基于OCTA构建糖尿病肾脏病临床预测模型OA北大核心CSTPCD
Clinical Prediction Model for Diabetic Kidney Disease Based on Optical Coherence Tomography Angiography
[目的]探讨基于光学相干断层扫描血管成像技术(OCTA),筛查糖尿病肾脏病(DKD)高风险人群的临床预测模型.[方法]本研究以567例糖尿病患者为研究对象,在逐步logistic回归分析的基础上,运用随机森林算法筛选纳入建模的指标,构建基于OCTA糖尿病肾脏病临床预测模型.通过受试者工作特征曲线评价模型区分度,通过决策曲线分析评估模型临床有效性.[结果]构建基于OCTA的DKD临床预测模型,ROC曲线下面积为0.878,Bri-er=0.11.[结论]本研究构建了基于OCTA结果进行糖尿病肾脏病临床预测的列线图预测模型,并从多维度验证模型,从而达到早期预警、提前实施干预的目的.
[Objective]To construct and validate a clinical prediction model for diabetic kidney disease(DKD)based on optical coherence tomography angiography(OCTA).[Methods]This study enrolled 567 diabetes patients.The random forest algorithm as well as logistic regression analysis were applied to construct the prediction model.The model discrimina-tion and clinical usefulness were evaluated by receiver operating characteristic curve(ROC)and decision curve analysis(DCA),respectively.[Results]The clinical prediction model for DKD based on OCTA was constructed with area under the curve(AUC)of 0.878 and Brier score of 0.11.[Conclusions]Through multidimensional verification,the clinical pre-diction nomogram model based on OCTA allowed for early warning and advanced intervention of DKD.
陆丽娇;徐楠;刘鑫鑫;杜芳芳;郑枞;彭鸿钧;曹明哲;艾诗蓓
中山大学附属第七医院眼科,广东 深圳 518000
临床医学
光学相干断层扫描血管成像技术糖尿病肾脏病临床预测模型受试者工作特征曲线决策曲线分析
optical coherence tomography angiography(OCTA)diabetic kidney disease(DKD)clinical predic-tion modelreceiver operating characteristic curve(ROC)decision curve analysis(DCA)
《中山大学学报（医学科学版）》 2024 (002)
253-260 / 8
评论