Spine DiseaseDeepSurgeryNCT05166018
Validity and Accuracy of a Machine Learning Predictive Model in the Exploitation of Patients Related Outcomes in Spine Surgery
A study testing SuMO Patient in people with Spine Disease and Spinal Fusion, run by Cortexx Medical Intelligence at 2 sites in France.
Trial summary
The objective of the study is the establishment, optimization and prospective evaluation of a digital predictive platform capable of providing for each lumbar spine operated patient a clinical predictive status: Patient green (success) orange (treatment failure ), red patient (complication) in order to optimize his… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Spine Disease, Spinal Fusion, Surgery
- What is being tested?
- SuMO Patient
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 174 participants
- Where
- 2 sitesFrance
- Study dates
- 1 Sep 2021to 31 Jan 2023
- Phase
- Interventional
- 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
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Major patient
- Eligible for lumbar decompression surgery, instrumented or not
- Social insured
- Having given consent
- Eligible for the acts described in Protocole
Who cannot join
- Minor
- Pregnant or breastfeeding woman
- Safeguard measure or guardianship
- Arthrodesis on more than 2 levels
- Interventions linked to a traumatic or infectious context are excluded
Trial locations and contacts
2 sites in 1 country.
France2 sites
Polyclinique Jean Villar
Bruges, New Aquitaine, 33520
Clinique Geoffroy Saint-Hilaire
Paris, Île-de-France Region, 75005
About this study
Official title: Validity and Accuracy of a Machine Learning Predictive Model in the Exploitation of Patients Related Outcomes in Spine Surgery Multicenter Longitudinal Prospective Study on a National Cohort Clinical Evolution After Lumbar Surgery
The objective of the study is the establishment, optimization and prospective evaluation of a digital predictive platform capable of providing for each lumbar spine operated patient a clinical predictive status: Patient green (success) orange (treatment failure ), red patient (complication) in order to optimize his medical care up to 6 months.
- Conditions
- Spine Disease, Spinal Fusion, Surgery, Spine Degeneration
- Being tested
- SuMO Patient
- Medical subject headings
- Spinal Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
SuMO PatientDiagnostic test
The current study is interventional insofar as the patient is collecting all of his socio-medical information. The analysis of the data provided by the patient makes it possible to establish a long-term prognosis for the patient but does not in itself constitute a parallel medical approach.
SUMO allows the surgeon to transmit post-operative advice developed by the surgeons themselves.
| Study group | Role | What they receive |
|---|---|---|
| SuMO Patient | Experimental | 92 data will be collected during the patient care episode. Among the 92 criteria, 63 are pre-operative, 29 are post-operative in order to provide an evolutionary prediction during the management of the patient.
Post-operative follow-up criteria making it possible to establish the scalability or non-scalability of the quality of life after the surgical procedure.
The results will be compared to the prediction proposed by the machine learning algorithm. Receives: Diagnostic Test: SuMO Patient |
What is being measured
The primary outcome is the main question the study is designed to answer.
Optimization of a tool for predicting the postoperative clinical course after lumbar surgery
Establishment and prospective evaluation of a predictive tool with the area under the receiver operating characteristic (AUROC) metric >= 80% Sensitivity >= 90% Specificity >= 60% in the capacity of providing for each back operated patient a clinical predictive status: green patient (success) orange (treatment failure), red patient (complication).
Measured: 6 months after surgery
Secondary outcomes (1)
Collection of optimized data in the patient operative long terms care
Implementation, optimization and evaluation of a digital tool for collecting patient data on the episode of care
Outcome (unit) - Result expected assessment time connection means preoperatively (second/connection) - 300s time 'use and navigation (second) - 1800s number of connections made by the patient preoperatively (number) - 5 number of connections / day before operation (number) - 1 number of use (number) - 15 number of drops / connection (Ratio%) - <20% number of lost view (no connection> 20 days) (Ratio%) - <10% evaluation of average using time post-operative (second/connections) - 300 Time of use and navigation (second) - 1800 number of connections made by the patient in post -operative (number) - 5 number of connections / day after operation (number)- 1 number of uses (number) - 15 number of withdrawals (Ratio%) - <20% number of lost to follow-up (no connection> 20 days) (Ratio%) - <10% number of documents analyzed / patient (number) - 10
Measured: 14 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted21 Dec 2021
- Study start1 Sep 2021
- Primary completion31 Jan 2023
- Study completion31 Jan 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Spine DiseaseStudies 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- The patient will be required to complete a guided digital questionnaire at each follow-up assessment. This questionnaire will be completed online by the patient in the Surgery Medical Outcomes (SuMO system) system developped by the Society Cortexx Medical Intelligence. The system access procedures and connection codes will be known to the patient by the investigating physician. Patients will, throughout the study, be automatically informed via the SUMO system of the availability of data to be completed. The security of patient data is guaranteed by encrypted and separate storage of medical data, in order to comply with applicable regulatory requirements.
- Masking
- None (open label)
- Enrolment
- 174 participants (actual)
Sponsor and investigators
- Lead sponsor
- Cortexx Medical Intelligence
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- GCS Ramsay Santé pour l'Enseignement et la Recherche, Elsan, Malakoff-Humanis
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05166018
- Sponsor's protocol ID
- DeepSurgeryMH_01
- Other IDs
- 2021-A00055-36
- Acronym
- DeepSurgery
- Status last verified
- Oct 2026
- First submitted
- 16 Nov 2021
- Last updated
- 22 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Andre A, Peyrou B, Carpentier A, Vignaux JJ. Feasibility and Assessment of a Machine Learning-Based Predictive Model of Outcome After Lumbar Decompression Surgery. Global Spine J. 2022 Jun;12(5):894-908. doi: 10.1177/2192568220969373. Epub 2020 Nov 19.
