Development of Predictive Scale for Diabetic Kidney Disease Progression Based on Decision Tree Classification Model

Xiao CHEN

doi:10.12259/j.issn.2095-610X.S20240816

Volume 45 Issue 8

Aug. 2024

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Xiao CHEN. Development of Predictive Scale for Diabetic Kidney Disease Progression Based on Decision Tree Classification Model[J]. Journal of Kunming Medical University, 2024, 45(8): 109-116. doi: 10.12259/j.issn.2095-610X.S20240816

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Xiao CHEN. Development of Predictive Scale for Diabetic Kidney Disease Progression Based on Decision Tree Classification Model[J]. Journal of Kunming Medical University, 2024, 45(8): 109-116. doi: 10.12259/j.issn.2095-610X.S20240816

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Development of Predictive Scale for Diabetic Kidney Disease Progression Based on Decision Tree Classification Model

doi: 10.12259/j.issn.2095-610X.S20240816

Xiao CHEN

Dept. of Endocrinology，The 2nd People’s Hospital of Liupanshui City，Liupanshui Guizhou 553403，China

Received Date: 2023-12-18
Available Online: 2024-06-26
Publish Date: 2024-08-25

Abstract

Abstract

Objective To establish a diabetic kidney disease （DKD） progression prediction scale based on the decision tree classification model. Methods A retrospective analysis was conducted on 308 patients with diabetic kidney disease admitted to Department of Endocrinology, the Second People's Hospital of Liupanshui from July 2020 to July 2021. The patients were divided into two groups: microalbuminuria group （n = 224） and macroalbuminuria group （n = 84）. Univariate and multivariate Logistic regression analysis were performed on demographic data, past medical history and other indicators of the two groups of patients, and a DKD progression prediction scale was established using the decision tree classification model. Results Among the 308 subjects, 84 （27.27%） had macroalbuminuria and 224 （72.73%） had microalbuminuria. Multivariate Logistic regression analysis showed that systolic blood pressure （OR = 1.022, P = 0.003） and serum creatinine （OR = 1.012, P < 0.001） and total protein levels （OR = 0.953, P = 0.003） were risk factors for macroalbuminuria. The decision tree classification model was used to establish a prediction scale with a total score of 60 points and a diagnostic threshold of 33 points. The area under the ROC curve of the decision tree model （0.781） was greater than that of the multivariate logistic regression model （0.769）. The sensitivity was 95.2% and the specificity was 78.9%. Conclusion DKD progression prediction scale can accurately assess the progression of DKD and has good clinical value for the early prediction of DKD progression.
- Diabetic kidney disease,
- Decision tree classification model,
- Progress,
- Predictive scale

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References(26)

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