Mortality prediction following non-traumatic amputation of the lower extremity

Author:

Norvell D C1ORCID,Thompson M L2,Boyko E J345,Landry G6,Littman A J357,Henderson W G8,Turner A P910,Maynard C7,Moore K P5,Czerniecki J M91011

Affiliation:

1. Spectrum Research, Tacoma, Washington, USA

2. Department of Biostatistics, University of Washington, Seattle, Washington, USA

3. Department of Epidemiology, University of Washington, Seattle, Washington, USA

4. Division of Internal Medicine, University of Washington, Seattle, Washington, USA

5. Epidemiologic Research and Information Center, VA Puget Sound Health Care System, Seattle, Washington, USA

6. Department of Surgery, Division of Vascular Surgery, Oregon Health and Science University, Portland, Oregon, USA

7. Health Services Research and Development, VA Puget Sound Health Care System, Seattle, Washington, USA

8. Adult and Child Consortium for Outcomes Research and Delivery Science, University of Colorado, Denver, Colorado, USA

9. Department of Rehabilitation Medicine, University of Washington, Seattle, Washington, USA

10. Rehabilitation Care Services, VA Puget Sound Health Care System, Seattle, Washington, USA

11. Veterans Affairs (VA) Center for Limb Loss and Mobility (CLiMB), VA Puget Sound Health Care System, Seattle, Washington, USA

Abstract

Abstract Background Patients who undergo lower extremity amputation secondary to the complications of diabetes or peripheral artery disease have poor long-term survival. Providing patients and surgeons with individual-patient, rather than population, survival estimates provides them with important information to make individualized treatment decisions. Methods Patients with peripheral artery disease and/or diabetes undergoing their first unilateral transmetatarsal, transtibial or transfemoral amputation were identified in the Veterans Affairs Surgical Quality Improvement Program (VASQIP) database. Stepdown logistic regression was used to develop a 1-year mortality risk prediction model from a list of 33 candidate predictors using data from three of five Department of Veterans Affairs national geographical regions. External geographical validation was performed using data from the remaining two regions. Calibration and discrimination were assessed in the development and validation samples. Results The development sample included 5028 patients and the validation sample 2140. The final mortality prediction model (AMPREDICT-Mortality) included amputation level, age, BMI, race, functional status, congestive heart failure, dialysis, blood urea nitrogen level, and white blood cell and platelet counts. The model fit in the validation sample was good. The area under the receiver operating characteristic (ROC) curve for the validation sample was 0·76 and Cox calibration regression indicated excellent calibration (slope 0·96, 95 per cent c.i. 0·85 to 1·06; intercept 0·02, 95 per cent c.i. –0·12 to 0·17). Given the external validation characteristics, the development and validation samples were combined, giving a total sample of 7168. Conclusion The AMPREDICT-Mortality prediction model is a validated parsimonious model that can be used to inform the 1-year mortality risk following non-traumatic lower extremity amputation of patients with peripheral artery disease or diabetes.

Funder

US Department of Veterans Affairs, Office of Research and Development, Rehabilitation Research and Development

Publisher

Oxford University Press (OUP)

Subject

Surgery

Reference32 articles.

1. Patient experience of recovery after major leg amputation for arterial disease;Columbo;Vasc Endovascular Surg,2018

2. Major lower extremity amputation: outcome of a modern series;Aulivola;Arch Surg,2004

3. Domains that determine quality of life in vascular amputees;Suckow;Ann Vasc Surg,2015

4. Lower extremity amputation in peripheral artery disease: improving patient outcomes;Swaminathan;Vasc Health Risk Manag,2014

5. Risk factors for early failure of surgical amputations: an analysis of 8878 isolated lower extremity amputation procedures;O'Brien;J Am Coll Surg,2013

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