ABSTRACT
INTRODUCTION: Rubella is an important infectious, vaccine-preventable etiology of congenital defects. The aim of the study was to develop a prediction nomogram to assess the probability of an infant being at risk for congenital rubella based on demographics and ophthalmological findings. METHODS: This was a cross-sectional sentinel surveillance study conducted at 5 centers spanning pan-India and involved 1134 infants. The diagnosis of rubella was made using standard guidelines. For the construction of the prediction model, laboratory-confirmed cases were grouped as "at-risk" (AR) infants and the discarded cases into "not at risk" (NAR) infants. Univariate analysis (p value cut-off < 0.05) followed by multivariate binary logistic regression model development was performed. RESULTS: The average (median) age of the suspected CRS infants was 3 (IQR 1-6) months, and the average (mean) age of their mothers was 25.8 ± 4.1 years. Out of the total infants, 81 (7.3%) died, 975 (88%) were alive, and 55 (5.0%) were lost to follow-up. The final model showed that the odds of cataract, retinopathy, glaucoma, microcornea, and age of the infant at presentation were 3.1 (2.2-4.3), 4.9(2.3-10.4), 2.7(1.1-5.9), 2.3(1.1-4.7), and 1.1 (1-1.1), respectively, for the AR infant as compared to NAR infant. AUC of final model was 0.68 (95% CI Delong, 0.64-0.72). Bootstrapping for calibration of the model showed satisfactory results. Nomogram, along with a web version, was developed. CONCLUSION: The developed nomogram would have a wide community-based utilization and will help in prioritizing attention to high-risk children, thereby avoiding loss to follow-up.