威胁视力的2型糖尿病视网膜病变风险预测模型的建立与验证

Development and Validation of a Predictive Risk Model for Vision-threatening Diabetic Retinopathy in Patients with Type 2 Diabetes

【目的】基于简单易得的临床资料,开发并验证2型糖尿病(T2DM)患者并发威胁视力的视网膜病变(VTDR)的风险预测模型,为基层医院提供便捷有效的预测工具,以便早期识别和转诊高危人群。【方法】使用2017年至2020年广州糖尿病眼病研究中T2DM患者临床数据构建列线图预测模型。使用Logistic回归分析VTDR的影响因素并建立模型,受试者工作特征曲线(ROC)、Hosmer-Lemeshow检验、校准曲线、决策曲线(DCA)用于评价模型的性能。使用k折交叉验证得到的平均ROC下面积对模型进行内部验证,使用东莞眼科研究数据对模型进行外部验证。【结果】建模集共纳入患者2161例,并发VTDR者135例(6.25%)。年龄(P<0.001,OR=0.927,95%CI:0.898~0.957)、体质量指数(P<0.001,OR=0.845,95%CI:0.821~0.932)与VTDR负相关,糖尿病病程(P<0.001,OR=1.064,95%CI:1.035~1.094)、是否使用胰岛素(P=0.045,OR=1.534,95%CI:1.010~2.332)、收缩压(P<0.001,OR=1.019,95%CI:1.008~1.029)、糖化血红蛋白(P<0.001,OR=1.484,95%CI:1.341~1.643)和血清肌酐(P<0.001,OR=1.017,95%CI:1.010~1.023)与VTDR正相关,均被纳入模型。ROC提示建模集和验证集中该模型预测VTDR发生的曲线下面积分别为0.797和0.762;Hosmer-Lemeshow检验(P>0.05)及校准曲线表明预测概率与观测概率具有较高一致性;DCA表明模型在建模集和验证集中均能产生净效益。【结论】年龄、糖尿病病程、是否使用胰岛素、体质量指数、收缩压、糖化血红蛋白和血清肌酐是VTDR的独立影响因素,基于上述变量构建的列线图模型有良好的预测效力,可以为基层医院早期识别和转诊VTDR提供科学依据,值得应用推广。

【Objective】To develop and validate a predictive risk model for vision-threatening diabetic retinopathy in patients with type 2 diabetes using readily accessible clinical data,which may provide a convenient and effective predic‐tion tool for early identification and referral of at-risk populations.【Methods】A nomogram model was developed using a dataset obtained from patients with T2DM who participated in the Guangzhou Diabetic Eye Study from November 2017 to December 2020.Logistic regression was used to construct the model,and model performance was evaluated using receiver operating characteristic curve,Hosmer-Lemeshow test,calibration curve and decision curve analysis.The model under‐went internal validation through the mean AUC of k-fold cross-validation method,and further external validation was con‐ducted in the Dongguan Eye Study.【Results】A total of 2161 individuals were included in the model development dataset,of whom 135(6.25%)people were diagnosed with VTDR.Age(P<0.001,OR=0.927,95%CI:0.898~0.957)and body mass index(P<0.001,OR=0.845,95%CI:0.821~0.932)were found to be negatively correlated with VTDR,whereas dia‐betes duration(P<0.001,OR=1.064,95%CI:1.035~1.094),insulin use(P=0.045,OR=1.534,95%CI:1.010~2.332),systolic blood pressure(P<0.001,OR=1.019,95%CI:1.008~1.029),glycated hemoglobin(P<0.001,OR=1.484,95%CI:1.341~1.643),and serum creatinine(P<0.001,OR=1.017,95%CI:1.010~1.023)were positively correlated with VTDR.All these variables were included in the model as predictors.The model showed strong discrimination in the de‐velopment dataset with an area under the receiver operating characteristic curve(AUC)of 0.797 and in the external valida‐tion dataset(AUC 0.762).The Hosmer-Lemeshow test(P>0.05)and the calibration curve displayed good agreement.De‐cision curve analysis showed that the nomogram produced net benefit in the two datasets.【Conclusions】Independent fac‐tors influencing VTDR include age,duration of diabetes mellitus,insulin use,body mass index,systolic blood pressure,glycosylated hemoglobin,and serum creatinine.The nomogram constructed using these variables demonstrates a high de‐gree of predictive validity.The model can serve as a valuable tool for early detection and referral of VTDR in primary care clinics.Therefore,its application and promotion are highly recommended.