预测儿童Ⅱ期人工晶状体植入术后青光眼相关不良事件的风险:一项为期3年的研究

Predicting the risk of glaucoma-related adverse events following secondary intraocular lens implantation in paediatric eyes:a 3-year study

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(glaucomarelated 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.