Evidence map›Paper›PMID 40915558›Full record

Trial reportArchives of physical medicine and rehabilitation2026

Quantifying Exercise Intensity to Predict Changes in Walking Capacity in Individuals with Chronic Stroke.

Kiersten M McCartney, Pierce Boyne, Ryan Pohlig, Susanne M Morton, Darcy S Reisman

Abstract readRandomized Controlled TrialMulticenter Study
In one paragraph

Trial report in Archives of physical medicine and rehabilitation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Trial
  2. Article
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

5 authors.

Kiersten M McCartneyDepartment of Physical Therapy, University of Delaware, Newark, DE 19716; Biomechanics and Movement Science Program, University of Delaware, Newark, DE 19716.
Pierce BoyneDepartment of Rehabilitation, Exercise and Nutrition Sciences, University of Cincinnati, Cincinnati, OH 45221.
Ryan PohligBiostatistics Core, Epidemiology Department, University of Delaware, Newark, DE 19716.
Susanne M MortonDepartment of Physical Therapy, University of Delaware, Newark, DE 19716; Biomechanics and Movement Science Program, University of Delaware, Newark, DE 19716.
Darcy S ReismanDepartment of Physical Therapy, University of Delaware, Newark, DE 19716; Biomechanics and Movement Science Program, University of Delaware, Newark, DE 19716. Electronic address: dreisman@udel.edu.

Funding

Promoting Recovery Optimization with WALKing Exercise after Stroke (PROWALKS)R01HD086362 · NICHD · UNIVERSITY OF DELAWARE · PI REISMAN, DARCY S. · 2016 to 2020
$4.0M
PT/PHD Predoctoral Training Program Diversity SupplementT32HD007490 · NICHD · UNIVERSITY OF DELAWARE · PI DARCY S. REISMAN · 1996 to 2026
$3.7M
Building a data science workforce to improve the reproducibility of rehabilitation researchR25HD105583 · NICHD · UNIVERSITY OF SOUTHERN CALIFORNIA · PI David Nelson Kennedy, Sook-Lei Liew · 2022 to 2026
$812k
NICHD NIH HHS R01 HD086362NICHD NIH HHS R25 HD105583NICHD NIH HHS T32 HD007490
6 · The paper itself

Abstract

objectiveTo examine whether exercise intensity, quantified as heart rate or training speed, predicts walking outcomes in people with chronic stroke.

designThis is a secondary analysis from a larger randomized controlled trial ("Promoting Recovery Optimization of Walking Activity in Stroke"; NIH1R01HD086362).

settingFour outpatient rehabilitation clinics.

participantsParticipants with chronic stroke with a walking speed of 0.3-1.0 m/s and step activity of <8000 steps per day. This analysis included participants (N=169; age, 63.1±12.5, 46% women) with complete baseline and postintervention data.

interventionsParticipants were randomized into (1) fast-walking training or (2) fast-walking training and step-activity monitoring behavioral group. Of importance, participants received up to 36 sessions of 30-minute high-intensity treadmill walking training across 12 weeks.

main outcome measuresThe primary outcomes were a baseline-to-postintervention change in 6-minute walk test distance and fastest walking speed. Exercise intensity was quantified as either a percentage of heart rate reserve or self-selected walking speed.

resultsTwo separate multiple linear regressions with robust errors analyzed the relationship of exercise intensity metrics (% heart rate, training speed) on baseline-to-postintervention changes in 2 walking capacity outcomes (6-minute walk test, fastest walking speed) after accounting for covariates. Training speed was a significant predictor of both a change in 6-minute walk test distance (b=0.359; 95% CI, 0.108-0.610; P=.005) and fastest walking speed (b=0.001; 95% CI, 0.001-0.002; P=.003). Heart rate was not a significant predictor of either outcome (both P>.373).

conclusionsTraining speed significantly predicts changes in walking capacity outcomes in people with chronic stroke following a fast-walking treadmill intervention. This suggests rehabilitation clinicians may use training speed as the metric of exercise intensity when prescribing walking interventions to people with chronic stroke.

Indexed as

Exercise TherapyStroke RehabilitationWalkingAgedChronic DiseaseFemaleHeart RateHumansMaleMiddle AgedStrokeWalking SpeedWalk TestExercise intensityRehabilitationStrokeWalking

Identifiers

PMID40915558
PMCPMC12422713

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Registered trials

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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.