Development and validation of a model for predicting myopia in young children in China.

BACKGROUND

Early detection of myopia risk and timely intervention are key to reducing the incidence of myopia. This study aimed to construct a myopia prediction model that included perinatal factors and evaluate the correlation between each factor and myopia.

METHODS

A cross-sectional study was conducted. A questionnaire was used to investigate the related factors. The predictors of myopia onset were determined via univariate analysis (Model A), LASSO regression and 10-fold cross validation (Model B). The perinatal factors in Model B were removed to form Model C. Binary logistic regression was used to establish the model. Then, internal and external verification were performed. The differentiation, calibration, and clinical benefits of the three models were compared.

RESULTS

A total of 1322 participants with an average age of 7.85 ± 1.58 years were included in the study. Model B included age, axial length (AL), AL to corneal curvature (AL/CR) ratio, steep K (K2) value, parental myopia, and maternal history of gestational hypertension. Neither Model A nor Model C included perinatal factors. Model B had the best discrimination ability in the development, internal validation, and external validation groups and showed the best consistency and clinical benefit in all three groups. After model standardization, the effects of the respective variables on the results were as follows: AL/CR ratio: 59.14, maternal history of gestational hypertension: 44.03, AL: 30.47, K2: 5.65, parental myopia: 4.55, and age: 0.35.

CONCLUSIONS

A maternal history of gestational hypertension was associated with myopia. The effect of perinatal factors on myopia deserves attention. TRIAL REGISTRATION: ChiCTR2200065398. November 3, 2022. ( http://www.chictr.org.cn ).