Aseptic Loosening of Prosthetic JointNCT06724094
Artificial Intelligence to Detect Early Total Knee Replacement Implant Failure
An observational study of Aseptic Loosening of Prosthetic Joint, run by University Hospital Southampton NHS Foundation Trust.
Trial summary
The goal of this trial is to investigate whether Machine Learning (ML) can be used to detect small degrees of loosening, lucent zones, or any other changes on radiographs that might predict early failure following NexGen total knee replacement. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Aseptic Loosening of Prosthetic Joint
- How many people
- 2,105 participants
- Where
- No sites listed yet
- Study dates
- Aug 2025to Dec 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: The population will be adults who had the recalled a NexGen Total Knee Replacement with a standard tibial tray. It will include adults only, who has the TKR at University Hospitals Southampton between 2003 and 2022.
Who may be able to join
- Had a NexGen TKR between 2003 and 2022.
Who cannot join
- Below 18 yrs old.
- Revision surgery for any reason other than aseptic loosening
- patients who have not had a revision but who do not have a well functioning TKR.
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
Official title: Using Machine Learning to Detect and Predict Loosening NexGen Total Knee Replacement
The goal of this trial is to investigate whether Machine Learning (ML) can be used to detect small degrees of loosening, lucent zones, or any other changes on radiographs that might predict early failure following NexGen total knee replacement.
Researchers will identify plain AP and lateral plain film radiographs from two groups of patients. Those who has NexGen total knee replacements (TKRs) that went on to failure, and those who has well performing TKRs. Radiographs from these two groups will be labelled as 'failure' and 'well performing' and will be processed through a machine learning algorithm.
Read more
The algorithm will be successful if it is able to detect a NexGen TKR that went on to failure or went on to perform well. This will be determined by using a test set.
The population will be adults who had the recalled a NexGen Total Knee Replacement with a standard tibial tray. It will include adults only, who has the TKR at University Hospitals Southampton between 2003 and 2022.
Failure will be defined as revision of tibial or femoral components which is likely due to aspectic loosening. It will exclude washouts, exchange of poly, peri-prosthetic fractures, microbiologically confirmed infection.
Well performing TKRs will be defined as patients who have had their TKR in situ for 10 years and have reported no significant symptoms.
- Conditions
- Aseptic Loosening of Prosthetic Joint
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Failed | This group will be made up of patient who had revision TKR due to aseptic loosening within 10 years of primary arthroplasty | |
| Well performing | This group will be made up of patients who have an asymptomatic TKR 10 years after primary arthroplasty. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Predictive accuracy of machine learning model
The predictive accuracy of a machine learning algorithm. Using common ML measured, AUROC etc.
Measured: Up to 21 years. Data starts from 2003.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Dec 2024
- Study startAug 2025 (estimated)
- Primary completionDec 2025 (estimated)
- Study completionDec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Aseptic Loosening of Prosthetic JointStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Retrospective
- Enrolment
- 2,105 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University Hospital Southampton NHS Foundation Trust
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06724094
- Sponsor's protocol ID
- T&O0238
- Status last verified
- Dec 2024
- First submitted
- 6 Nov 2024
- Last updated
- 13 May 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 13 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Using Machine Learning to Detect and Predict Loosening NexGen Total Knee Replacement
- ClinicalTrials.gov ID
- NCT06724094
- Acronym / sponsor ID
- T&O0238
- Conditions
- Aseptic Loosening of Prosthetic Joint
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 2,105 participants (estimated)
- Lead sponsor
- University Hospital Southampton NHS Foundation TrustUniversity, hospital or other
- Study start
- Aug 2025 (estimated)
- Primary completion
- Dec 2025 (estimated)
- Study completion
- Dec 2025 (estimated)
- First posted
- 9 Dec 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The goal of this trial is to investigate whether Machine Learning (ML) can be used to detect small degrees of loosening, lucent zones, or any other changes on radiographs that might predict early failure following NexGen total knee replacement.
Researchers will identify plain AP and lateral plain film radiographs from two groups of patients. Those who has NexGen total knee replacements (TKRs) that went on to failure, and those who has well performing TKRs. Radiographs from these two groups will be labelled as 'failure' and 'well performing' and will be processed through a machine learning algorithm.
The algorithm will be successful if it is able to detect a NexGen TKR that went on to failure or went on to perform well. This will be determined by using a test set.
The population will be adults who had the recalled a NexGen Total Knee Replacement with a standard tibial tray. It will include adults only, who has the TKR at University Hospitals Southampton between 2003 and 2022.
Failure will be defined as revision of tibial or femoral components which is likely due to aspectic loosening. It will exclude washouts, exchange of poly, peri-prosthetic fractures, microbiologically confirmed infection.
Well performing TKRs will be defined as patients who have had their TKR in situ for 10 years and have reported no significant symptoms.
Study design
- Observational model
- Case-control
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Failed | – | –This group will be made up of patient who had revision TKR due to aseptic loosening within 10 years of primary arthroplasty |
| Well performing | – | –This group will be made up of patients who have an asymptomatic TKR 10 years after primary arthroplasty. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The population will be adults who had the recalled a NexGen Total Knee Replacement with a standard tibial tray. It will include adults only, who has the TKR at University Hospitals Southampton between 2003 and 2022.
Key inclusion criteria (1 listed)
- Had a NexGen TKR between 2003 and 2022.
Key exclusion criteria (3 listed)
- Below 18 yrs old.
- Revision surgery for any reason other than aseptic loosening
- patients who have not had a revision but who do not have a well functioning TKR.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Predictive accuracy of machine learning model
Time frame: Up to 21 years. Data starts from 2003.
The predictive accuracy of a machine learning algorithm. Using common ML measured, AUROC etc.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 May 2025.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Questions about this trial
What is this clinical trial studying?
An observational study of Aseptic Loosening of Prosthetic Joint, run by University Hospital Southampton NHS Foundation Trust.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 13 May 2025. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Rory Ormiston (07443 432819, rory.ormiston@uhs.nhs.uk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Predictive accuracy of machine learning model (time frame: Up to 21 years. Data starts from 2003.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 May 2025.