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Naseem R, Howe N, Williams CJ, Pretorius S, Green K. What diagnostic tests are available for respiratory infections or pulmonary exacerbations in cystic fibrosis: A scoping literature review. Respir Investig 2024; 62:817-831. [PMID: 39024929 DOI: 10.1016/j.resinv.2024.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Revised: 07/02/2024] [Accepted: 07/06/2024] [Indexed: 07/20/2024]
Abstract
A scoping review methodological framework formed the basis of this review. A search of two electronic databases captured relevant literature published from 2013. 1184 articles were screened, 200 of which met inclusion criteria. Included studies were categorised as tests for either respiratory infections OR pulmonary exacerbations. Data were extracted to ascertain test type, sample type, and indication of use for each test type. For infection, culture is the most common testing method, particularly for bacterial infections, whereas PCR is utilised more for the diagnosis of viral infections. Spirometry tests, indicating lung function, facilitate respiratory infection diagnoses. There is no clear definition of what an exacerbation is in persons with CF. A clinical checklist with risk criteria can determine if a patient is experiencing an exacerbation event, however the diagnosis is clinician-led and will vary between individuals. Fuchs criteria are one of the most frequently used tests to assess signs and symptoms of exacerbation in persons with CF. This scoping review highlights the development of home monitoring tests to facilitate earlier and easier diagnoses, and the identification of novel biomarkers for indication of infections/exacerbations as areas of current research and development. Research is particularly prevalent regarding exhaled breath condensate and volatile organic compounds as an alternative sampling/biomarker respectively for infection diagnosis. Whilst there are a wide range of tests available for diagnosing respiratory infections and/or exacerbations, these are typically used clinically in combination to ensure a rapid, accurate diagnosis which will ultimately benefit both the patient and clinician.
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Affiliation(s)
- Raasti Naseem
- NIHR Newcastle HealthTech Research Centre in Diagnostic and Technology Evaluation, Fourth floor William Leech Building, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom
| | - Nicola Howe
- NIHR Newcastle HealthTech Research Centre in Diagnostic and Technology Evaluation, Fourth floor William Leech Building, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom.
| | - Cameron J Williams
- NIHR Newcastle HealthTech Research Centre in Diagnostic and Technology Evaluation, Fourth floor William Leech Building, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom
| | - Sara Pretorius
- NIHR Newcastle HealthTech Research Centre in Diagnostic and Technology Evaluation, Fourth floor William Leech Building, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom
| | - Kile Green
- NIHR Newcastle HealthTech Research Centre in Diagnostic and Technology Evaluation, Fourth floor William Leech Building, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom
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Hoppe JE, Sjoberg J, Hong G, Poch K, Zemanick ET, Thee S, Edmondson C, Patel D, Sathe M, Borowitz D, Putman MS, Lechtzin N, Riekert KA, Basile M, Goss CH, Jarosz ME, Rosenfeld M. Remote endpoints for clinical trials in cystic fibrosis: Report from the U.S. CF foundation remote endpoints task force. J Cyst Fibros 2024; 23:725-733. [PMID: 38429150 DOI: 10.1016/j.jcf.2024.02.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 01/18/2024] [Accepted: 02/19/2024] [Indexed: 03/03/2024]
Abstract
The COVID-19 pandemic necessitated a rapid shift in clinical research to perform virtual visits and remote endpoint assessments, providing a key opportunity to optimize the use of remote endpoints for clinical trials in cystic fibrosis. The use of remote endpoints could allow more diverse participation in clinical trials while minimizing participant burden but must be robustly evaluated to ensure adequate performance and feasibility. In response, the Cystic Fibrosis Foundation convened the Remote Endpoint Task Force (Supplemental Table 1), a multidisciplinary group of CF researchers with remote endpoint expertise and community members tasked to better understand the current and future use of remote endpoints for clinical research. Here, we describe the current use of remote endpoints in CF clinical research, address key unanswered questions regarding their use and feasibility, and discuss the next steps to determine clinical trial readiness.
