Evidence map›Paper›PMID 39839574›Full record

ArticleFederal practitioner : for the health care professionals of the VA, DoD, and PHS2024

Multidisciplinary Amputation Prevention at the DeBakey VA Hospital: Our First Decade.

Neal R Barshes, Aimee D Garcia, Cezarina Mindru, Maria Rodriguez-Barradas, Panos Kougias, David M Green, Samir S Awad

Abstract read
In one paragraph

Article in Federal practitioner : for the health care professionals of the VA, DoD, and PHS, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Neal R BarshesMichael E. DeBakey Veterans Affairs Medical Center, Houston, Texas.
Aimee D GarciaMichael E. DeBakey Veterans Affairs Medical Center, Houston, Texas.
Cezarina MindruMichael E. DeBakey Veterans Affairs Medical Center, Houston, Texas.
Maria Rodriguez-BarradasMichael E. DeBakey Veterans Affairs Medical Center, Houston, Texas.
Panos KougiasState University of New York (SUNY) Downstate, Brooklyn.
David M GreenMichael E. DeBakey Veterans Affairs Medical Center, Houston, Texas.
Samir S AwadMichael E. DeBakey Veterans Affairs Medical Center, Houston, Texas.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In 2011, the Veterans Health Administration (VHA) undertook multidisciplinary efforts to improve care for patients with nonhealing foot ulcers and reduce leg amputation rates. This article examines the impact of interdisciplinary care for amputation prevention in the VHA. Methods: The VHA patient population was characterized using internal registries. Texas hospital admission data were used to identify sex and zip-code matched cohorts. VHA provided data on national and local frequencies of various amputations and the number of patients with diabetes. Results: Compared to matched nonveteran patients, veterans treated at VHA hospitals were older and more often self-identified as Black. They also had significantly higher rates of diabetes, chronic kidney disease, and systolic heart failure. A decrease from 160 to 66 amputations per 100,000 was seen from 2012 to 2017 (a 60% reduction) after implementing interdisciplinary care. Several evidence-directed practices were implemented during the study period. The proportion of angiograms for foot ulcers or gangrene increased from 28.9% to 90.9%. Conclusions: Interdisciplinary care can significantly reduce leg amputation rates. This reduction does not seem dependent on a particular model for providing inpatient care.

Identifiers

PMID39839574
PMCPMC11745363

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.