Clinical Prediction Model for Diabetic Kidney Disease Based on Optical Coherence Tomography Angiography

LU Lijiao; XU Nan; LIU Xinxin; DU Fangfang; ZHENG Cong; PENG Hongjun; CAO Mingzhe; AI Shibei

doi:10.13471/j.cnki.j.sun.yat-sen.univ（med.sci）.20240319.002

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Clinical Prediction Model for Diabetic Kidney Disease Based on Optical Coherence Tomography Angiography

Preclinic Research | 更新时间：2024-04-15

- Clinical Prediction Model for Diabetic Kidney Disease Based on Optical Coherence Tomography Angiography
- Journal of Sun Yat-sen University(Medical Sciences) Vol. 45, Issue 2, Pages: 253-260(2024)
- 作者机构：
  
  中山大学附属第七医院眼科，广东深圳 518000
- 作者简介：
  
  CAO Mingzhe，E-mail：caomzh7@mail.sysu.edu.cn
  AI Shibei， E-mail： aishb@mail.sysu.edu.cn
- 基金信息：
- DOI：10.13471/j.cnki.j.sun.yat-sen.univ（med.sci）.20240319.002
  CLC： R77
- Published：20 March 2024，
  
  Received：30 November 2023，
  
  Accepted：14 March 2024
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陆丽娇,徐楠,刘鑫鑫等.基于OCTA构建糖尿病肾脏病临床预测模型[J].中山大学学报（医学科学版）,2024,45(02):253-260.

LU Lijiao,XU Nan,LIU Xinxin,et al.Clinical Prediction Model for Diabetic Kidney Disease Based on Optical Coherence Tomography Angiography[J].Journal of Sun Yat-sen University(Medical Sciences),2024,45(02):253-260.
陆丽娇,徐楠,刘鑫鑫等.基于OCTA构建糖尿病肾脏病临床预测模型[J].中山大学学报（医学科学版）,2024,45(02):253-260. DOI： 10.13471/j.cnki.j.sun.yat-sen.univ（med.sci）.20240319.002.

LU Lijiao,XU Nan,LIU Xinxin,et al.Clinical Prediction Model for Diabetic Kidney Disease Based on Optical Coherence Tomography Angiography[J].Journal of Sun Yat-sen University(Medical Sciences),2024,45(02):253-260. DOI： 10.13471/j.cnki.j.sun.yat-sen.univ（med.sci）.20240319.002.

摘要

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，Brier=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。

Abstract

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 discrimination 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 prediction nomogram model based on OCTA allowed for early warning and advanced intervention of DKD.

关键词

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

Keywords

optical coherence tomography angiography （OCTA）diabetic kidney disease （DKD）clinical prediction modelreceiver operating characteristic curve （ROC）decision curve analysis （DCA）

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