Risk factor analysis and clinical decision tree model construction for diabetic retinopathy in Western China

Yuan-Yuan Zhou; Tai-Cheng Zhou; Nan Chen; Guo-Zhong Zhou; Hong-Jian Zhou; Xing-Dong Li; Jin-Rui Wang; Chao-Fang Bai; Rong Long; Yu-Xin Xiong; Ying Yang

doi:10.4239/wjd.v13.i11.986

Risk factor analysis and clinical decision tree model construction for diabetic retinopathy in Western China

World J Diabetes. 2022 Nov 15;13(11):986-1000. doi: 10.4239/wjd.v13.i11.986.

Authors

Affiliations

¹ Department of Endocrinology and Metabolism, The Sixth Affiliated Hospital of Kunming Medical University, The People's Hospital of Yuxi City, Yuxi 653100, Yunnan Province, China.
² Department of Endocrinology and Metabolism, Affiliated Hospital of Yunnan University, The Second People's Hospital of Yunnan Province, Kunming 650021, Yunnan Province, China.
³ Department of Endocrinology and Metabolism, The Frist People's Hospital of Anning City, Anning City 650300, Yunnan Province, China.
⁴ Department of Endocrinology and Metabolism, Affiliated Hospital of Yunnan University, The Second People's Hospital of Yunnan Province, Kunming 650021, Yunnan Province, China. yangying2072@126.com.

Abstract

Background: Diabetic retinopathy (DR) is the driving force of blindness in patients with type 2 diabetes mellitus (T2DM). DR has a high prevalence and lacks effective therapeutic strategies, underscoring the need for early prevention and treatment. Yunnan province, located in the southwest plateau of China, has a high pre-valence of DR and an underdeveloped economy.

Aim: To build a clinical prediction model that will enable early prevention and treatment of DR.

Methods: In this cross-sectional study, 1654 Han population with T2DM were divided into groups without (n = 826) and with DR (n = 828) based on fundus photography. The DR group was further subdivided into non-proliferative DR (n = 403) and proliferative DR (n = 425) groups. A univariate analysis and logistic regression analysis were conducted and a clinical decision tree model was constructed.

Results: Diabetes duration ≥ 10 years, female sex, standing- or supine systolic blood pressure (SBP) ≥ 140 mmHg, and cholesterol ≥ 6.22 mmol/L were risk factors for DR in logistic regression analysis (odds ratio = 2.118, 1.520, 1.417, 1.881, and 1.591, respectively). A greater severity of chronic kidney disease (CKD) or hemoglobin A 1c increased the risk of DR in patients with T2DM. In the decision tree model, diabetes duration was the primary risk factor affecting the occurrence of DR in patients with T2DM, followed by CKD stage, supine SBP, standing SBP, and body mass index (BMI). DR classification outcomes were obtained by evaluating standing SBP or BMI according to the CKD stage for diabetes duration < 10 years and by evaluating CKD stage according to the supine SBP for diabetes duration ≥ 10 years.

Conclusion: Based on the simple and intuitive decision tree model constructed in this study, DR classification outcomes were easily obtained by evaluating diabetes duration, CKD stage, supine or standing SBP, and BMI.

Keywords: Decision tree; Diabetic retinopathy; Type 2 diabetes; Western China.