Topic: The G-ROP criteria, incorporating postnatal weight gain, are widely validated for retinopathy of prematurity (ROP) screening. We assessed the G-ROP algorithm's diagnostic accuracy across various outcomes and explored heterogeneity sources.
Clinical relevance: If G-ROP maintains sensitivity with fewer exams, it would optimize screening for this blinding disease.
Method: We searched PubMed, EMBASE, and Cochrane databases (through September 2024) for studies using G-ROP to predict type 1, type 2, treated, or any-stage ROP. We assessed risk of bias using QUADAS-2 and certainty of evidence using GRADE approach. The protocol was prospectively registered with PROSPERO (CRD42024571794).
Results: Twenty-three studies were included. For type 1 ROP (17 cohorts; 1,406 infants), sensitivity was 0.99 (95% CI: 0.99-1.00; I2=44.5%) and specificity (9 cohorts; 2,522 infants) was 0.34 (95% CI: 0.32-0.36; I2=96.3%).The diagnostic odds ratio (DOR) was 6.22 (95% CI: 2.34-16.53; I2=40.7%) ; AUC was 0.87 (95% CI: 0.83-0.90). Certainty of evidence was high for sensitivity and low for specificity and DOR. For type 2 ROP, pooled sensitivity from 9 cohorts (871 infants) was 0.98 (95% CI: 0.97-0.99; I2=41.4%), while specificity from 3 cohorts (621 infants) was 0.25 (95% CI: 0.22-0.29; I2=92.2%). The DOR was 3.21 (95% CI: 1.24-8.28; I2=0%); AUC was 0.76 (95% CI: 0.72-0.80). Certainty was high for sensitivity, very low for specificity, and moderate for DOR. For any-stage ROP, pooled sensitivity from 16 cohorts (3,674 infants) was 0.87 (95% CI: 0.86-0.88; I2=90.2%), while specificity from 13 cohorts (2,846 infants) was 0.45 (95% CI: 0.43-0.47; I2=95.8%). The DOR was 5.88 (95% CI: 3.89-8.89; I2=75.3%), and the AUC was 0.78 (95% CI: 0.74-0.81). Certainty was low for sensitivity, low for specificity, and moderate for DOR.
Conclusions: The G-ROP algorithm demonstrates consistently high sensitivity, particularly for type 1 and treated ROP, supporting its use as a screening tool for severe disease. While the model reduces examinations compared with current standards, its low specificity may limit its usefulness in low-resource settings, where minimizing unnecessary screening is essential.
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