AI-Assisted Remote Asthma Management for Childhood Asthma

Overseen By Lynnea Myers, PhD, PhD, RN

Age: < 18

Sex: Any

Trial Phase: Academic

Sponsor: Mayo Clinic

Must be taking: Inhaled corticosteroids

Disqualifiers: Cystic fibrosis, Pregnancy, Others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

Duration: 6 months

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial investigates whether children with asthma can manage their condition at home using an AI tool called the Asthma-Guidance and Prediction System, combined with a home device called AsthmaTuner. It compares the effectiveness of this approach to the usual clinic visits for asthma care. The trial includes two main groups: one using the AI tool and device alongside standard care, and a control group receiving only standard care. Children aged 6-17 with active asthma, whose caregivers can participate regularly, might be suitable candidates for this trial. As an unphased trial, this study provides a unique opportunity to contribute to innovative asthma management research.

Will I have to stop taking my current medications?

The trial protocol does not specify whether you need to stop taking your current medications. However, it mentions that participants should have active asthma and may be on asthma control or rescue medication.

What prior data suggests that this AI-assisted remote asthma management method is safe for children?

Research shows that the Asthma-Guidance and Prediction System (A-GPS) aids doctors by predicting asthma flare-ups. It reduces decision-making time by 80%, enhancing asthma management. Studies have not identified major safety issues.

The AsthmaTuner assists individuals in managing asthma at home. Studies have evaluated its effectiveness in improving asthma control and quality of life. While these studies do not highlight specific safety concerns, users have managed their condition with the tool, suggesting it is well-tolerated.

Both tools aim to manage asthma, a common condition in children. No specific data indicates safety problems with either tool. Since this trial phase is "Not Applicable," these tools are likely considered safe for everyday use. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the Asthma-Guidance and Prediction System (A-GPS) with AsthmaTuner because it offers a new way to manage childhood asthma remotely. Unlike traditional treatments, which often rely on regular in-person checkups and medication adjustments, this system uses AI to predict and guide asthma management, potentially leading to more personalized and timely interventions. By integrating technology into asthma care, this approach aims to empower patients and caregivers with real-time insights, making asthma management more proactive and tailored to individual needs.

What evidence suggests that the AI-assisted remote asthma management system could be effective for childhood asthma?

This trial will evaluate the integration of the Asthma-Guidance and Prediction System (A-GPS) and AsthmaTuner into asthma care. Research has shown that A-GPS uses artificial intelligence to predict asthma flare-ups by analyzing data from electronic health records to identify potential problems before they occur. Meanwhile, AsthmaTuner, a digital app, helps manage asthma by tracking symptoms and treatments. Studies have found that AsthmaTuner can improve asthma control and assist patients in making quicker decisions about their care. Together, these tools aim to make managing asthma more effective and proactive. Participants in the intervention groups will have these tools integrated into their standard care, while control groups will receive standard care without these tools. ^{1 2 3 4 6}

Who Is on the Research Team?

Young Juhn, MD, MPH

Principal Investigator

Mayo Clinic

Are You a Good Fit for This Trial?

This trial is for kids aged 6-17 with asthma and their caregivers. Kids must have had an asthma check-up in the last 3 months, be able to follow up every 3-6 months, and not be on certain other treatments or studies. Caregivers need to help out and both must read/write English.

Inclusion Criteria

I am a child with asthma and have a caregiver willing to join me in my treatment and follow-ups.

My last asthma check-up was over 3 months ago.

I am between 7-17 years old and can give consent, or my caregiver can.

Exclusion Criteria

My child has symptoms that may not be just asthma, like trouble breathing during exercise or other specific lung issues.

I am a child and not pregnant.

I am a child who does not meet the specified eligibility criteria.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants use the Asthma-Guidance and Prediction System (A-GPS) with AsthmaTuner for remote asthma management

6 months

Remote management with potential on-site visits

Follow-up

Participants are monitored for safety and effectiveness after treatment

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

• Asthma-Guidance and Prediction System
• AsthmaTuner

Trial Overview

The study tests if managing asthma at home using a mobile device (AsthmaTuner) and AI system (Asthma-Guidance) is as good as usual care that happens in clinics. It's about making treatment easier by staying at home.

How Is the Trial Designed?

Group I: Pediatric Asthma Intervention Group Experimental Treatment 2 Interventions

Along with clinical standard of care for asthma, subjects will have Asthma-Guidance and Prediction System (A-GPS) with AsthmaTuner (AT) integrated into care.

