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http://dx.doi.org/10.4040/jkan.20257

Development of a Diabetic Foot Ulceration Prediction Model and Nomogram  

Lee, Eun Joo (College of Nursing, Healthcare Sciences & Human Ecology, Dong-Eui University)
Jeong, Ihn Sook (College of Nursing, Pusan National University)
Woo, Seung Hun (Department of Orthopedics, Pusan National University Yangsan Hospital)
Jung, Hyuk Jae (Endovascular and Vascular and Transplantation Division, Department of Surgery, Pusan National University Hospital)
Han, Eun Jin (Division of Nursing, Severance Hospital)
Kang, Chang Wan (IT Convergence College of Components and Materials Engineering, Dong-Eui University)
Hyun, Sookyung (College of Nursing, Pusan National University)
Publication Information
Journal of Korean Academy of Nursing / v.51, no.3, 2021 , pp. 280-293 More about this Journal
Abstract
Purpose: This study aimed to identify the risk factors for diabetic foot ulceration (DFU) to develop and evaluate the performance of a DFU prediction model and nomogram among people with diabetes mellitus (DM). Methods: This unmatched case-control study was conducted with 379 adult patients (118 patients with DM and 261 controls) from four general hospitals in South Korea. Data were collected through a structured questionnaire, foot examination, and review of patients' electronic health records. Multiple logistic regression analysis was performed to build the DFU prediction model and nomogram. Further, their performance was analyzed using the Lemeshow-Hosmer test, concordance statistic (C-statistic), and sensitivity/specificity analyses in training and test samples. Results: The prediction model was based on risk factors including previous foot ulcer or amputation, peripheral vascular disease, peripheral neuropathy, current smoking, and chronic kidney disease. The calibration of the DFU nomogram was appropriate (χ2 = 5.85, p = .321). The C-statistic of the DFU nomogram was .95 (95% confidence interval .93~.97) for both the training and test samples. For clinical usefulness, the sensitivity and specificity obtained were 88.5% and 85.7%, respectively at 110 points in the training sample. The performance of the nomogram was better in male patients or those having DM for more than 10 years. Conclusion: The nomogram of the DFU prediction model shows good performance, and is thereby recommended for monitoring the risk of DFU and preventing the occurrence of DFU in people with DM.
Keywords
Diabetic Foot; Foot Ulcer; Logistic Models; Risk;
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