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AI could spot rare fabry disease from hospital records

NCT ID NCT05106764

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
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study aims to develop a computer algorithm that can detect Fabry disease earlier by analyzing hospital electronic health records. Researchers will look at data from the past 10 years to see if they can identify patients with Fabry disease using a ranking system. No drugs or devices are being tested. The goal is to create a tool that helps doctors diagnose this rare condition sooner.

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 a tool that helps doctors spot Fabry disease earlier, potentially improving patient outcomes.
What could go wrong
This is a retrospective data analysis, not a clinical trial testing a treatment. The algorithm may not work well in other hospitals or real-world settings.

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

50 people

The number who actually took part.

Started

Nov 2023

Finished

Dec 2025

Lead sponsor

A company

The lead sponsor is a pharmaceutical, biotech, or medical-device company.

Who can take part

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

Who is studied

Data from all in-patient or out- patient datasets of the participating hospital in the last 10 years will be used to test the forecasting power of the algorithm.

Ages

Children (under 18), adults (18 to 64) and older adults (65 and over)

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: * In-patient or out-patient datasets of the participating hospital in the last 10 years * Participants at any age Positive controls: a subset of all participant hospital records that includes the participants with confirmed FD.

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Conditions

The condition(s) this trial relates to.

As listed by the trial registrant

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

Contacts and locations

Locations

  • Universitätsklinikum Erlangen Kinder- und Jugendklinik

    Erlangen, 91054, Germany

  • Universitätsklinikum Erlangen Neurologische Klinik

    Erlangen, 91054, Germany

  • Universitätsklinikum Giessen

    Giessen, 35389, Germany

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