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AI may predict lung decline in cystic fibrosis kids using muscle and balance data

NCT ID NCT07770854

Knowledge-focused Sponsor: Gazi University Source: ClinicalTrials.gov ↗

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Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed This study
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Aug 18, 2026 · Last updated Aug 19, 2026 · Updated 1 time

Summary

This study explores whether machine learning can predict lung function in children with cystic fibrosis using previously collected data on muscle oxygenation, postural balance, and other clinical markers. Researchers will analyze archived spirometry, exercise, and quality-of-life data from 31 children aged 6-18. The goal is to see if these non-invasive measures can help estimate key lung function indicators like FEV1 and FVC. No new tests or interventions are involved; it's a data-only analysis.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

What this could lead to
If successful, this could lead to better, non-invasive ways to monitor lung health in children with cystic fibrosis, potentially improving early detection and management.
What could go wrong
This is a small, retrospective analysis of existing data, so findings may not generalize. It does not test a new treatment, and machine learning predictions may not translate into clinical practice.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

31 people

The number who actually took part.

Started

Jan 2021

Finished

Mar 2025

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

The study population will consist of archived records from children aged 6 to 18 years with cystic fibrosis who were referred by the Division of Pediatric Pulmonology, Gazi University Faculty of Medicine, and evaluated at the Cardiopulmonary Rehabilitation Unit, Department of Physiotherapy and Rehabilitation, Gazi University Faculty of Health Sciences, between April 2021 and September 2022. Only records meeting the prespecified eligibility criteria and containing the variables required for the principal analyses will be included. No new recruitment or participant contact will occur.

Ages

6 to 18 years

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * Age 6 to 18 years at the time of the source assessment * Diagnosis of cystic fibrosis according to the criteria specified in the Cystic Fibrosis Foundation consensus report * Clinically stable at the time of the source assessment * Receiving standard medical treatment * Written informed consent/assent from the participant and parent or legal guardian for participation in the source study * Availability of archived data for the principal variables required for the present analysis Exclusion Criteria: * Diagnosed visual, hearing, vestibular, or neurological disorder that could affect balance * Hospitalization within the month preceding the source assessment * Participation in a structured exercise training program within the 3 months preceding the source assessment * History of COVID-19 or tobacco use * Orthopedic disorder affecting mobility or history of musculoskeletal surgery * Acute pulmonary exacerbation at the time of assessment * Allergic bronchopulmonary aspergillosis * History of lung or liver transplantation * Systemic corticosteroid use * Pulmonary hypertension or cardiovascular instability * Missing archived records required for the principal analyses

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Conditions

The condition(s) this trial relates to.

cystic fibrosis Motor Activity

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Cystic fibrosis (CF)

Contacts and locations

Locations

  • Gazi University Faculty of Health Sciences Department of Cardiopulmonary Physiotherapy and Rehabilitation, Ankara, Çankaya 06490

    Ankara, Ankara, 06560, Turkey (Türkiye)

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