PubMed 33207969Andre A, Peyrou B, Vignaux JJ, Boissiere L, Obeid I. Validity and accuracy of a machine learning predictive model in the exploitation of patient-related outcomes in spine surgery. Front Surg. 2026 Jan 9;12:1710512. doi: 10.3389/fsurg.2025.1710512. eCollection 2025.
PubMed 41583840
Study at a glance
From the registry record, last updated by the sponsor on 22 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Validity and Accuracy of a Machine Learning Predictive Model in the Exploitation of Patients Related Outcomes in Spine Surgery Multicenter Longitudinal Prospective Study on a National Cohort Clinical Evolution After Lumbar Surgery
- ClinicalTrials.gov ID
- NCT05166018
- Acronym / sponsor ID
- DeepSurgery / DeepSurgeryMH_01
- Conditions
- Spine Disease, Spinal Fusion, Surgery, Spine Degeneration
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 174 participants (actual)
- Lead sponsor
- Cortexx Medical IntelligenceIndustry (pharma, biotech, devices)
- Collaborators
- GCS Ramsay Santé pour l'Enseignement et la Recherche, Elsan, Malakoff-Humanis
- Study start
- 1 Sep 2021 (actual)
- Primary completion
- 31 Jan 2023 (actual)
- Study completion
- 31 Jan 2023 (actual)
- First posted
- 21 Dec 2021 (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 objective of the study is the establishment, optimization and prospective evaluation of a digital predictive platform capable of providing for each lumbar spine operated patient a clinical predictive status: Patient green (success) orange (treatment failure ), red patient (complication) in order to optimize his medical care up to 6 months.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- The patient will be required to complete a guided digital questionnaire at each follow-up assessment. This questionnaire will be completed online by the patient in the Surgery Medical Outcomes (SuMO system) system developped by the Society Cortexx Medical Intelligence. The system access procedures and connection codes will be known to the patient by the investigating physician. Patients will, throughout the study, be automatically informed via the SUMO system of the availability of data to be completed. The security of patient data is guaranteed by encrypted and separate storage of medical data, in order to comply with applicable regulatory requirements.
| Arm | Type | Receives |
|---|---|---|
| SuMO Patient | Experimental | Diagnostic Test: SuMO Patient92 data will be collected during the patient care episode. Among the 92 criteria, 63 are pre-operative, 29 are post-operative in order to provide an evolutionary prediction during the management of the patient. Post-operative follow-up criteria making it possible to establish the scalability or non-scalability of the quality of life after the surgical procedure. The results will be compared to the prediction proposed by the machine learning algorithm. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (5 listed)
- Major patient
- Eligible for lumbar decompression surgery, instrumented or not
- Social insured
- Having given consent
- Eligible for the acts described in Protocole
Key exclusion criteria (5 listed)
- Minor
- Pregnant or breastfeeding woman
- Safeguard measure or guardianship
- Arthrodesis on more than 2 levels
- Interventions linked to a traumatic or infectious context are excluded
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 |
|---|---|---|
| SuMO PatientThe current study is interventional insofar as the patient is collecting all of his socio-medical information. The analysis of the data provided by the patient makes it possible to establish a long-term prognosis for the patient but does not in itself constitute a parallel medical approach. SUMO allows the surgeon to transmit post-operative advice developed by the surgeons themselves. | Diagnostic test | SuMO Patient |
Primary outcome
Optimization of a tool for predicting the postoperative clinical course after lumbar surgery
Time frame: 6 months after surgery
Establishment and prospective evaluation of a predictive tool with the area under the receiver operating characteristic (AUROC) metric >= 80% Sensitivity >= 90% Specificity >= 60% in the capacity of providing for each back operated patient a clinical predictive status: green patient (success) orange (treatment failure), red patient (complication).
1 secondary outcome
Collection of optimized data in the patient operative long terms care
Time frame: 14 months
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 22 Oct 2026.
- Background: PubMed 33207969Andre A, Peyrou B, Carpentier A, Vignaux JJ. Feasibility and Assessment of a Machine Learning-Based Predictive Model of Outcome After Lumbar Decompression Surgery. Global Spine J. 2022 Jun;12(5):894-908. doi: 10.1177/2192568220969373. Epub 2020 Nov 19.
- Results publication: PubMed 41583840Andre A, Peyrou B, Vignaux JJ, Boissiere L, Obeid I. Validity and accuracy of a machine learning predictive model in the exploitation of patient-related outcomes in spine surgery. Front Surg. 2026 Jan 9;12:1710512. doi: 10.3389/fsurg.2025.1710512. eCollection 2025.
- Individual participant dataSharing planned: No
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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.
The record lists no contact. Use the official record to reach the sponsor.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing SuMO Patient in people with Spine Disease and Spinal Fusion, run by Cortexx Medical Intelligence at 2 sites in France.
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 5 inclusion and 5 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 22 Oct 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in France. 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?
Optimization of a tool for predicting the postoperative clinical course after lumbar surgery (time frame: 6 months after surgery). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05166018, which also lists 2 linked publications.
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 22 Oct 2026.