# Evaluation of clinical trajectories and identification of modifiable risk factors to improve secondary prevention of amputation in Veterans with diabetes following an initial toe amputation.

> **NIH VA I01** · VA PUGET SOUND HEALTHCARE SYSTEM · 2020 · —

## Abstract

Toe amputations are often naively viewed as an inconsequential surgical procedure with little functional
impact. Instead, a toe amputation is often the inciting event in a cascade of progressive loss of function and
quality of life. One in three people undergoing toe amputations due to chronic illness fail to heal the amputation
in a timely manner, requiring additional amputation surgery(ies) and one in five die in the following year.
Inadequate healing may be related to suboptimal management of comorbid conditions (e.g., diabetes,
peripheral vascular disease, depression and/or PTSD). Veterans with limited social support may be further
limited in their ability to self-manage their illness and engage in treatment to facilitate healing and prevent
additional amputation. Veterans who undergo r
epeated amputations lose functional life years as they are
hospitalized, recover from surgery, are re-hospitalized and undergo additional surgeries.
 This 3-year study has three primary aims: 1) to characterize amputation trajectories and evaluate
trends in subsequent amputation and death in the year after initial toe amputation overall, based on
demographic characteristics, selected clinical factors (e.g., vascular status), and geographic location (e.g.,
Veterans Integrated Service Networks [VISN]), 2) to evaluate the associations between modifiable risk factors
and 1-year risk of subsequent amputation or death while controlling for important risk factors that confound
these associations, and 3) to acquire knowledge, attitudes, and behaviors related to secondary prevention
using semi-structured interviews among patients who have undergone a toe amputation and providers who
care for these patients to develop future interventions that improve outcomes in these patients. We will
accomplish these goals by using the newly constructed VHA Amputee Registry/Repository, merged with
relevant VA electronic medical record data, and in-depth interviews with providers and patients. Our proposed
research – a retrospective cohort study including all VHA patients (~16,000-19,000) with diabetes with a first
ever toe amputation between FY 2005 and 2016 -- will be the largest study conducted to date, national in
scope, and will supplement structured data with unstructured data to ascertain key information about not only
the amputation but also other relevant patient characteristics. For Aim 1, frequencies and percentages of the
following clinical outcomes will be obtained: subsequent amputation within 1-, 6-, and 12-months; counts of
subsequent amputations; the final level of amputation at 12 months; and death. After evaluating crude rates,
identifying and inspecting outliers, we will formally test for trends across time by including year as a predictor
variable in logistic regression models, considering the use of piece-wise regression to allow for multiple slopes
(non-linear trends). Similar models will be constructed to test for variation across VISN. Key modifiable risk
fact...

## Key facts

- **NIH application ID:** 9883777
- **Project number:** 5I01HX002044-03
- **Recipient organization:** VA PUGET SOUND HEALTHCARE SYSTEM
- **Principal Investigator:** Alyson Littman
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2020
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2018-01-01 → 2020-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9883777

## Citation

> US National Institutes of Health, RePORTER application 9883777, Evaluation of clinical trajectories and identification of modifiable risk factors to improve secondary prevention of amputation in Veterans with diabetes following an initial toe amputation. (5I01HX002044-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9883777. Licensed CC0.

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