State University of New York College of Optometry, New York, NY, USA.
Retina Foundation of the Southwest, Dallas, TX, USA.
Transl Vis Sci Technol. 2024 May 1;13(5):25. doi: 10.1167/tvst.13.5.25.
The purpose of this study was to investigate the development of optical biometric components in children with hyperopia, and apply a machine-learning model to predict axial length.
Children with hyperopia (+1 diopters [D] to +10 D) in 3 age groups: 3 to 5 years (n = 74), 6 to 8 years (n = 102), and 9 to 11 years (n = 36) were included. Axial length, anterior chamber depth, lens thickness, central corneal thickness, and corneal power were measured; all participants had cycloplegic refraction within 6 months. Spherical equivalent (SEQ) was calculated. A mixed-effects model was used to compare sex and age groups and adjust for interocular correlation. A classification and regression tree (CART) analysis was used to predict axial length and compared with the linear regression.
Mean SEQ for all 3 age groups were similar but the 9 to 11 year old group had 0.49 D less hyperopia than the 3 to 5 year old group (P < 0.001). With the exception of corneal thickness, all other ocular components had a significant sex difference (P < 0.05). The 3 to 5 year group had significantly shorter axial length and anterior chamber depth and higher corneal power than older groups (P < 0.001). Using SEQ, age, and sex, axial length can be predicted with a CART model, resulting in lower mean absolute error of 0.60 than the linear regression model (0.76).
Despite similar values of refractive errors, ocular biometric parameters changed with age in hyperopic children, whereby axial length growth is offset by reductions in corneal power.
We provide references for optical components in children with hyperopia, and a machine-learning model for convenient axial length estimation based on SEQ, age, and sex.
本研究旨在探讨远视儿童眼生物测量参数的发展，并应用机器学习模型预测眼轴长度。
纳入远视（+1 屈光度[D]至+10 D）的 3 个年龄组儿童：3 至 5 岁（n=74）、6 至 8 岁（n=102）和 9 至 11 岁（n=36）。测量眼轴长度、前房深度、晶状体厚度、中央角膜厚度和角膜曲率；所有参与者在 6 个月内进行睫状肌麻痹验光。计算等效球镜（SEQ）。采用混合效应模型比较性别和年龄组，并调整眼间相关性。采用分类回归树（CART）分析预测眼轴长度，并与线性回归进行比较。
3 个年龄组的平均 SEQ 相似，但 9 至 11 岁组的远视程度比 3 至 5 岁组低 0.49 D（P<0.001）。除了角膜厚度，所有其他眼部参数均存在显著的性别差异（P<0.05）。3 至 5 岁组的眼轴长度、前房深度较短，角膜曲率较高，与年龄较大的组相比差异有统计学意义（P<0.001）。使用 SEQ、年龄和性别，可以通过 CART 模型预测眼轴长度，其平均绝对误差为 0.60，低于线性回归模型（0.76）。
尽管远视儿童的屈光不正值相似，但眼生物测量参数随年龄变化，眼轴长度的增长被角膜曲率的降低所抵消。
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