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AI could predict who struggles after ACL surgery

NCT ID NCT07284771

Knowledge-focused Sponsor: Chinese University of Hong Kong Source: ClinicalTrials.gov ↗

What the study statuses mean

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Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting This study
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
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 uses machine learning to predict how well people recover after ACL surgery. Researchers will measure muscle strength and size, along with other factors, to identify patients who may not respond well to standard rehabilitation. The goal is to create a tool that helps doctors personalize rehab plans. About 182 participants will be followed for one year after surgery.

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 personalized rehab approach that helps more people return to sports safely after ACL surgery.
What could go wrong
This is an observational study, not a treatment trial, so it won't directly improve outcomes. The machine learning model may not work well in other hospitals or patient groups.

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

About 182 people

The number the study aims to enrol. It can still change while the study runs.

Expected to start

Apr 2026

An estimate. Start dates often move.

Expected to finish

Aug 2028

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.

Who is studied

All the ACLR patients will be recruited at the Orthopaedics Outpatient Clinic at Prince of Wales Hospital.

Ages

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

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: * Unilateral ACL injury and plan for ACLR * Commit the post-operation physiotherapy in Prince of Wales Hospital Exclusion Criteria: * Preoperative radiographic signs of arthritis * Patient non-compliance to the rehabilitation program

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As listed by the trial registrant

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

Machine learning

How to take part

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  1. The official record

    ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.

    Open the record ↗

  2. A doctor treating you

    A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.

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