Surgery Clinical Trial
— DeepSurgeryOfficial title:
Optimization of a Tool for Predicting Postoperative Clinical Evolution After Lumbar Surgery Multicenter Longitudinal Prospective Study on a National Cohort Clinical Evolution After Lumbar Surgery
Verified date | February 2023 |
Source | Cortexx Medical Intelligence |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
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.
Status | Completed |
Enrollment | 119 |
Est. completion date | December 30, 2022 |
Est. primary completion date | June 30, 2022 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: - Major patient - Eligible for lumbar decompression surgery, instrumented or not - Social insured - Having given consent - Eligible for the acts described in Protocole Exclusion Criteria: - 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 |
Country | Name | City | State |
---|---|---|---|
France | Polyclinique Jean Villar | Bruges | Nouvelle Aquitaine |
France | Clinique Geoffroy Saint-Hilaire | Paris |
Lead Sponsor | Collaborator |
---|---|
Cortexx Medical Intelligence | Elsan, Malakoff-Humanis, Ramsay Générale de Santé |
France,
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. — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | 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). | 14 months | |
Secondary | 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 |
14 months |
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