Rotator Cuff TearsNCT06145815
Machine Learning Predictive Model for Rotator Cuff Repair Failure
An observational study of Rotator Cuff Tears, run by La Tour Hospital at 1 site in Switzerland.
Trial summary
There is little overall evidence behind clinical practice guidelines for diagnosis and treatment of rotator cuff repair. The purpose of this study was to compare the performance of different machine learning models that use pre-operative data from an international and multicentric database to predict if a patient that… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Rotator Cuff Tears
- What is being tested?
- Arthroscopic rotator cuff repair
- Type of treatment
- Surgery or procedure
- How many people
- 4,789 participants
- Where
- 1 siteSwitzerland
- Study dates
- 1 Sep 2022to 1 Nov 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
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
- Adult, Older adult
Study population: All adult patients who were primarily treated for rotator cuff tears by partial or complete surgical repair with a planned arthroscopic procedure were included in study.
Who may be able to join
- Primarily treated for rotator cuff tears by partial or complete surgical repair with a planned arthroscopic procedure
- Reparable tears
- No language barrier hindering questionnaire completion or legal incompetence were not included
Who cannot join
- missing pre- or post-operative single-assessment numeric evaluation (SANE)
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Predictive Model for Minimal Important Change After Rotator Cuff Repair Using Machine Learning Methods: A Pilot Study
There is little overall evidence behind clinical practice guidelines for diagnosis and treatment of rotator cuff repair. The purpose of this study was to compare the performance of different machine learning models that use pre-operative data from an international and multicentric database to predict if a patient that underwent rotator cuff repair could achieve the minimal important change (MIC) for single assessment numeric evaluation (SANE) at one year follow-up.
- Conditions
- Rotator Cuff Tears
- Being tested
- Arthroscopic rotator cuff repair
- Keywords
- Artificial intelligence, Machine Learning, Minimal Important Change
- Medical subject headings
- Rotator Cuff Injuries
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Arthroscopic rotator cuff repairProcedure or surgery
Patients underwent an arthroscopic repair for rotator cuff lesions
| Study group | Role | What they receive |
|---|---|---|
| MIC RCR patients | Patients who improved their SANE score beyond the minimal important change one year after arthroscopic rotator cuff repair Receives: Procedure: Arthroscopic rotator cuff repair | |
| No-MIC RCR patients | Patients who did not improve their SANE score beyond the minimal important change one year after arthroscopic rotator cuff repair Receives: Procedure: Arthroscopic rotator cuff repair |
What is being measured
The primary outcome is the main question the study is designed to answer.
SANE score
Single Assessment Numeric Evaluation (SANE). From 0 (worst) to 100 (best).
Measured: At 12 post-operative months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Nov 2023
- Study start1 Sep 2022
- Primary completion1 Sep 2022
- Study completion1 Nov 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Rotator Cuff TearsStudies 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
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 4,789 participants (actual)
Sponsor and investigators
- Lead sponsor
- La Tour Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Dr. Alexandre Lädermann, La Tour Hospital
- Investigators
- Alexandre Lädermann, MD, Principal investigator, La Tour hospital, Meyrin (1217) Geneva, Switzerland
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06145815
- Sponsor's protocol ID
- CCER #2020-02670
- Status last verified
- Nov 2023
- First submitted
- 17 Nov 2023
- Last updated
- 29 Nov 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 29 Nov 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Predictive Model for Minimal Important Change After Rotator Cuff Repair Using Machine Learning Methods: A Pilot Study
- ClinicalTrials.gov ID
- NCT06145815
- Acronym / sponsor ID
- CCER #2020-02670
- Conditions
- Rotator Cuff Tears
- Keywords
- Artificial intelligence, Machine Learning, Minimal Important Change
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 4,789 participants (actual)
- Lead sponsor
- La Tour HospitalUniversity, hospital or other
- Study start
- 1 Sep 2022 (actual)
- Primary completion
- 1 Sep 2022 (actual)
- Study completion
- 1 Nov 2023 (actual)
- First posted
- 24 Nov 2023 (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.
There is little overall evidence behind clinical practice guidelines for diagnosis and treatment of rotator cuff repair. The purpose of this study was to compare the performance of different machine learning models that use pre-operative data from an international and multicentric database to predict if a patient that underwent rotator cuff repair could achieve the minimal important change (MIC) for single assessment numeric evaluation (SANE) at one year follow-up.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| MIC RCR patients | – | Procedure: Arthroscopic rotator cuff repairPatients who improved their SANE score beyond the minimal important change one year after arthroscopic rotator cuff repair |
| No-MIC RCR patients | – | Procedure: Arthroscopic rotator cuff repairPatients who did not improve their SANE score beyond the minimal important change one year after arthroscopic rotator cuff repair |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- All adult patients who were primarily treated for rotator cuff tears by partial or complete surgical repair with a planned arthroscopic procedure were included in study.
Key inclusion criteria (3 listed)
- Primarily treated for rotator cuff tears by partial or complete surgical repair with a planned arthroscopic procedure
- Reparable tears
- No language barrier hindering questionnaire completion or legal incompetence were not included
Key exclusion criteria (1 listed)
- missing pre- or post-operative single-assessment numeric evaluation (SANE)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Arthroscopic rotator cuff repairPatients underwent an arthroscopic repair for rotator cuff lesions | Procedure or surgery | MIC RCR patients, No-MIC RCR patients |
Primary outcome
SANE score
Time frame: At 12 post-operative months
Single Assessment Numeric Evaluation (SANE). From 0 (worst) to 100 (best).
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 Nov 2023.
- Individual participant dataSharing planned: Undecided
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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. This study is not recruiting at the moment.
Alexandre Lädermann, MD principal investigator
La Tour hospital, Meyrin (1217) Geneva, Switzerland
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Rotator Cuff Tears, run by La Tour Hospital at 1 site in Switzerland.
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 3 inclusion and 1 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: finished, as of the sponsor's last update on 29 Nov 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Switzerland. Whether a site is taking part right now should be confirmed with that site. See every site.
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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
SANE score (time frame: At 12 post-operative months). 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 29 Nov 2023.