Estimating Recent US Limb Loss Prevalence and Updating Future Projections.

Abstract

Objective: To estimate limb loss prevalence in the United States (US) by etiology and anatomical position and the trends of limb loss over 40 years.

Design: We used the National Inpatient Sample, Healthcare Cost and Utilization Project to estimate current and future limb loss prevalence in the US and by anatomical location. Prevalence estimates were based on the incidence and duration of the disease. Lastly, we use a linear regression to estimate future projections of limb loss prevalence.

Setting: Open-sourced data from the National Inpatient Sample, Healthcare Cost and Utilization Project.

Participants: Persons who have undergone an amputation at a community hospital participating in the National Inpatient Sample database. We define community hospitals as all nonfederal, short-term, general, and other specialty hospitals, excluding hospital units of institutions.

Interventions: Not applicable.

Main outcome measures: The current prevalence of limb loss.

Results: The total estimated number of people living with limb loss in the US was 2,309,000. In total, ∼91% of persons underwent lower extremity amputation, while only 9.2% underwent upper extremity amputations. By 2060, we projected a 145% increase in people living with limb loss in the US. Most of these are caused by vascular disease and diabetes which are projected to increase by 36% and 67%, respectively, by 2060. The number of people living with limb loss will double by 2050, while the number of people with diabetes will double by 2040.

Conclusions: Our updated estimate for the prevalence of limb loss in 2019 was comparable to previous projections for 2020; however, our projected estimates are markedly increased relative to those of other studies. Our increased values are caused by the increased prevalence of diabetes and peripheral vascular diseases resulting in amputation. These results highlight the importance of research directed at both limb preservation and amputation optimization and the allocation of health care resources.