Predictive Modeling of Cycloplegic Refraction Using Non-Cycloplegia Ocular Parameters With Emphasis on Lens-Related Features.

IF 2.6 3区医学 Q2 OPHTHALMOLOGY

Translational Vision Science & Technology Pub Date : 2025-10-01 DOI:10.1167/tvst.14.10.3

Qiang Su, Bei Du, Bingqin Li, Chen Yang, Yicheng Ge, Haochen Han, Chea-Su Kee, Wenxue Li, Ruihua Wei

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引用次数: 0

Abstract

Purpose: The study aimed to develop a predictive model for refraction after cycloplegia by leveraging non-cycloplegia ocular parameters and focusing on lens-related features.

Methods: A total of 153 children 4 to 15 years old were enrolled in this study. This study randomized gender distribution. Sex, age, intraocular pressure (IOP), refraction before and after cycloplegia, and optical biometry (OB) parameters were collected. Four prediction models for spherical refraction were developed: a control group without lens-related features and three experimental groups incorporating lens-related features. Features such as lens diopter, anterior surface curvature radius, and lens thickness played significant roles. The models were evaluated using statistical measures: mean square error (MSE), Root mean square error (RSME), Mean absolute error (MAE) and r-square (r2). Least absolute shrinkage and selection operator (LASSO) regression and the L1 regularization term were used for feature screening and machine learning for extreme gradient enhancement. The extreme gradient boosting (XGBoost) method was used to develop the model.

Results: The predictive model incorporating lens-related features demonstrated superior performance in estimating refraction after cycloplegia compared to the model without such features. Among the models with lens-related features, the IOL of contact lens algorithm (IOLcl) group exhibited the highest efficacy, boasting an r2 of 0.964, MSE of 0.241, RMSE of 0.472, and MAE of 0.307.

Conclusions: The study provided valuable insights into developing a robust predictive model for refraction after cycloplegia, emphasizing the importance of lens-related features and the morphological changes in the crystalline lens during accommodation.

Translational relevance: This predictive model has potential advantages in avoiding complications associated with cycloplegia and can be widely applied for clinic vision screening in optometry.

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利用非睫状体睫状体参数对睫状体屈光进行预测建模。

目的：本研究旨在利用非睫状体睫状体的眼部参数和晶状体相关特征，建立一个预测睫状体截瘫后屈光的模型。方法：153名4 ~ 15岁的儿童被纳入本研究。本研究随机化性别分布。收集性别、年龄、眼内压（IOP）、睫状体麻痹前后屈光、光学生物测量（OB）参数。建立了四种预测模型：无晶状体相关特征的对照组和有晶状体相关特征的三个实验组。晶状体屈光度、晶状体前表面曲率半径和晶状体厚度等特征起着重要作用。采用均方误差（MSE）、均方根误差（RSME）、平均绝对误差（MAE）和r-平方（r2）等统计指标对模型进行评价。最小绝对收缩和选择算子（LASSO）回归和L1正则化项用于特征筛选和机器学习用于极端梯度增强。采用极限梯度增强（XGBoost）方法建立模型。结果：与没有晶状体相关特征的模型相比，结合晶状体相关特征的预测模型在估计睫状体麻痹后屈光方面表现出优越的性能。在具有晶状体相关特征的模型中，隐形眼镜IOL算法（IOLcl）组的疗效最高，r2为0.964，MSE为0.241，RMSE为0.472，MAE为0.307。结论：该研究为建立一个强大的预测模型提供了有价值的见解，强调了晶状体相关特征和晶状体在调节过程中的形态变化的重要性。翻译相关性：该预测模型在避免睫状体麻痹并发症方面具有潜在优势，可广泛应用于验光中的临床视力筛查。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Translational Vision Science & Technology Engineering-Biomedical Engineering

CiteScore

5.70

自引率

3.30%

发文量

346

审稿时长

25 weeks

期刊介绍： Translational Vision Science & Technology (TVST), an official journal of the Association for Research in Vision and Ophthalmology (ARVO), an international organization whose purpose is to advance research worldwide into understanding the visual system and preventing, treating and curing its disorders, is an online, open access, peer-reviewed journal emphasizing multidisciplinary research that bridges the gap between basic research and clinical care. A highly qualified and diverse group of Associate Editors and Editorial Board Members is led by Editor-in-Chief Marco Zarbin, MD, PhD, FARVO. The journal covers a broad spectrum of work, including but not limited to: Applications of stem cell technology for regenerative medicine, Development of new animal models of human diseases, Tissue bioengineering, Chemical engineering to improve virus-based gene delivery, Nanotechnology for drug delivery, Design and synthesis of artificial extracellular matrices, Development of a true microsurgical operating environment, Refining data analysis algorithms to improve in vivo imaging technology, Results of Phase 1 clinical trials, Reverse translational ("bedside to bench") research. TVST seeks manuscripts from scientists and clinicians with diverse backgrounds ranging from basic chemistry to ophthalmic surgery that will advance or change the way we understand and/or treat vision-threatening diseases. TVST encourages the use of color, multimedia, hyperlinks, program code and other digital enhancements.