# BEST-VIVA Registry (vCLI)

> **NIH NIH R01** · DUKE UNIVERSITY · 2020 · $770,362

## Abstract

Project Summary / Abstract
Critical limb ischemia (CLI), a lack of blood flow to the leg characterized by leg pain at rest or by tissue loss,
affects approximately 2 million Americans and is characterized by increased rates of cardiovascular and limb
complications. Management of CLI is rapidly evolving, with the advent of minimally invasive techniques to
restore blood flow and advances in wound care. However, there is little consensus regarding optimal
treatment. The ongoing NIH funded BEST-CLI is designed to assess the comparative effectiveness of
minimally invasive versus full surgical restoration of blood flow in CLI, however, little is known about current
nationwide practice patterns, outcomes, quality of life, and healthcare resource utilization in CLI. Additionally,
the BEST-CLI trial will enroll a selected patient population that may not be fully representative of “real world”
CLI patients. As a result, in conjunction with the BEST-CLI investigators and BEST-CLI Trial, we
propose the companion BEST-VIVA registry (vCLI) to investigate the following aims: 1) Describe the
baseline demographics, comorbidities, and treatment strategies of consecutive patients excluded from the
BEST-CLI Trial and included in the vCLI registry, with a focus on variations in care 2) Describe the clinical
outcomes – specifically major adverse limb events (MALE) free survival, wound healing, and major adverse
cardiovascular events (MACE) - by treatment strategy in CLI patients, with a focus on causes of outcome
variation within treatment strategy 3) Describe healthcare related quality of life and healthcare costs, by
treatment strategy in the vCLI registry, with a focus on causes of variation in quality of life and costs.
Methods: The vCLI registry will be funded by a unique public / private partnership with governance from both
vCLI primary investigators and BEST-CLI primary investigators. For Aim 1, Multilevel multivariate regression
will be used to identify patient, physician/hospital, and geographic factors associated with variations in
treatment strategies. For Aim 2, Kaplan Meier and cumulative incidence estimates of limb and cardiovascular
outcomes will be stratified by treatment strategy and other subgroups of interest. The impact of diabetes and
CKD will be quantified by multivariable modeling and clinical risk prediction scores will be developed separately
for each treatment strategy. For Aim 3, quality of life, costs, and cost effectiveness will be described for each
treatment strategy and sources of variation within each treatment strategy will be identified via multivariable
regression. Impact: The results of the grant will help to illuminate current practices and outcomes in the care
of CLI. Data generated regarding patient demographics, variations in clinical outcomes, and variations in costs
/ cost effectiveness will serve to 1) identify targets for future healthcare systems interventions to improve
adherence to guideline recommended care and 2) prov...

## Key facts

- **NIH application ID:** 9913570
- **Project number:** 5R01HL141213-02
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Manesh R Patel
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $770,362
- **Award type:** 5
- **Project period:** 2019-04-15 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9913570

## Citation

> US National Institutes of Health, RePORTER application 9913570, BEST-VIVA Registry (vCLI) (5R01HL141213-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/9913570. Licensed CC0.

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