The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Global prevalence of traumatic non-fatal limb amputation
Abstract
Background: Reliable information on both global need for prosthetic services and the current prosthetist workforce is limited. Global burden of disease estimates can provide valuable insight into amputation prevalence due to traumatic causes and global prosthetists needed to treat traumatic amputations. Objectives: This study was conducted to quantify and interpret patterns in global distribution and prevalence of traumatic limb amputation by cause, region, and age within the context of prosthetic rehabilitation, prosthetist need, and prosthetist education. Study design: A secondary database descriptive study. Methods: Amputation prevalence and prevalence rate per 100,000 due to trauma were estimated using the 2017 global burden of disease results. Global burden of disease estimation utilizes a Bayesian metaregression and best available data to estimate the prevalence of diseases and injuries, such as amputation. Results: In 2017, 57.7 million people were living with limb amputation due to traumatic causes worldwide. Leading traumatic causes of limb amputation were falls (36.2%), road injuries (15.7%), other transportation injuries (11.2%), and mechanical forces (10.4%). The highest number of prevalent traumatic amputations was in East Asia and South Asia followed by Western Europe, North Africa, and the Middle East, high-income North America and Eastern Europe. Based on these prevalence estimates, approximately 75,850 prosthetists are needed globally to treat people with traumatic amputations. Conclusion: Amputation prevalence estimates and patterns can inform prosthetic service provision, education and planning.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
James, S. L., Abate, D., Abate, K. H., Abay, S. M., Abbafati, C., Abbasi, N., Abbastabar, H., Abd-Allah, F., Abdela, J., Abdelalim, A., et al. (2018) · The Lancet · doi:10.1016/s0140-6736(18)32279-7 · Cited by 13,867
Self-citationVos, T., Abajobir, A. A., Abate, K. H., Abbafati, C., Abbas, K. M., Abd-Allah, F., Abdulkader, R. S., Abdulle, A. M., Abebo, T. A., Abera, S. F., et al. (2017) · The Lancet · doi:10.1016/s0140-6736(17)32154-2 · Cited by 13,220
Self-citationVos, T., Allen, C., Arora, M., Barber, R. M., Bhutta, Z. A., Brown, A., Carter, A., Casey, D. C., Charlson, F. J., Chen, A. Z., et al. (2016) · The Lancet · doi:10.1016/s0140-6736(16)31678-6 · Cited by 7,253
Self-citationEstimating the Prevalence of Limb Loss in the United States: 2005 to 2050
Ziegler-Graham, K., MacKenzie, E. J., Ephraim, P. L., Travison, T. G., & Brookmeyer, R. (2008) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2007.11.005 · Cited by 2,816
(2000) · American Journal of Public Health · doi:10.2105/ajph.90.4.523 · Cited by 1,320
Haagsma, J. A., Graetz, N., Bolliger, I., Naghavi, M., Higashi, H., Mullany, E. C., Abera, S. F., Abraham, J. P., Adofo, K., Alsharif, U., et al. (2016) · Injury Prevention · doi:10.1136/injuryprev-2015-041616 · Cited by 1,302
Self-citationChang, J. T., Morton, S. C., Rubenstein, L. Z., Mojica, W. A., Maglione, M., Suttorp, M. J., Roth, E. A., & Shekelle, P. G. (2004) · BMJ · doi:10.1136/bmj.328.7441.680 · Cited by 1,168
The global map for traumatic spinal cord injury epidemiology: update 2011, global incidence rate
Lee, B. B., Cripps, R. A., Fitzharris, M., & Wing, P. C. (2014) · Spinal Cord · doi:10.1038/sc.2012.158 · Cited by 871
Upper-Limb Prosthetics: Critical Factors in Device Abandonment
Biddiss, E., & Chau, T. (2007) · American Journal of Physical Medicine & Rehabilitation · doi:10.1097/phm.0b013e3181587f6c · Cited by 645
Moxey, P. W., Gogalniceanu, P., Hinchliffe, R. J., Loftus, I. M., Jones, K. J., Thompson, M. M., & Holt, P. J. (2011) · Diabetic Medicine · doi:10.1111/j.1464-5491.2011.03279.x · Cited by 589
Metadata
- Authors
- McDonald, C. L., Westcott-McCoy, S., Weaver, M. R., Haagsma, J., & Kartin, D.
- Venue
- Prosthetics & Orthotics International
- Published
- 2020-12
- Volume
- 45
- Issue
- 2
- Pages
- 105-114
- ISSN
- 0309-3646 (ISSN-L)
- 1746-1553
- OpenAlex
- W3109781171
- Cited by
- 357
- References
- 27
- FWCI
- 10.03
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Global prevalence of traumatic non-fatal limb amputation. https://app.cochat.ai/papers/10.1177/0309364620972258
- The paper
- McDonald, C. L., Westcott-McCoy, S., Weaver, M. R., Haagsma, J., & Kartin, D. (2021). Global prevalence of traumatic non-fatal limb amputation. Prosthetics & Orthotics International. https://doi.org/10.1177/0309364620972258
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
