J M Czerniecki1,2,3, M L Thompson4, A J Littman5,6,7, E J Boyko8,9, G J Landry10, W G Henderson11, A P Turner2,3, C Maynard6, K P Moore8, D C Norvell1,12. 1. Veterans Affairs (VA) Center for Limb Loss and Mobility (CLiMB), VA Puget Sound Health Care System, Seattle, USA. 2. Rehabilitation Care Services, VA Puget Sound Health Care System, Seattle, USA. 3. Department of Rehabilitation, University of Washington, Portland, Oregon, USA. 4. Department of Biostatistics, University of Washington, Portland, Oregon, USA. 5. Center for Veteran-Centered and Value-Driven Care, VA Puget Sound Health Care System, Seattle, USA. 6. Health Services Research and Development, VA Puget Sound Health Care System, Seattle, USA. 7. Department of Epidemiology, University of Washington, Portland, Oregon, USA. 8. Epidemiologic Research and Information Center, VA Puget Sound Health Care System, Seattle, USA. 9. Department of Medicine, University of Washington, Portland, Oregon, USA. 10. Department of Surgery, Division of Vascular Surgery, Oregon Health and Science University, Portland, Oregon, USA. 11. Adult and Child Consortium for Outcomes Research and Delivery Science, University of Colorado, Denver, Colorado, USA. 12. Spectrum Research, Tacoma, USA.
Abstract
BACKGROUND: Patients undergoing amputation of the lower extremity for the complications of peripheral artery disease and/or diabetes are at risk of treatment failure and the need for reamputation at a higher level. The aim of this study was to develop a patient-specific reamputation risk prediction model. METHODS: Patients with incident unilateral transmetatarsal, transtibial or transfemoral amputation between 2004 and 2014 secondary to diabetes and/or peripheral artery disease, and who survived 12 months after amputation, were identified using Veterans Health Administration databases. Procedure codes and natural language processing were used to define subsequent ipsilateral reamputation at the same or higher level. Stepdown logistic regression was used to develop the prediction model. It was then evaluated for calibration and discrimination by evaluating the goodness of fit, area under the receiver operating characteristic curve (AUC) and discrimination slope. RESULTS: Some 5260 patients were identified, of whom 1283 (24·4 per cent) underwent ipsilateral reamputation in the 12 months after initial amputation. Crude reamputation risks were 40·3, 25·9 and 9·7 per cent in the transmetatarsal, transtibial and transfemoral groups respectively. The final prediction model included 11 predictors (amputation level, sex, smoking, alcohol, rest pain, use of outpatient anticoagulants, diabetes, chronic obstructive pulmonary disease, white blood cell count, kidney failure and previous revascularization), along with four interaction terms. Evaluation of the prediction characteristics indicated good model calibration with goodness-of-fit testing, good discrimination (AUC 0·72) and a discrimination slope of 11·2 per cent. CONCLUSION: A prediction model was developed to calculate individual risk of primary healing failure and the need for reamputation surgery at each amputation level. This model may assist clinical decision-making regarding amputation-level selection.
BACKGROUND:Patients undergoing amputation of the lower extremity for the complications of peripheral artery disease and/or diabetes are at risk of treatment failure and the need for reamputation at a higher level. The aim of this study was to develop a patient-specific reamputation risk prediction model. METHODS:Patients with incident unilateral transmetatarsal, transtibial or transfemoral amputation between 2004 and 2014 secondary to diabetes and/or peripheral artery disease, and who survived 12 months after amputation, were identified using Veterans Health Administration databases. Procedure codes and natural language processing were used to define subsequent ipsilateral reamputation at the same or higher level. Stepdown logistic regression was used to develop the prediction model. It was then evaluated for calibration and discrimination by evaluating the goodness of fit, area under the receiver operating characteristic curve (AUC) and discrimination slope. RESULTS: Some 5260 patients were identified, of whom 1283 (24·4 per cent) underwent ipsilateral reamputation in the 12 months after initial amputation. Crude reamputation risks were 40·3, 25·9 and 9·7 per cent in the transmetatarsal, transtibial and transfemoral groups respectively. The final prediction model included 11 predictors (amputation level, sex, smoking, alcohol, rest pain, use of outpatient anticoagulants, diabetes, chronic obstructive pulmonary disease, white blood cell count, kidney failure and previous revascularization), along with four interaction terms. Evaluation of the prediction characteristics indicated good model calibration with goodness-of-fit testing, good discrimination (AUC 0·72) and a discrimination slope of 11·2 per cent. CONCLUSION: A prediction model was developed to calculate individual risk of primary healing failure and the need for reamputation surgery at each amputation level. This model may assist clinical decision-making regarding amputation-level selection.
Authors: Chelsea Leonard; George Sayre; Sienna Williams; Alison Henderson; Daniel Norvell; Aaron P Turner; Joseph Czerniecki Journal: PLoS One Date: 2022-03-18 Impact factor: 3.752
Authors: Damianos G Kokkinidis; Stefanos Giannopoulos; Moosa Haider; Timothy Jordan; Anita Sarkar; Gagan D Singh; Eric A Secemsky; Jay Giri; Joshua A Beckman; Ehrin J Armstrong Journal: Vasc Med Date: 2020-05-27 Impact factor: 3.239
Authors: Brenig L Gwilym; Cherry-Ann Waldron; Emma Thomas-Jones; Ryan Preece; Sarah Milosevic; Lucy Brookes-Howell; Philip Pallmann; Debbie Harris; Ian Massey; Jo Burton; Philippa Stewart; Katie Samuel; Sian Jones; David Cox; Adrian Edwards; Chris Twine; David C Bosanquet Journal: BJS Open Date: 2021-11-09