A Proposed Method for Estimating Refractive Error in Primary School Children

Background This study aimed to evaluate consecutive measurements of biometric parameters, age, and refraction in a cohort of Turkish primary school-age children and to assess the correlation between biometric changes and refraction. Methodology The study population was seven and 12-year-old children (n = 197). The retrieved data consisted of three consecutive measurements with a one-year interval for each subject. Data from one eye (right) were used. Age, gender, body mass index, spherical equivalent (SE), axial length (AL), anterior chamber depth (ACD), central corneal thickness (CCT), keratometry (K), and lens thickness (LT) were analyzed. The onset and final data were retrieved from the database in 2013 and 2016, respectively. Statistically, logistic and Cox regression models of all parameters were analyzed, and the significance level was set at 5%. Results The median of the onset and final SE values were -0.00 D (0.00-0.00) and 0.50 D (0.19-1.00), respectively. The onset AL (hazard ratio (HR) = 5.82, 95% confidence interval (CI) = 3.45-9.76, β = 1.76, p < 0.001), K(mean )(HR = 2.28, 95% CI = 1.67-3.11, β = 0.82, p < 0.001), and age (HR = 0.77, 95% CI = 0.59-0.99, β = -0.26, p = 0.046) were correlated with myopia progression. To calculate the estimated SE, the onset data were included in the logistic regression model. The onset SE (β = 0.916, p < 0.001), AL (β = -0.451, p < 0.001), ACD (β = 0.430, p = 0.005), and K (β = -0.172, p < 0.001) were correlated with the mean final SE. An equation was generated using the regression model analysis. Conclusions The onset parameters of SE, AL, ACD, and K were confirmed to correlate with the final SE values in the proposed model. To confirm the use of the refractive calculator, a cross-validation analysis is needed to estimate three-year subsequent refractive error among seven and 12-year-old children.