DIGIPREDICT: Physiological, Behavioural and Environmental Predictors of Asthma Attacks-A Prospective Observational Study Using Digital Markers and Artificial Intelligence - Study Protocol

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aut.relation.issue1
aut.relation.journalBMJ Open Respiratory Research
aut.relation.startpagee002275
aut.relation.volume11
dc.contributor.authorChan, Amy Hai Yan
dc.contributor.authorTe Ao, Braden
dc.contributor.authorBaggott, Christina
dc.contributor.authorCavadino, Alana
dc.contributor.authorEikholt, Amber A
dc.contributor.authorHarwood, Matire
dc.contributor.authorHikaka, Joanna
dc.contributor.authorGibbs, Dianna
dc.contributor.authorHudson, Mariana
dc.contributor.authorMirza, Farhaan
dc.contributor.authorNaeem, Muhammed Asif
dc.contributor.authorSemprini, Ruth
dc.contributor.authorChang, Catherina L
dc.contributor.authorTsang, Kevin CH
dc.contributor.authorShah, Syed Ahmar
dc.contributor.authorJeremiah, Aron
dc.contributor.authorAbeysinghe, Binu Nisal
dc.contributor.authorRoy, Rajshri
dc.contributor.authorWall, Clare
dc.contributor.authorWood, Lisa
dc.contributor.authorDalziel, Stuart
dc.contributor.authorPinnock, Hilary
dc.contributor.authorvan Boven, Job FM
dc.contributor.authorRoop, Partha
dc.contributor.authorHarrison, Jeff
dc.date.accessioned2024-05-28T04:07:30Z
dc.date.available2024-05-28T04:07:30Z
dc.date.issued2024-05-22
dc.description.abstractINTRODUCTION: Asthma attacks are a leading cause of morbidity and mortality but are preventable in most if detected and treated promptly. However, the changes that occur physiologically and behaviourally in the days and weeks preceding an attack are not always recognised, highlighting a potential role for technology. The aim of this study 'DIGIPREDICT' is to identify early digital markers of asthma attacks using sensors embedded in smart devices including watches and inhalers, and leverage health and environmental datasets and artificial intelligence, to develop a risk prediction model to provide an early, personalised warning of asthma attacks. METHODS AND ANALYSIS: A prospective sample of 300 people, 12 years or older, with a history of a moderate or severe asthma attack in the last 12 months will be recruited in New Zealand. Each participant will be given a smart watch (to assess physiological measures such as heart and respiratory rate), peak flow meter, smart inhaler (to assess adherence and inhalation) and a cough monitoring application to use regularly over 6 months with fortnightly questionnaires on asthma control and well-being. Data on sociodemographics, asthma control, lung function, dietary intake, medical history and technology acceptance will be collected at baseline and at 6 months. Asthma attacks will be measured by self-report and confirmed with clinical records. The collected data, along with environmental data on weather and air quality, will be analysed using machine learning to develop a risk prediction model for asthma attacks. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the New Zealand Health and Disability Ethics Committee (2023 FULL 13541). Enrolment began in August 2023. Results will be presented at local, national and international meetings, including dissemination via community groups, and submission for publication to peer-reviewed journals. TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trials Registry ACTRN12623000764639; Australian New Zealand Clinical Trials Registry.
dc.identifier.citationBMJ Open Respiratory Research, ISSN: 2052-4439 (Print); 2052-4439 (Online), BMJ Publishing Group, 11(1), e002275-. doi: 10.1136/bmjresp-2023-002275
dc.identifier.doi10.1136/bmjresp-2023-002275
dc.identifier.issn2052-4439
dc.identifier.issn2052-4439
dc.identifier.urihttp://hdl.handle.net/10292/17604
dc.languageeng
dc.publisherBMJ Publishing Group
dc.relation.urihttps://bmjopenrespres.bmj.com/content/11/1/e002275
dc.rights© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
dc.rights.accessrightsOpenAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectAsthma
dc.subjectClinical Epidemiology
dc.subjectInhaler devices
dc.subjectSurveys and Questionnaires
dc.subjectTelemedicine
dc.subjectAsthma
dc.subjectClinical Epidemiology
dc.subjectInhaler devices
dc.subjectSurveys and Questionnaires
dc.subjectTelemedicine
dc.subject32 Biomedical and Clinical Sciences
dc.subject3201 Cardiovascular Medicine and Haematology
dc.subject3202 Clinical Sciences
dc.subjectLung
dc.subjectAsthma
dc.subjectRespiratory
dc.subject3 Good Health and Well Being
dc.subject3201 Cardiovascular medicine and haematology
dc.subject3202 Clinical sciences
dc.subject.meshAdolescent
dc.subject.meshAdult
dc.subject.meshArtificial Intelligence
dc.subject.meshAsthma
dc.subject.meshChild
dc.subject.meshFemale
dc.subject.meshHumans
dc.subject.meshMale
dc.subject.meshNebulizers and Vaporizers
dc.subject.meshNew Zealand
dc.subject.meshObservational Studies as Topic
dc.subject.meshProspective Studies
dc.subject.meshHumans
dc.subject.meshAsthma
dc.subject.meshArtificial Intelligence
dc.subject.meshProspective Studies
dc.subject.meshNew Zealand
dc.subject.meshMale
dc.subject.meshAdult
dc.subject.meshFemale
dc.subject.meshChild
dc.subject.meshObservational Studies as Topic
dc.subject.meshNebulizers and Vaporizers
dc.subject.meshAdolescent
dc.subject.meshHumans
dc.subject.meshAsthma
dc.subject.meshProspective Studies
dc.subject.meshNebulizers and Vaporizers
dc.subject.meshArtificial Intelligence
dc.subject.meshAdolescent
dc.subject.meshAdult
dc.subject.meshChild
dc.subject.meshNew Zealand
dc.subject.meshFemale
dc.subject.meshMale
dc.subject.meshObservational Studies as Topic
dc.titleDIGIPREDICT: Physiological, Behavioural and Environmental Predictors of Asthma Attacks-A Prospective Observational Study Using Digital Markers and Artificial Intelligence - Study Protocol
dc.typeJournal Article
pubs.elements-id554146
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