Chang Hongmei, Fang Qiang, Liu Xianli
Department of Ophthalmology, Zibo Municipal Hospital, No. 139, Huangong Road, Linzi District, Zibo City, Shandong Province, 255400, China.
Department of Ophthalmology, 148 Hospital of Zibo City, RongTong Medical Healthcare Group Co. Ltd, Zibo, 255300, China.
BMC Ophthalmol. 2025 Apr 9;25(1):188. doi: 10.1186/s12886-025-03983-3.
To explore the influencing factors of posterior capsular opacification (Posterior Capsular Opacification, PCO) after intraocular lens implantation treated with Nd: YAG(Neodymium: Yttrium-Aluminum-Garnet) laser and to establish a predictive model to evaluate its risk.
From January 2018 to June 2023, the data of 312 patients with posterior capsule opacification and Nd: YAG laser treatment in our hospital were retrospectively analyzed. All patients were randomly divided into training group (218 cases) and verification group (94 cases) at the ratio of 7:3. In the training set, the independent risk factors of posterior capsule opacification before operation were identified by multivariate Logistic regression analysis, and the nomogram prediction model was constructed. By drawing ROC (receiver operating characteristic) curve and calibration curve, the prediction effectiveness of the model is evaluated, and the verification is carried out in the verification set, and its clinical application value is explored by Decision Curve Analysis (DCA).
Among 312 patients, 84 (22.92%) developed PCO. The logistic results showed that age ≥ 60 years, extracapsular excision surgery, multifocal intraocular lens, axial length ≥ 24 mm, preoperative visual acuity < 0.3, high laser energy, and large posterior capsule incision aperture were associated with the occurrence of PCO (P < 0.05). The C-index indexes of the nomograph model were 0.870 and 0.842 in the training set and verification set, respectively, and the average was absolute. In the Hosmer-Lemeshow test, the χ values of the training set and the verification set are 4.007(P = 0.856) and 2.841(P = 0.943), respectively. The ROC curve shows that the AUC(Area Under Curve) values of the training set and the verification set are 0.870 (95% CI: 0.810-0.929) and 0.843 (95% CI: 0.732-0.954) respectively, and the combination of sensitivity and specificity is 0.792, 0.810, 0.765 and 0.792 respectively.
The nomogram prediction model based on Nd: YAG laser treatment of PCO risk factors after intraocular lens implantation has high accuracy and calibration, which can provide a key reference for formulating preventive measures, help to reduce the incidence of PCO and improve the prognosis of patients.
探讨钕：钇铝石榴石（Nd：YAG）激光治疗人工晶状体植入术后后囊膜混浊（Posterior Capsular Opacification，PCO）的影响因素，并建立预测模型以评估其风险。
回顾性分析2018年1月至2023年6月我院312例接受后囊膜混浊Nd：YAG激光治疗患者的数据。所有患者按7：3随机分为训练组（218例）和验证组（94例）。在训练集中，通过多因素Logistic回归分析确定术前后囊膜混浊的独立危险因素，并构建列线图预测模型。通过绘制ROC（受试者工作特征）曲线和校准曲线评估模型的预测效能，并在验证集中进行验证，通过决策曲线分析（DCA）探索其临床应用价值。
312例患者中，84例（22.92%）发生PCO。Logistic结果显示，年龄≥60岁、囊外摘除术、多焦点人工晶状体、眼轴长度≥24mm、术前视力<0.3、激光能量高和后囊切口孔径大与PCO的发生相关（P<0.05）。列线图模型在训练集和验证集的C指数分别为0.870和0.842，平均绝对误差。在Hosmer-Lemeshow检验中，训练集和验证集的χ值分别为4.007（P=0.856）和2.841（P=0.943）。ROC曲线显示，训练集和验证集的AUC（曲线下面积）值分别为0.870（95%CI：0.810-0.929）和0.843（95%CI：0.732-0.954），敏感性和特异性的组合分别为0.792、0.810、0.765和0.792。
基于Nd：YAG激光治疗人工晶状体植入术后PCO危险因素的列线图预测模型具有较高的准确性和校准度，可为制定预防措施提供关键参考，有助于降低PCO的发生率，改善患者预后。
