ORIGINAL RESEARCH article
Front. Endocrinol.
Sec. Renal Endocrinology
Volume 16 - 2025 | doi: 10.3389/fendo.2025.1557185
Establishment and validation of a Risk Prediction Model for Urinary Tract Infection in Elderly Patients With Type 2 Diabetes Mellitus
Provisionally accepted
- 1People's Republic of China, Anhui, China
- 2Department of Neurology, People’s Hospital of Lixin County, Bozhou, China
- 3Department of Nosocomial Awareness, Lixin County Hospital of Traditional Chinese Medicine, Bozhou, China., Bozhou, China
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Objectives: This study aimed to identify the risk factors for urinary tract infection (UTI) in elderly patients with type 2 diabetes mellitus (T2DM) and to develop and validate a nomogram that predicts the probability of UTI based on these factors.Methods:We collected clinical data from patients with diabetes who were aged 60 years or older. These patients were then divided into a modeling population (n=281) and an internal validation population (n=121) based on the principle of random assignment. LASSO regression analysis was conducted using the modeling population to identify the independent risk factors for UTI in elderly patients with T2DM. Logistics univariate and multifactor regressions were performed by the screened influencing factors, and then column line graph prediction models for UTI in elderly patients with T2DM were made by these influencing factors, using receiver operating characteristic curve and area under curve, C-index validation, and calibration curve to initially evaluate the model discrimination and calibration. Model validation was performed by the internal validation set, and the ROC curve, C-index and calibration curve were used to further evaluate the column line graph model performance. Finally, using DCA (decision curve analysis), we observed whether the model could be used better in clinical settings.The study enrolled a total of 402 patients with T2DM, of which 281 were in the training cohort, and 70 of these patients had UTI. Six
Keywords: Urinary tract infection, type 2 diabetes mellitus, nomogram, Decision curve analysis, Diabetes Mellitus
Received: 08 Jan 2025; Accepted: 23 Jun 2025.
Copyright: © 2025 Li, Li and He. 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: Yaqiang Li, People's Republic of China, Anhui, China
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