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Affiliation(s)
- Jordana E Hoppe
- Department of Pediatrics, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora CO, USA.
| | | | - Gina Hong
- Department of Medicine, Division of Pulmonary, Allergy and Critical Care, Perelman School of Medicine at the University of Pennsylvania, Philadelphia Pennsylvania, USA
| | - Katie Poch
- Department of Medicine, National Jewish Health, Denver CO, USA
| | - Edith T Zemanick
- Department of Pediatrics, University of Colorado School of Medicine and Children's Hospital Colorado, Aurora CO, USA
| | - Stephanie Thee
- Department of Pediatric Respiratory Medicine, Immunology and Critical Care Medicine and Cystic Fibrosis Center, Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Claire Edmondson
- Department of Paediatric Respiratory Medicine, Great Ormond Street Hospital, London WC1N3JH, USA
| | - Dhiren Patel
- Division of Pediatric Gastroenterology, Hepatology and Nutrition, Cardinal Glennon Children's Medical Center, Saint Louis University School of Medicine, St. Louis MO, USA
| | - Meghana Sathe
- Pediatric Gastroenterology and Nutrition, University of Texas Southwestern/Children's Health, Dallas Texas, USA
| | - Drucy Borowitz
- Department of Pediatrics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo New York, USA
| | - Melissa S Putman
- Division of Pediatric Endocrinology, Boston Children's Hospital, Boston MA, USA
| | - Noah Lechtzin
- Division of Pulmonary and Critical Care, Johns Hopkins University School of Medicine, Baltimore Maryland, USA
| | - Kristin A Riekert
- Division of Pulmonary and Critical Care, Johns Hopkins University School of Medicine, Baltimore Maryland, USA
| | - Melissa Basile
- Feinstein Institutes for Medical Research, Northwell Health, Manhasset NY, USA
| | - Christopher H Goss
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of Washington Medical Center, Seattle Washington, USA; Department of Pediatrics, University of Washington School of Medicine and Seattle Children's Research Institute, Seattle Washington, USA
| | | | - Margaret Rosenfeld
- Department of Pediatrics, University of Washington School of Medicine and Seattle Children's Research Institute, Seattle Washington, USA
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Chan AHY, Te Ao B, Baggott C, Cavadino A, Eikholt AA, Harwood M, Hikaka J, Gibbs D, Hudson M, Mirza F, Naeem MA, Semprini R, Chang CL, Tsang KCH, Shah SA, Jeremiah A, Abeysinghe BN, Roy R, Wall C, Wood L, Dalziel S, Pinnock H, van Boven JFM, Roop P, Harrison J. DIGIPREDICT: physiological, behavioural and environmental predictors of asthma attacks-a prospective observational study using digital markers and artificial intelligence-study protocol. BMJ Open Respir Res 2024; 11:e002275. [PMID: 38777583 PMCID: PMC11116853 DOI: 10.1136/bmjresp-2023-002275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 04/11/2024] [Indexed: 05/25/2024] Open
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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Affiliation(s)
- Amy Hai Yan Chan
- School of Pharmacy, The University of Auckland Faculty of Medical and Health Sciences, Auckland, Region, New Zealand
| | - Braden Te Ao
- School of Population Health, University of Auckland, Auckland, New Zealand
| | - Christina Baggott
- Department of Respiratory Medicine and Respiratory research unit, Waikato Hospital, Hamilton, New Zealand
| | - Alana Cavadino
- School of Population Health, University of Auckland, Auckland, New Zealand
| | - Amber A Eikholt
- University Medical Centre Groningen, Groningen Research Institute for Asthma and COPD, Groningen, Netherlands
- Medication Adherence Expertise Center of the northern Netherlands (MAECON), Groningen, Netherlands
| | - Matire Harwood
- School of Population Health, University of Auckland, Auckland, New Zealand
| | - Joanna Hikaka
- Te Kupenga Hauora Māori, University of Auckland, Auckland, New Zealand
| | - Dianna Gibbs
- Pinnacle Midlands Health Network, Hamilton, New Zealand
| | - Mariana Hudson
- School of Pharmacy, The University of Auckland Faculty of Medical and Health Sciences, Auckland, Region, New Zealand
| | - Farhaan Mirza
- Department of IT and Software Engineering, Auckland University of Technology, Auckland, New Zealand
| | - Muhammed Asif Naeem
