Congenital cataract (CC) is one of the most common causes of pediatric visual impairment. As our understanding of CC's etiology, clinical manifestations, and pathogenic genes deepens,various CC categorization systems based on diferent classifcation criteria have been proposed. Regrettably, the application of the CC category in clinical practice and scientifc research is limited. It is challenging to obtain preciseinformation that could guide the timely treatment decision-making for pediatric cataract patients or predict their prognosis from a specific CC classification. This review aims to discuss the statusquo of CC categorization systems and the potential directions for future research in this field, focusingon categorization principles and scientific application in clinical practice. Additionally, it aims to propose the potential directions for future research in this domain.
Congenital cataract (CC) is one of the most common causes of pediatric visual impairment. As our understanding of CC's etiology, clinical manifestations, and pathogenic genes deepens,various CC categorization systems based on diferent classifcation criteria have been proposed. Regrettably, the application of the CC category in clinical practice and scientifc research is limited. It is challenging to obtain preciseinformation that could guide the timely treatment decision-making for pediatric cataract patients or predict their prognosis from a specific CC classification. This review aims to discuss the statusquo of CC categorization systems and the potential directions for future research in this field, focusingon categorization principles and scientific application in clinical practice. Additionally, it aims to propose the potential directions for future research in this domain.
Ⅱ期人工晶状体(intraocular lens,IOL)植入常用于矫正先天性白内障摘除术后无晶状体眼状态。IOL屈光力计算是影响儿童Ⅱ期IOL植入术后视功能发育和改善的关键因素之一。现有IOL屈光力计算公式是基于成人有晶状体眼的数据研发，能准确预测成人眼IOL植入的屈光力，但是对儿童Ⅱ期IOL植入的屈光力预测准确性欠佳，主要原因包括：1)儿童II期植入术前为无晶状体眼，缺乏部分公式定义中的有晶状体眼的前房深度(是指从角膜前表面中央顶点到晶状体前表面的距离)和晶状体厚度。2)公式根据囊袋内植入IOL预测屈光力，但儿童Ⅱ期IOL睫状沟植入术在临床上应用更为广泛。当IOL植入睫状沟时有效晶状体位置发生前移，可能引起屈光预测误差。3)成人眼的发育已完成，目标屈光度多为正视或近视眼(-3.00 ~ +1.00 D)，但是儿童眼仍在发育，需针对其特性测算合适的远视目标屈光度(+0.50 ~ +12.00 D)以适应眼球发育引起的屈光变化。为使Ⅱ期IOL植入患儿达到术前预设的目标屈光度，对现有公式进行选择与优化至关重要。
Secondary intraocular lens (IOL) implantation is a common treatment for pediatric aphakia. The accurate prediction of IOL power calculation plays a pivotal role in the postoperative development and improvement of visual function for pediatric secondary IOL implantation. Current IOL power calculation formulas were developed based on data from adult phakic eyes and displayed good performance in adult population. However, the formulas showed poor performance in pediatric aphakic population due to the following reasons: 1) In these pediatric aphakic patients, the unavailability of phakic anterior chamber depth (the distance from corneal epithelium to the anterior surface of the lens) and lens thickness (LT) greatly limits the application of some IOL power calculation formulas. 2) IOL power calculation formulas predict the effective lens position on the basis of in-the-bag IOL implantation, whereas sulcus implantation is more widely used in pediatric secondary implantation. Effective lens position in capsular placement is more posterior to ciliary sulcus IOL placement. When applying the initial IOL power calculated for capsular implantation to sulcus implantation, it can lead to refractive errors. 3) Adult eyes have completed their development, with target refractions often being emmetropic or myopic (-3.00 ~ +1.00 D), while pediatric eyes are still developing, necessitating the calculation of an appropriate hyperopic (+0.50 ~ +12.00 D) target refraction to accommodate refractive changes due to ocular growth.To achieve the predetermined target refractive outcomes, the selection and optimization of IOL power calculation formulas is critically important for pediatric secondary IOL implantation.
目的：建立并评估儿童Ⅱ期人工晶状体(intraocular lens,IOL)植入术后青光眼相关不良事件(glaucoma-related adverse events,GRAEs)的预测模型。方法：选取于中山大学中山眼科中心行Ⅱ期IOL植入术的无晶状体眼患儿205例(356眼)，并在术后对其随访3年。采用Cox比例风险模型确定GRAEs的预测因子，并建立列线图预测模型。采用随时间变化的受试者工作特征(receiver operating characteristic,ROC)曲线、决策曲线分析、Kaplan-Meier曲线评估模型性能，并通过Bootstrapping的C指数和校准图进行内部验证。结果：行Ⅱ期IOL植入术时年龄较大(HR=1.50, 95% CI: 1.03 ~2.19)、术后一过性高眼压(HR=9.06, 95% CI: 2.97~27.67)和IOL睫状沟植入术(HR=14.55, 95% CI: 2.11~100.57)是GRAEs的危险因素(均P<0.05)，并据此建立了两个列线图预测模型。在术后1、2、3年，模型1的ROC曲线下面积(area under curve,AUC)分别为0.747(95% CI: 0.776 ~0.935)、0.765 (95% CI: 0.804 ~0.936)和0.748 (95% CI: 0.736~0.918)，模型2的AUC分别为0.881 (95% CI: 0.836 ~0.926)、0.895 (95% CI: 0.852 ~0.938)和0.848 (95% CI: 0.752~0.945)。在内部验证和评价中，两种模型均表现出良好的性能和临床净效益。Kaplan-Meier曲线显示两个不同的风险组在两个模型中都能被显著且稳健地区分。此外，本研究也构建了在线风险计算器。结论：两种列线图均能灵敏、准确地识别Ⅱ期IOL植入术后GRAEs的高危患儿，有助对其进行早期识别和及时干预。
Aims: To establish and evaluate predictive models for glaucoma-related adverse events (GRAEs) following secondary intraocular lens (IOL) implantation in paediatric eyes. Methods: 205 children (356 aphakic eyes) receiving secondary IOL implantation at Zhongshan Ophthalmic Center with a 3-year follow-up were enrolled. Cox proportional hazard model was used to identify predictors of GRAEs and developed nomograms. Model performance was evaluated with time-dependent receiver operating characteristic (ROC) curves, decision curve analysis, Kaplan-Meier curves and validated internally through C-statistics and calibration plot of the bootstrap samples. Results: Older age at secondary IOL implantation (HR=1.5, 95% CI: 1.03 to 2.19), transient intraocular hypertension (HR=9.06, 95% CI: 2.97 to 27.67) and ciliary sulcus implantation (HR=14.55, 95% CI: 2.11 to 100.57) were identified as risk factors for GRAEs (all p<0.05). Two nomograms were established. At postoperatively 1, 2 and 3 years, model 1 achieved area under the ROC curves (AUCs) of 0.747 (95% CI: 0.776 to 0.935), 0.765 (95% CI: 0.804 to 0.936) and 0.748 (95% CI: 0.736 to 0.918), and the AUCs of model 2 were 0.881 (95% CI: 0.836 to 0.926), 0.895 (95% CI: 0.852 to 0.938) and 0.848 (95% CI: 0.752 to 0.945). Both models demonstrated fine clinical net benefit and performance in the interval validation. The Kaplan-Meier curves showing two distinct risk groups were well discriminated and robust in both models. An online risk calculator was constructed. Conclusions: Two nomograms could sensitively and accurately identify children at high risk of GRAEs after secondary IOL implantation to help early identification and timely intervention.
