感性引发了对漏诊需要治疗病例的担忧。与更敏感的本地工具相比,其性能次优。需要进行区域特异性模型验证和阈值调整,以提高其预测价值,同时尽量减少假阴性。