- Department of IT and Software Engineering, Auckland University of Technology, Auckland, New Zealand
- National University of Computer and Emerging Sciences, Islamabad, Pakistan
| | - Ruth Semprini
- Medical Research Institute of New Zealand, Wellington, New Zealand
| | - Catherina L Chang
- Department of Respiratory Medicine and Respiratory research unit, Waikato Hospital, Hamilton, New Zealand
| | - Kevin C H Tsang
- University College London, London, UK
- The University of Edinburgh Usher Institute of Population Health Sciences and Informatics, Edinburgh, Edinburgh, UK
| | - Syed Ahmar Shah
- The University of Edinburgh Usher Institute of Population Health Sciences and Informatics, Edinburgh, Edinburgh, UK
| | - Aron Jeremiah
- Department of Electrical, Computer and Software Engineering, University of Auckland, Auckland, New Zealand
| | - Binu Nisal Abeysinghe
- Department of Electrical, Computer and Software Engineering, University of Auckland, Auckland, New Zealand
| | - Rajshri Roy
- Department of Nutrition and Dietetics, University of Auckland, Auckland, New Zealand
| | - Clare Wall
- Department of Nutrition and Dietetics, University of Auckland, Auckland, New Zealand
| | - Lisa Wood
- Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, New South Wales, Australia
| | - Stuart Dalziel
- Children's Emergency Department, Starship Children's Hospital, Auckland, New Zealand
| | - Hilary Pinnock
- The University of Edinburgh Usher Institute of Population Health Sciences and Informatics, Edinburgh, Edinburgh, UK
| | - Job F M van Boven
- University Medical Centre Groningen, Groningen Research Institute for Asthma and COPD, Groningen, Netherlands
- Medication Adherence Expertise Center of the northern Netherlands (MAECON), Groningen, Netherlands
| | - Partha Roop
- Department of Electrical, Computer and Software Engineering, University of Auckland, Auckland, New Zealand
| | - Jeff Harrison
- School of Pharmacy, The University of Auckland Faculty of Medical and Health Sciences, Auckland, Region, New Zealand
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Masrour O, Personnic J, Amat F, Abou Taam R, Prevost B, Lezmi G, Gonsard A, Nathan N, Pirojoc A, Delacourt C, Wanin S, Drummond D. Objectives for algorithmic decision-making systems in childhood asthma: Perspectives of children, parents, and physicians. Digit Health 2024; 10:20552076241227285. [PMID: 38389509 PMCID: PMC10883132 DOI: 10.1177/20552076241227285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/28/2023] [Indexed: 02/24/2024] Open
Abstract
Objectives To identify with children, parents and physicians the objectives to be used as parameters for algorithmic decision-making systems (ADMSs) adapting treatments in childhood asthma. Methods We first conducted a qualitative study based on semi-structured interviews to explore the objectives that children aged 8-17 years, their parents, and their physicians seek to achieve when taking/giving/prescribing a treatment for asthma. Following the grounded theory approach, each interview was independently coded by two researchers; reconciled codes were used to assess code frequency, categories were defined, and the main objectives identified. We then conducted a quantitative study based on questionnaires using these objectives to determine how children/parents/physicians ranked these objectives and whether their responses were aligned. Results We interviewed 71 participants (31 children, 30 parents and 10 physicians) in the qualitative study and identified seven objectives associated with treatment uptake and five objectives associated with treatment modalities. We included 291 participants (137 children, 137 parents, and 17 physicians) in the quantitative study. We found little correlation between child, parent, and physician scores for each of the objectives. Each child's asthma history influenced the choice of scores assigned to each objective by the child, parents, and physician. Conclusion The identified objectives are quantifiable and relevant to the management of asthma in the short and long term. They can therefore be incorporated as parameters for future ADMS. Shared decision-making seems essential to achieve consensus among children, parents, and physicians when choosing the weight to assign to each of these objectives.
