Evidence map›Paper›PMID 41768409›Full record

ArticleFrontiers in rehabilitation sciences2026

Gait stability in peripheral artery disease: a phase-dependent analysis using gait tube methodology.

Arash Mohammadzadeh Gonabadi, Iraklis I Pipinos, Sara A Myers, Farahnaz Fallahtafti

Abstract read
In one paragraph

Article in Frontiers in rehabilitation sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

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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

4 authors.

Arash Mohammadzadeh GonabadiResearch Institute, Madonna Rehabilitation Hospitals, Omaha, NE, United States.
Iraklis I PipinosDepartment of Surgery, University of Nebraska Medical Center, Omaha, NE, United States.
Sara A MyersDepartment of Biomechanics, University of Nebraska at Omaha, Omaha, NE, United States.
Farahnaz FallahtaftiDepartment of Biomechanics, University of Nebraska at Omaha, Omaha, NE, United States.

Funding

Improving mobility in peripheral artery disease using an ankle foot orthosisR01HD090333 · NICHD · UNIVERSITY OF NEBRASKA OMAHA · PI MYERS, SARA A · 2016 to 2020
$2.1M
NICHD NIH HHS R01 HD090333RRD VA I01 RX003266RRD VA I21 RX004632
6 · The paper itself

Abstract

Introduction: Peripheral Artery Disease (PAD) affects over eight million U.S. adults, impairing mobility, quality of life, and increasing fall and cardiovascular risks. PAD reduces lower limb blood flow and contributes to neuromuscular dysfunction, leading to unstable gait. Traditional stability metrics often miss phase-specific changes. Gait Tube Stability (GTS) is a phase-dependent, three-dimensional method that analyzes center of mass (COM) velocity using ellipsoidal variability to detect directional instability. This study examined whether GTS can identify phase-specific gait deficits in PAD compared with age-matched controls. Methods: Fifty-two PAD patients and 132 healthy individuals walked on a force-instrumented treadmill at self-selected speeds. GTS metrics-including ellipsoid volume and direction-specific variabilities (AP, ML, VT)-were computed from 3D COM velocity. Data were segmented by gait phase and analyzed using Wilcoxon rank-sum tests and Statistical Parametric Mapping (SPM). Results: PAD patients exhibited significantly lower ellipsoid volumes (3.07 × 10 Discussion: GTS revealed phase-specific gait deficits in PAD, especially during weight acceptance and early stance, indicating a constrained, energy-conserving strategy that may elevate fall risk. By detecting critical instability phases, GTS can guide targeted physical therapy, assistive device use, and optimal timing for robotic or exoskeleton support-supporting personalized interventions and offering a sensitive tool for clinical gait stability assessment.

Indexed as

fall riskgait tube stabilityperipheral artery disease (PAD)phase-dependent analysiswalking stability

Identifiers

PMID41768409
PMCPMC12935866

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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.