| Title: | Triaxial accelerometer-measured physical activity and functional behaviours among people with High Grade Glioma: The BrainWear Study |
| Journal: | PLOS ONE |
| Published: | 24 May 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37224155/ |
| DOI: | https://doi.org/10.1371/journal.pone.0285399 |
| URL: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0285399&type=printable |
Publication 7817
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Abstract
BACKGROUND: High-grade gliomas (HGG) account for 60-75% of all adult gliomas. The complexity of treatment, recovery and survivorship creates a need for novel monitoring approaches. Accurate assessment of physical function plays a vital role in clinical evaluation. Digital wearable tools could help us address unmet needs by offering unique advantages such as scale, cost and continuous real-world objective data. We present data from 42 patients enrolled into the BrainWear study. METHODS: An AX3 accelerometer was worn by patients from diagnosis or at recurrence. Age-, sex-matched UK Biobank control groups were chosen for comparison. RESULTS: 80% of data were categorised as high-quality demonstrating acceptability. Remote, passive monitoring identifies moderate activity reduces both during a course of radiotherapy (69 to 16 minutes/day) and at the time of progressive disease assessed by MRI (72 to 52 minutes/day). Mean acceleration (mg) and time spent walking daily (h/day) correlated positively with the global health quality of life and physical functioning scores and inversely with the fatigue score. Healthy controls walked on average 2.91h/day compared to 1.32h/day for the HGG group on weekdays and 0.91h/day on the weekend. The HGG cohort slept for longer on weekends (11.6h/day) than weekdays (11.2h/day) compared to healthy controls (8.9h/day). CONCLUSION: Wrist-worn accelerometers are acceptable and longitudinal studies feasible. HGG patients receiving a course of radiotherapy reduce their moderate activity by 4-fold and are at least half as active as healthy controls at baseline. Remote monitoring can provide a more informed and objective understanding of patient activity levels to help optimise health related quality of life (HRQoL) among a patient cohort with an extremely limited lifespan.4 Authors
- Seema Dadhania
- Lillie Pakzad-Shahabi
- Sanjay Mistry
- Matt Williams
1 Application
| Application ID | Title |
|---|---|
| 63790 | Integrating Wearable and personal data using machine-learning approaches |
Enabling scientific discoveries that improve human health