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Affiliation(s)
- Omar Masrour
- Department of Pediatric Pulmonology and Allergology, University Hospital Necker-Enfants Malades, AP-HP, Paris, France
| | - Johan Personnic
- Department of Pediatrics, University Hospital Ambroise Paré, AP-HP, Paris, France
| | - Flore Amat
- Department of Pediatric Pulmonology and Allergology, University Hospital Robert Debré, AP-HP, Paris, France
| | - Rola Abou Taam
- Department of Pediatric Pulmonology and Allergology, University Hospital Necker-Enfants Malades, AP-HP, Paris, France
| | - Blandine Prevost
- Department of Pediatric Pulmonology, University Hospital Armand Trousseau, AP-HP, Paris, France
| | - Guillaume Lezmi
- Department of Pediatric Pulmonology and Allergology, University Hospital Necker-Enfants Malades, AP-HP, Paris, France
| | - Apolline Gonsard
- Department of Pediatric Pulmonology and Allergology, University Hospital Necker-Enfants Malades, AP-HP, Paris, France
| | - Nadia Nathan
- Department of Pediatric Pulmonology, University Hospital Armand Trousseau, AP-HP, Paris, France
| | | | - Christophe Delacourt
- Department of Pediatric Pulmonology and Allergology, University Hospital Necker-Enfants Malades, AP-HP, Paris, France
- Faculté de Médecine, Université Paris Cité, Paris, France
| | - Stéphanie Wanin
- Department of Pediatric Allergology, University Hospital Armand Trousseau, APHP, Paris, France
| | - David Drummond
- Department of Pediatric Pulmonology and Allergology, University Hospital Necker-Enfants Malades, AP-HP, Paris, France
- Faculté de Médecine, Université Paris Cité, Paris, France
- Inserm UMR 1138, HeKA team, Centre de Recherche des Cordeliers, Paris, France
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Aneni K, Chen CH, Meyer J, Cho YT, Lipton ZC, Kher S, Jiao MG, Gomati de la Vega I, Umutoni FA, McDougal RA, Fiellin LE. Identifying Game-Based Digital Biomarkers of Cognitive Risk for Adolescent Substance Misuse: Protocol for a Proof-of-Concept Study. JMIR Res Protoc 2023; 12:e46990. [PMID: 37995115 DOI: 10.2196/46990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 09/06/2023] [Accepted: 10/03/2023] [Indexed: 11/24/2023] Open
Abstract
BACKGROUND Adolescents at risk for substance misuse are rarely identified early due to existing barriers to screening that include the lack of time and privacy in clinic settings. Games can be used for screening and thus mitigate these barriers. Performance in a game is influenced by cognitive processes such as working memory and inhibitory control. Deficits in these cognitive processes can increase the risk of substance use. Further, substance misuse affects these cognitive processes and may influence game performance, captured by in-game metrics such as reaction time or time for task completion. Digital biomarkers are measures generated from digital tools that explain underlying health processes and can be used to predict, identify, and monitor health outcomes. As such, in-game performance metrics may represent digital biomarkers of cognitive processes that can offer an objective method for assessing underlying risk for substance misuse. OBJECTIVE This is a protocol for a proof-of-concept study to investigate the utility of in-game performance metrics as digital biomarkers of cognitive processes implicated in the development of substance misuse. METHODS This study has 2 aims. In aim 1, using previously collected data from 166 adolescents aged 11-14 years, we extracted in-game performance metrics from a video game and are using machine learning methods to determine whether these metrics predict substance misuse. The extraction of in-game performance metrics was guided by literature review of in-game performance metrics and gameplay guidebooks provided by the game developers. In aim 2, using data from a new sample of 30 adolescents playing the same video game, we will test if metrics identified in aim 1 correlate with cognitive processes. Our hypothesis is that in-game performance metrics that are predictive of substance misuse in aim 1 will correlate with poor cognitive function in our second sample. RESULTS This study was funded by