DIGIPREDICT: physiological, behavioural and environmental predictors of asthma attacks-a prospective observational study using digital markers and artificial intelligence-study protocol.

IF 3.6 3区医学 Q1 RESPIRATORY SYSTEM BMJ Open Respiratory Research Pub Date : 2024-05-22 DOI:10.1136/bmjresp-2023-002275

Amy Hai Yan Chan, Braden Te Ao, Christina Baggott, Alana Cavadino, Amber A Eikholt, Matire Harwood, Joanna Hikaka, Dianna Gibbs, Mariana Hudson, Farhaan Mirza, Muhammed Asif Naeem, Ruth Semprini, Catherina L Chang, Kevin C H Tsang, Syed Ahmar Shah, Aron Jeremiah, Binu Nisal Abeysinghe, Rajshri Roy, Clare Wall, Lisa Wood, Stuart Dalziel, Hilary Pinnock, Job F M van Boven, Partha Roop, Jeff Harrison

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Abstract

Introduction: 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.

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DIGIPREDICT：哮喘发作的生理、行为和环境预测因素--一项使用数字标记和人工智能的前瞻性观察研究--研究方案。

导言：哮喘发作是发病和死亡的主要原因，但如果及时发现和治疗，大多数哮喘是可以预防的。然而，在哮喘发作前几天和几周内发生的生理和行为变化并不总是被人们所认识，这就凸显了技术的潜在作用。这项名为 "DIGIPREDICT "的研究旨在利用嵌入在智能设备（包括手表和吸入器）中的传感器来识别哮喘发作的早期数字标记，并利用健康和环境数据集以及人工智能来开发一个风险预测模型，以提供哮喘发作的早期个性化预警：将在新西兰招募 300 名 12 岁或以上、在过去 12 个月中有中度或重度哮喘发作史的人作为前瞻性样本。每位参与者将获得智能手表（用于评估心率和呼吸频率等生理指标）、峰值流量计、智能吸入器（用于评估依从性和吸入情况）和咳嗽监测应用程序，在 6 个月内定期使用，每两周进行一次有关哮喘控制和健康状况的问卷调查。将在基线和 6 个月时收集有关社会人口统计学、哮喘控制、肺功能、饮食摄入、病史和技术接受度的数据。哮喘发作情况将通过自我报告进行测量，并通过临床记录进行确认。收集到的数据以及天气和空气质量等环境数据将通过机器学习进行分析，以建立哮喘发作风险预测模型：该研究已获得新西兰健康与残疾伦理委员会（New Zealand Health and Disability Ethics Committee）的伦理批准（2023 FULL 13541）。注册工作于 2023 年 8 月开始。研究结果将在当地、国内和国际会议上公布，包括通过社区团体进行传播，并提交给同行评审期刊发表：澳大利亚新西兰临床试验注册中心 ACTRN12623000764639；澳大利亚新西兰临床试验注册中心 ACTRN12623000764639。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

BMJ Open Respiratory Research RESPIRATORY SYSTEM-

CiteScore

6.60

自引率

2.40%

发文量

审稿时长

12 weeks

期刊介绍： BMJ Open Respiratory Research is a peer-reviewed, open access journal publishing respiratory and critical care medicine. It is the sister journal to Thorax and co-owned by the British Thoracic Society and BMJ. The journal focuses on robustness of methodology and scientific rigour with less emphasis on novelty or perceived impact. BMJ Open Respiratory Research operates a rapid review process, with continuous publication online, ensuring timely, up-to-date research is available worldwide. The journal publishes review articles and all research study types: Basic science including laboratory based experiments and animal models, Pilot studies or proof of concept, Observational studies, Study protocols, Registries, Clinical trials from phase I to multicentre randomised clinical trials, Systematic reviews and meta-analyses.