Den här översättningen är inte klar ännu. Den här sidan är just nu på engelska.

Gå till den engelska sidan

Cure My Disease

Don't miss your cure!

 Log in / Sign up

Biking for science: could AI predict blood sugar spikes during exercise?

NCT ID NCT07286019

Knowledge-focused Sponsor: Universitat de Girona Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

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 This study
Running, but no longer taking on new participants.
Completed
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study asks 29 adults with type 1 diabetes to complete a 75 km gravel bike ride while wearing a continuous glucose monitor and providing saliva and urine samples. Researchers want to collect detailed data to help build artificial intelligence models that can predict how exercise affects blood sugar. The study does not test any drug or treatment—it focuses on gathering information for future research.

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 AI tools that help people with type 1 diabetes manage their glucose during exercise.
What could go wrong
This is a small, early-stage data collection study with only 29 participants. It does not test any treatment, so direct benefits are not expected.

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.

Phase

Not a phased trial

Phase numbers describe drug development. The registry uses this when they do not apply, as it does for trials of devices, procedures or behaviour changes, and for observational studies.

Participants

29 people

The number who actually took part.

Started

Nov 2025

Expected to finish

Dec 2025

An estimate. End dates often move.

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.

Ages

18 to 60 years

Sex

Anyone

Healthy volunteers

Accepted

You do not need to have the condition being studied to take part.

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: * Type 1 diabetes for \> 5 years. * Age between 18-60 years. * HbA1c ≤ 8.5%. * Body mass index between 18 and 30 kg/m². * Physically active (≥ 4 hours/week of exercise). * Laboratory data and EKG without alterations of the last 12 months. * Valid Type 2 sports medical examination, which includes a monitored stress test with continuous ECG and blood pressure monitoring, as well as an official medical certificate confirming fitness to participate in this study. * Experience using CGM sensors and be used to self-monitor blood glucose and carbohydrate counting. Exclusion Criteria: * Unable to ride gravel bikes. * Unable to use clipless pedals. * Pregnancy and breastfeeding. * Hypoglycemia unawareness (Clarke Test \> 3). * Severe hypoglycemia in the previous 6 monhts. * Progressive fatal disease. * History of drug or alcohol abuse. * Impaired liver function. * Clinically relevant microvascular complications (macroalbuminuria, pre-proliferative and proliferative retinopathy), cardiovascular, hepatic, neurological, endocrine or other systemic disease, apart from T1D. * Mental conditions that prevent the subject from understanding the nature, purpose and possible consequences of the study. * Using an experimental drug or device during the prior 30 days. Inclusion (healthy control group): adults 18-60 years without diabetes and physically active (≥ 4 hours/week of exercise) who can provide pre/post saliva and uringe samples for omics analyses.

Get updates

Get notified about this study

Sign up to get updates when this study changes or when new studies for Type 1 diabetes (T1D) are added.

Vår säkerhetsrekommendation!

Genom att skicka in godkänner du våra Användarvillkor

Conditions

The condition(s) this trial relates to.

Insulin Resistance Motor Activity type 1 diabetes mellitus

As listed by the trial registrant

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

Type 1 diabetes (T1D)

Contacts and locations

Locations

  • Modeling & Intelligent Control Engineering Laboraotry (Universitat de Girona)

    Girona, Girona, 17003, Spain

More trials for these conditions

Other studies related to the condition(s) this trial covers.