Group II: Clinician Intervention Group Experimental Treatment 2 Interventions

Clinicians will integrate Asthma-Guidance and Prediction System (A-GPS) with AsthmaTuner (AT) into clinical standard of care for asthma.

Group III: Asthma Care Coordinator Intervention Group Experimental Treatment 2 Interventions

Asthma Care Coordinators will integrate Asthma-Guidance and Prediction System (A-GPS) with AsthmaTuner (AT) into clinical standard of care for asthma.

Group IV: Pediatric Asthma Control Group Active Control 1 Intervention

Subjects will receive clinical standard of care for asthma.

Group V: Clinician Control Group Active Control 1 Intervention

Clinicians will provide clinical standard of care for pediatric asthma patients.

Group VI: Asthma Care Coordinator Control Group Active Control 1 Intervention

Asthma Care Coordinators will provide clinical standard of care for pediatric asthma patients.

Who Is Running the Clinical Trial?

Mayo Clinic

Lead Sponsor

Trials

3,427

Recruited

3,221,000+

Published Research Related to This Trial

The modified asthma control measure (ACM) effectively identifies uncontrolled asthma with a high sensitivity of 0.99 and a specificity of 0.65 in a study of 498 subjects.

This patient-reported outcome measure (PROM) can differentiate between well-controlled and uncontrolled asthma and is suitable for use in digital remote monitoring without requiring a license.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Toward an asthma patient-reported outcome measure for use in digital remote monitoring. Rudin, RS., Qureshi, N., Foer, D., et al.[2022]

The study introduces a cloud-based wearable IoT aldehyde sensor system designed to monitor environmental factors that can trigger asthma, potentially improving asthma management.

This innovative sensor system allows for real-time data collection and analysis, which can help researchers and patients better understand and manage asthma triggers in their daily environments.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A Wearable IoT Aldehyde Sensor for Pediatric Asthma Research and Management. Li, B., Dong, Q., Downen, RS., et al.[2020]

The study involved 1306 quality control tests of an electronic monitoring device for asthma inhalers, showing a high reliability rate of 84% for pre-issue tests and 87% for return tests, although some devices had issues with under-recording.

Children using the device with reminder features reported significantly higher acceptability scores compared to those without reminders, with over 90% finding the device easy to use, indicating strong potential for improving asthma management in this age group.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Electronic adherence monitoring device performance and patient acceptability: a randomized control trial. Chan, AHY., Stewart, AW., Harrison, J., et al.[2018]

Citations

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pmc.ncbi.nlm.nih.gov

pmc.ncbi.nlm.nih.gov/articles/PMC8328289/

Artificial intelligence-assisted clinical decision support for ...

We developed the Asthma-Guidance and Prediction System (A-GPS), an AI-assisted CDS tool providing 1) a high-level summary of relevant clinical ...

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mayo.edu

mayo.edu/research/clinical-trials/cls-20260171

A Study to Develop and Implement the Asthma-Guidance ...

The purpose of this study is to test the use and effectiveness of the asthma-Guidance and Prediction System (a-GPS) within the Asthma Management Program, a ...

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jaci-global.org

jaci-global.org/article/S2772-8293(25)00030-X/fulltext

AI model for predicting asthma prognosis in children

We aimed to develop artificial intelligence (AI) models using various clinical variables extracted from EHRs to predict childhood asthma prognosis.

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pmc.ncbi.nlm.nih.gov

pmc.ncbi.nlm.nih.gov/articles/PMC9285150/

A Technical Performance Study and Proposed Systematic and ...

In this study, we propose a machine learning-based clinical decision support (CDS) system focused on pediatric asthma care to alleviate some of this burden.

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mayoclinic.org

mayoclinic.org/medical-professionals/pediatrics/news/technology-ai-advancements-in-pediatric-asthma-care/mac-20534885

Technology, AI advancements in pediatric asthma care

The A-GPS tool also includes a machine learning algorithm to predict future risk of asthma exacerbation based on the collected information from ...

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researchgate.net

researchgate.net/publication/339469125_Asthma-Guidance_and_Prediction_System_a-GPS_As_a_Precision_Asthma_Care_Tool

Asthma-Guidance and Prediction System (a-GPS) As ...

Our recent study showed that automated chart review via the NLP system reduced clinicians' time for making their clinical decision by about 80%.