ORIGINAL RESEARCH article
Front. Endocrinol.
Sec. Clinical Diabetes
Volume 16 - 2025 | doi: 10.3389/fendo.2025.1578767
Development of predictive nomogram for clinical use of special-grade antimicrobial agents in patients with diabetes foot infections
Provisionally accepted
- 1Central Hospital Affiliated to Shandong First Medical University, Jinan, China
- 2Central Hospital Affiliated to Shandong First, Jinan, China
- 3Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
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Objective: To develop a predictive model to quantify the possibility of special-grade antimicrobial agents (SGAs) usage in patients with diabetes foot infections (DFIs), providing reference and guidance for clinical practice.Methods. This is a cross-sectional study of 328 type 2 diabetes patients with DFIs.General clinical characteristics and biochemical indicators were extracted from the Hospital Information System (HIS) of Jinan Central Hospital in Shandong Province, China. Logistic regression analysis was performed to select predictors, and the nomogram was established based on selected viables visually. Then, the receive operating characteristic (ROC) curve, the calibration curve and the decision curve analysis (DCA) were used to evaluate the performance of this prediction model. Results. 5 predictors were selected by univariate analysis from 21 variables, including duration of hospitalization, Neutrophil, DBIL, ALB and Wagner grade. The multivariate logical regression analysis illustrated that these 5 factors were independent risk factors for SGAs usage in patients with DFIs. The nomogram model developed by these 5 risk predictors exhibited good prediction ability, as shown by the area under curve (AUC) of ROC curve was 0.884 in the training set and 0.825 in the validation set. Calibration curve showed a good calibration degree of the predictive nomogram model. Moreover, DCA curve showed that the nomogram exhibited greater clinical application values when the risk threshold was between 3% and 63%. Conclusion. Our novel nomogram model showed that duration of hospitalization, Neutrophil, DBIL, ALB and Wagner grade were the independent risk factors of SGAs usage in patients with DFIs. This prediction model behaved a great accurate value and provide reference of SGAs usage in clinic. Further validations are still needed to evaluate and improve the performance of this model.
Keywords: diabetes foot infections, special-grade antimicrobial agents, Wagner grade, multivariate logical regression analysis, Nomogram model
Received: 18 Feb 2025; Accepted: 23 Jul 2025.
Copyright: © 2025 Wang, Ma, Jiang and Guo. 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: Lubo Guo, Central Hospital Affiliated to Shandong First Medical University, Jinan, China
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