Mario Castro, Merrill Zavod, Annika Rutgersson, Magnus Jörntén-Karlsson, Bhaskar Dutta, Lynn Hagger
{"title":"iPREDICT:确定哮喘触发因素的特征并选择数字技术来预测疾病控制的变化","authors":"Mario Castro, Merrill Zavod, Annika Rutgersson, Magnus Jörntén-Karlsson, Bhaskar Dutta, Lynn Hagger","doi":"10.2147/jaa.s458618","DOIUrl":null,"url":null,"abstract":"<strong>Purpose:</strong> The iPREDICT program aimed to develop an integrated digital health solution capable of continuous data streaming, predicting changes in asthma control, and enabling early intervention.<br/><strong>Patients and Methods:</strong> As part of the iPREDICT program, asthma triggers were characterized by surveying 221 patients (aged ≥ 18 years) with self-reported asthma for a risk–benefit analysis of parameters predictive of changes in disease control. Seventeen healthy volunteers (age 25– 65 years) tested 13 devices to measure these parameters and assessed their usability attributes.<br/><strong>Results:</strong> Patients identified irritants such as chemicals, allergens, weather changes, and physical activity as triggers that were the most relevant to deteriorating asthma control. Device testing in healthy volunteers revealed variable data formats/units and quality issues, such as missing data and low signal-to-noise ratio. Based on user preference and data capture validity, a spirometer, vital sign monitor, and sleep monitor formed the iPREDICT integrated system for continuous data streaming to develop a personalized/predictive algorithm for asthma control.<br/><strong>Conclusion:</strong> These findings emphasize the need to systematically compare devices based on several parameters, including usability and data quality, to develop integrated digital technology programs for asthma care.<br/><br/><strong>Keywords:</strong> asthma, devices, digital, predictive algorithm, sensors<br/>","PeriodicalId":15079,"journal":{"name":"Journal of Asthma and Allergy","volume":"19 1","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"iPREDICT: Characterization of Asthma Triggers and Selection of Digital Technology to Predict Changes in Disease Control\",\"authors\":\"Mario Castro, Merrill Zavod, Annika Rutgersson, Magnus Jörntén-Karlsson, Bhaskar Dutta, Lynn Hagger\",\"doi\":\"10.2147/jaa.s458618\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Purpose:</strong> The iPREDICT program aimed to develop an integrated digital health solution capable of continuous data streaming, predicting changes in asthma control, and enabling early intervention.<br/><strong>Patients and Methods:</strong> As part of the iPREDICT program, asthma triggers were characterized by surveying 221 patients (aged ≥ 18 years) with self-reported asthma for a risk–benefit analysis of parameters predictive of changes in disease control. Seventeen healthy volunteers (age 25– 65 years) tested 13 devices to measure these parameters and assessed their usability attributes.<br/><strong>Results:</strong> Patients identified irritants such as chemicals, allergens, weather changes, and physical activity as triggers that were the most relevant to deteriorating asthma control. Device testing in healthy volunteers revealed variable data formats/units and quality issues, such as missing data and low signal-to-noise ratio. Based on user preference and data capture validity, a spirometer, vital sign monitor, and sleep monitor formed the iPREDICT integrated system for continuous data streaming to develop a personalized/predictive algorithm for asthma control.<br/><strong>Conclusion:</strong> These findings emphasize the need to systematically compare devices based on several parameters, including usability and data quality, to develop integrated digital technology programs for asthma care.<br/><br/><strong>Keywords:</strong> asthma, devices, digital, predictive algorithm, sensors<br/>\",\"PeriodicalId\":15079,\"journal\":{\"name\":\"Journal of Asthma and Allergy\",\"volume\":\"19 1\",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Asthma and Allergy\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2147/jaa.s458618\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ALLERGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Asthma and Allergy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/jaa.s458618","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ALLERGY","Score":null,"Total":0}
iPREDICT: Characterization of Asthma Triggers and Selection of Digital Technology to Predict Changes in Disease Control
Purpose: The iPREDICT program aimed to develop an integrated digital health solution capable of continuous data streaming, predicting changes in asthma control, and enabling early intervention. Patients and Methods: As part of the iPREDICT program, asthma triggers were characterized by surveying 221 patients (aged ≥ 18 years) with self-reported asthma for a risk–benefit analysis of parameters predictive of changes in disease control. Seventeen healthy volunteers (age 25– 65 years) tested 13 devices to measure these parameters and assessed their usability attributes. Results: Patients identified irritants such as chemicals, allergens, weather changes, and physical activity as triggers that were the most relevant to deteriorating asthma control. Device testing in healthy volunteers revealed variable data formats/units and quality issues, such as missing data and low signal-to-noise ratio. Based on user preference and data capture validity, a spirometer, vital sign monitor, and sleep monitor formed the iPREDICT integrated system for continuous data streaming to develop a personalized/predictive algorithm for asthma control. Conclusion: These findings emphasize the need to systematically compare devices based on several parameters, including usability and data quality, to develop integrated digital technology programs for asthma care.
期刊介绍:
An international, peer-reviewed journal publishing original research, reports, editorials and commentaries on the following topics: Asthma; Pulmonary physiology; Asthma related clinical health; Clinical immunology and the immunological basis of disease; Pharmacological interventions and new therapies.
Although the main focus of the journal will be to publish research and clinical results in humans, preclinical, animal and in vitro studies will be published where they shed light on disease processes and potential new therapies.