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ORIGINAL RESEARCH article

Front. Endocrinol.
Sec. Clinical Diabetes
Volume 15 - 2024 | doi: 10.3389/fendo.2024.1431873

Influencing factors of acute kidney injury in elderly patients with diabetic nephropathy and establishment of nomogram model

Provisionally accepted
Ganlin Wu Ganlin Wu 1,2Lang Liu Lang Liu 3Yanli Ye Yanli Ye 3*Meirong Xu Meirong Xu 3Yanxia Zhang Yanxia Zhang 4Zuopeng Lu Zuopeng Lu 5Min Min Min Min 3
  • 1 School of Clinical Medicine, Xianning Medical College, Hubei University of Science and Technology, Xianning, China
  • 2 National Demonstration Center for Experimental (General practice) Education, Xianning Medical College, Hubei University of Science and Technology, Xianning, China
  • 3 The Second Affiliated Hospital of Hubei University of Science and Technology, Xianning, Hubei Province, China
  • 4 Department of Nephrology,Tongren Hospital of Wuhan University(Wuhan Third Hospital), Wuhan University, Wuhan, China
  • 5 People's Hospital of Tongcheng County, Xianning, China

The final, formatted version of the article will be published soon.

    Purpose: To explore the influencing factors of acute kidney injury in elderly patients with diabetic nephropathy and to construct a nomogram model. Methods: The research subjects were 680 patients with type 2 diabetic nephropathy admitted to our hospital. The patients were included from May 2018 to August 2023. Patients with acute kidney injury were used as the merge group (n=50) , and patients without unmerge group (n=630) was included. The prevalence and predisposing factors of acute kidney injury in diabetic nephropathy were analyzed, multivariate logistic regression were used to analyze the influencing factors of acute kidney injury in patients , and a nomogram risk prediction model was established based on risk factors for verification. Results: Analysis of the factors of acute kidney injury in diabetic nephropathy found that severe infection was the main trigger, accounting for 40.00%, followed by nephrotoxic antibiotics and severe heart failure. The age, urine microalbumin-to-creatinine ratio (ACR), blood urea nitrogen (BUN), uric acid(UA), and cystatin C (CysC) levels of patients in the combined acute kidney injury group were significantly higher than those in the unmerge group (P<0.05), and the left ventricular ejection fraction (LVEF) and epidermal growth factor receptor (eGFR) levels were significantly lower than those in the unmerge group ( P<0.05). Age, ACR, and CysC levels are independent risk factors for acute kidney injury in diabetic nephropathy, and LVEF and eGFR are independent protective factors ( P<0.05). The C-index of the nomogram risk prediction model in predicting acute kidney injury in diabetic nephropathy is 0.768 (95% CI: 0.663-0.806), and the calibration curve tends to the ideal curve; the prediction threshold is >0.18, and the nomogram risk prediction model provides a clinical net benefits, and clinical net benefits were higher than independent predictors. Conclusion: The establishment of a nomogram model for acute kidney injury in elderly patients with diabetic nephropathy based on age, ACR, CysC, LVEF, and eGFR has a good predictive effect, which can help doctors more accurately assess the patient's condition and provide a basis for formulating personalized treatment plans.

    Keywords: Acute Kidney Injury, elderly diabetic nephropathy, Influencing factors, nomogram, Model

    Received: 13 May 2024; Accepted: 19 Nov 2024.

    Copyright: © 2024 Wu, Liu, Ye, Xu, Zhang, Lu and Min. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Yanli Ye, The Second Affiliated Hospital of Hubei University of Science and Technology, Xianning, Hubei Province, China

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