TY  - JOUR
AU  - Wiesmüller, Fabian
AU  - Prenner, Andreas
AU  - Ziegl, Andreas
AU  - El-Moazen, Gihan
AU  - Modre-Osprian, Robert
AU  - Baumgartner, Martin
AU  - Brodmann, Marianne
AU  - Seinost, Gerald
AU  - Silbernagel, Günther
AU  - Schreier, Günter
AU  - Hayn, Dieter
PY  - 2025
DA  - 2025/4/10
TI  - 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
JO  - JMIR Form Res
SP  - e65721
VL  - 9
KW  - mHealth
KW  - telehealth
KW  - peripheral arterial disease
KW  - home-based structured walking training
KW  - trend estimation
KW  - predictive modeling
KW  - continuous data
KW  - walking
KW  - walking training
KW  - prediction
KW  - prediction model
KW  - cardiovascular disease
KW  - stroke
KW  - heart failure
KW  - physical fitness
KW  - telehealth system
AB  - 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. Trial Registration: ClinicalTrials.gov Identifier: NCT05619835; https://tinyurl.com/mrxt7y9u 
SN  - 2561-326X
UR  - https://formative.jmir.org/2025/1/e65721
UR  - https://doi.org/10.2196/65721
DO  - 10.2196/65721
ID  - info:doi/10.2196/65721
ER  -