National Institute on Drug Abuse through the Center for Technology and Behavioral Health Pilot Core in May 2022. To date, we have extracted 285 in-game performance metrics. We obtained institutional review board approval on October 11, 2022. Data collection for aim 2 is ongoing and projected to end in February 2024. Currently, we have enrolled 12 participants. Data analysis for aim 2 will begin once data collection is completed. The results from both aims will be reported in a subsequent publication, expected to be published in late 2024. CONCLUSIONS Screening adolescents for substance use is not consistently done due to barriers that include the lack of time. Using games that provide an objective measure to identify adolescents at risk for substance misuse can increase screening rates, early identification, and intervention. The results will inform the utility of in-game performance metrics as digital biomarkers for identifying adolescents at high risk for substance misuse. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/46990.
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Affiliation(s)
- Kammarauche Aneni
- Child Study Center, Yale School of Medicine, New Haven, CT, United States
- Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, United States
| | - Ching-Hua Chen
- Center for Computational Health, IBM Research, Yorktown Heights, NY, United States
| | - Jenny Meyer
- Child Study Center, Yale School of Medicine, New Haven, CT, United States
- Fairfield University, Fairfield, CT, United States
| | - Youngsun T Cho
- Child Study Center, Yale School of Medicine, New Haven, CT, United States
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
| | - Zachary Chase Lipton
- Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburg, PA, United States
| | | | - Megan G Jiao
- McGovern Medical School, UTHealth Houston, Houston, TX, United States
| | | | | | - Robert A McDougal
- Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, United States
- Yale School of Public Health, New Haven, CT, United States
| | - Lynn E Fiellin
- Child Study Center, Yale School of Medicine, New Haven, CT, United States
- Yale School of Public Health, New Haven, CT, United States
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, United States
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Abstract
PURPOSE OF REVIEW We highlight the recent advances in home monitoring of patients with asthma, and show that these advances converge towards the implementation of digital twin systems. RECENT FINDINGS Connected devices for asthma are increasingly numerous, reliable and effective: new electronic monitoring devices extend to nebulizers and spacers, are able to assess the quality of the inhalation technique, and to identify asthma attack triggers when they include a geolocation function; environmental data can be acquired from databases and refined by wearable air quality sensors; smartwatches are better validated. Connected devices are increasingly integrated into global monitoring systems. At the same time, machine learning techniques open up the possibility of using the large amount of data collected to obtain a holistic assessment of asthma patients, and social robots and virtual assistants can help patients in the daily management of their asthma. SUMMARY Advances in the internet of things, machine learning techniques and digital patient support tools for asthma are paving the way for a new era of research on digital twins in asthma.
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Affiliation(s)
- David Drummond
- Department of Pediatric Pulmonology and Allergology, University Hospital Necker-Enfants Malades, AP-HP, Université Paris Cité, Inserm UMR 1138, HeKA team, Centre de Recherche des Cordeliers, Paris, France
| | - Jolt Roukema
- Department of Paediatrics/Paediatric Pulmonology, Radboud University Medical Centre, Amalia Children's Hospital, Nijmegen
| | - Mariëlle Pijnenburg
- Department of Paediatrics/Paediatric Respiratory Medicine and Allergology, Erasmus University Medical Centre - Sophia Children's Hospital, Rotterdam, The Netherlands
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