Journal of Korean Academy of Nursing (대한간호학회지)

Korean Society of Nursing Science (한국간호과학회)
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Development of a Diabetic Foot Ulceration Prediction Model and Nomogram

당뇨병성 발궤양 발생 위험 예측모형과 노모그램 개발

  • 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)
  • 이은주 (동의대학교 의료보건생활대학) ;
  • 정인숙 (부산대학교 간호대학) ;
  • 우승훈 (양산부산대학교병원 정형외과) ;
  • 정혁재 (부산대학교병원 혈관이식외과) ;
  • 한은진 (세브란스병원 간호국) ;
  • 강창완 (동의대학교 IT융합부품소재공과대학) ;
  • 현수경 (부산대학교 간호대학)
  • Received : 2020.10.28
  • Accepted : 2021.03.15
  • Published : 2021.06.30
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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

Acknowledgement

The authors express special thanks to Dr. R. Garry Sibbald for kindly giving us his permission to use the 60-second tool.

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