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				Development of a Diabetic Foot Ulceration Prediction Model and Nomogram														
			
			Eun Joo Lee, Ihn Sook Jeong, Seung Hun Woo, Hyuk Jae Jung, Eun Jin Han, Chang Wan Kang, Sookyung Hyun			
				J Korean Acad Nurs 2021;51(3):280-293.   Published online June 30, 2021			
									DOI: https://doi.org/10.4040/jkan.20257
							
							 
				
										
										 Abstract  PDFPurposeThis 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.
					Citations Citations to this article as recorded by   A Simple Nomogram for Predicting Stroke-Associated Pneumonia in Patients with Acute Ischemic StrokeYoun-Jung Lee, Hee Jung Jang
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 Applied Bionics and Biomechanics.2022; 2022: 1.     CrossRef
Prognostic factors in diabetes: Comparison of Chi-square automatic interaction detector (CHAID) decision tree technology and logistic regressionHae-Young Choi, Eun-Yeob Kim, Jaeyoung Kim
 Medicine.2022; 101(42): e31343.     CrossRef
 
		
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