ArticleFrontiers in endocrinology2024
Exploration of predictive risk factors for diabetic foot in patients with diabetes in Beijing: analysis of 5-year follow-up data of patients with diabetes mellitus in a single center in Beijing.
Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prediction of Factors Influencing the Incidence of Diabetic Foot Ulcers Using Classical Statistical and Machine Learning Approaches: A Systematic Review.International wound journal · 2026Pooled it
- Development and external validation of machine-learning based models to predict diabetic foot ulcer in diabetes population.Frontiers in endocrinology · 2025Article
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8 authors.
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Abstract
Background: Large-scale prospective cohort studies on diabetic foot ulcers risk factor screening in China are limited. Therefore, this prospective cohort study aimed to explore the predictive risk factors for diabetic foot ulcers to provide clinicians with concise and effective clinical indicators for identifying a high-risk diabetic foot and guiding the prevention of diabetic foot ulcers. Methods: Patients with diabetes who visited the Department of Endocrinology of Peking University First Hospital from October 2017 to December 2018 were selected as research participants by convenience sampling. A total of 968 patients were included. After enrollment, a dedicated person collected and recorded all baseline data. A dedicated telephone follow-up was conducted every 12-24 months to evaluate whether the endpoint event had occurred. All patients were followed up for an average of 61 (57-71) months, with 95% of them followed up for more than 60 months. According to the occurrence of endpoint events, they were divided into the DFU and non-DFU groups. The data between the two groups were analyzed using independent-sample t-test, Wilcoxon rank sum test, and chi square test. We used univariate and multivariate logistic regression analysis to analyze the factors that affected the occurrence of diabetic foot ulcers. Results and conclusions: After the 5-year follow-up, the incidence of diabetic foot was 25.83%. Multivariate logistic regression analysis revealed that body mass index (odds ratio: 1.046; 95% confidence interval: 1.001-1.093), abnormal pinprick sensation (odds ratio: 4.138; 95% confidence interval: 1.292-13.255), history of fungal foot infection (odds ratio: 2.287; 95% confidence interval: 1.517-3.448), abnormal 128-Hz tuning fork test (odds ratio: 2.628; 95% confidence interval: 1.098-6.294), and HbA1c≥ 8% (odds ratio: 1.522; 95% confidence interval: 1.014-2.284) were independent predictors of diabetic foot. Our study highlights clinically relevant indicators that may help to prevent the occurrence of diabetic foot and guide timely interventions.
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