Evidence map›Paper›PMID 40209048›Full record

ArticleJMIR formative research2025

Support of Home-Based Structured Walking Training and Prediction of the 6-Minute Walk Test Distance in Patients With Peripheral Arterial Disease Based on Telehealth Data: Prospective Cohort Study.

Fabian Wiesmüller, Andreas Prenner, Andreas Ziegl, Gihan El-Moazen, Robert Modre-Osprian, Martin Baumgartner, Marianne Brodmann, Gerald Seinost, Günther Silbernagel, Günter Schreier and 1 more

Abstract read
In one paragraph

Article in JMIR formative research, 2025. 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

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

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

11 authors.

Fabian WiesmüllerCenter for Health & Bioresources, AIT Austrian Institute of Technology GmbH, Graz, Austria.ORCID 0000-0001-6567-7782
Andreas PrennerDivision of Angiology, Department of Internal Medicine, Medical University of Graz, Graz, Austria.ORCID 0009-0008-5053-7996
Andreas Ziegltelbiomed Medizintechnik und IT Service GmbH, Graz, Austria.ORCID 0000-0003-1948-567X
Gihan El-MoazenInstitute of Neural Engineering, Graz University of Technology, Graz, Austria.ORCID 0009-0005-1623-8958
Robert Modre-Ospriantelbiomed Medizintechnik und IT Service GmbH, Graz, Austria.ORCID 0000-0003-3456-8780
Martin BaumgartnerCenter for Health & Bioresources, AIT Austrian Institute of Technology GmbH, Graz, Austria.ORCID 0000-0002-6731-6873
Marianne BrodmannDivision of Angiology, Department of Internal Medicine, Medical University of Graz, Graz, Austria.ORCID 0000-0001-6493-3799
Gerald SeinostDivision of Angiology, Department of Internal Medicine, Medical University of Graz, Graz, Austria.ORCID 0000-0002-2577-9984
Günther SilbernagelDivision of Angiology, Department of Internal Medicine, Medical University of Graz, Graz, Austria.ORCID 0000-0001-9323-329X
Günter SchreierCenter for Health & Bioresources, AIT Austrian Institute of Technology GmbH, Graz, Austria.ORCID 0000-0003-3724-4255
Dieter HaynCenter for Health & Bioresources, AIT Austrian Institute of Technology GmbH, Graz, Austria.ORCID 0000-0003-1822-9033

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Telehealth has been effective in managing cardiovascular diseases like stroke and heart failure and has shown promising results in managing patients with peripheral arterial disease. However, more work is needed to fully understand the effect of telehealth-based predictive modeling on the physical fitness of patients with peripheral arterial disease. Objective: For this work, data from the Keep Pace study were analyzed in depth to gain insights on temporal developments of patients' conditions and to develop models to predict the patients' total walking distance at the study end. This could help to determine patients who are likely to benefit from the telehealth program and to continuously provide estimations to the patients as a motivating factor. Methods: This work analyzes continuous patient-reported telehealth data, in combination with in-clinic data from 19 Fontaine stage II patients with peripheral arterial disease who underwent a 12-week telehealth-based walking program. This analysis granted insights into the increase of the total walking distance of the 6-minute walk tests (6MWT) as a measure for physical fitness, the steady decrease in the patients' pain, and the positive correlation between well-being and the total walking distance measured by the 6MWT. Results: This work analyzed trends of and correlations between continuous patient-generated data. Findings of this study include a significant decrease of the patients' pain sensation over time (P=.006), a low but highly significant correlation between pain sensation and steps taken on the same day (r=-0.11; P<.001) and the walking distance of the independently performed 6MWTs (r=-0.39; P<.001). Despite the reported pain, adherence to the 6MWT measurement protocol was high (85.53%). Additionally, patients significantly improved their timed-up-and-go test times during the study (P=.002). Predicting the total walking distance at the study end measured by the 6MWT worked well at study baseline (root mean squared error of 30 meters; 7.04% of the mean total walking distance at the study end of 425 meters) and continuously improved by adding further telehealth data. Future work should validate these findings in a larger cohort and in a prospective setting based on a clinical outcome. Conclusions: We conclude that the prototypical trend estimation has great potential for an integration in the telehealth system to be used in future work to provide tailored patient-specific advice based on these predictions. Continuous data from the telehealth system grant a deeper insight and a better understanding of the patients' status concerning well-being and level of pain as well as their current physical fitness level and the progress toward reaching set goals.

Indexed as

Exercise TherapyPeripheral Arterial DiseaseWalkingWalk TestAgedFemaleHumansMaleMiddle AgedPhysical FitnessProspective StudiesTelemedicinecardiovascular diseasecontinuous dataheart failurehome-based structured walking trainingmHealthperipheral arterial diseasephysical fitnesspredictionprediction modelpredictive modelingstroketelehealthtelehealth systemtrend estimationwalkingwalking training

Identifiers

PMID40209048
PMCPMC12005459

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.