Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/29235
Title: Protocol for Project Fizzyo, an analytic longitudinal observational cohort study of physiotherapy for children and young people with cystic fibrosis, with interrupted time-series design
Authors: Raywood, E
Douglas, H
Kapoor, K
Filipow, N
Murray, N
O'Connor, R
Stott, L
Saul, G
Kuzhagaliyev, T
Davies, G
Liakhovich, O
Van Schaik, T
Furtuna, B
Booth, J
Shannon, H
Bryon, M
Main, E
Issue Date: 7-Oct-2020
Publisher: BMJ Publishing Group
Citation: Raywood, E. et al. (2020) 'Protocol for Project Fizzyo, an analytic longitudinal observational cohort study of physiotherapy for children and young people with cystic fibrosis, with interrupted time-series design', BMJ Open, 10 (10), e039587, pp. 1 - 10. doi: 10.1136/bmjopen-2020-039587.
Abstract: Introduction: Daily physiotherapy is believed to mitigate the progression of cystic fibrosis (CF) lung disease. However, physiotherapy airway clearance techniques (ACTs) are burdensome and the evidence guiding practice remains weak. This paper describes the protocol for Project Fizzyo, which uses innovative technology and analysis methods to remotely capture longitudinal daily data from physiotherapy treatments to measure adherence and prospectively evaluate associations with clinical outcomes. Methods and analysis: A cohort of 145 children and young people with CF aged 6–16 years were recruited. Each participant will record their usual physiotherapy sessions daily for 16 months, using remote monitoring sensors: (1) a bespoke ACT sensor, inserted into their usual ACT device and (2) a Fitbit Alta HR activity tracker. Real-time breath pressure during ACTs, and heart rate and daily step counts (Fitbit) are synced using specific software applications. An interrupted time-series design will facilitate evaluation of ACT interventions (feedback and ACT-driven gaming). Baseline, mid and endpoint assessments of spirometry, exercise capacity and quality of life and longitudinal clinical record data will also be collected. This large dataset will be analysed in R using big data analytics approaches. Distinct ACT and physical activity adherence profiles will be identified, using cluster analysis to define groups of individuals based on measured characteristics and any relationships to clinical profiles assessed. Changes in adherence to physiotherapy over time or in relation to ACT interventions will be quantified and evaluated in relation to clinical outcomes. Ethics and dissemination: Ethical approval for this study (IRAS: 228625) was granted by the London-Brighton and Sussex NREC (18/LO/1038). Findings will be disseminated via peer-reviewed publications, at conferences and via CF clinical networks. The statistical code will be published in the Fizzyo GitHub repository and the dataset stored in the Great Ormond Street Hospital Digital Research Environment. Trial registration number: ISRCTN51624752; Pre-results.
Description: Twitter @fizzyocf
URI: https://bura.brunel.ac.uk/handle/2438/29235
DOI: https://doi.org/10.1136/bmjopen-2020-039587
Other Identifiers: ORCiD: Emma Raywood https://orcid.org/0000-0002-0993-5115
ORCiD: Helen Douglas https://orcid.org/0000-0002-5184-6300
ORCiD: Gwyneth Davies https://orcid.org/0000-0001-7937-2728
ORCiD: Tempest Van Schaik https://orcid.org/0000-0001-7745-2249
ORCiD: Eleanor Main https://orcid.org/0000-0002-9739-3167
e039587
Appears in Collections:Dept of Health Sciences Research Papers

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