DeepSurgery: Optimization of a Tool for Predicting Postoperative Clinical Evolution After Lumbar Surgery

Sponsor

Cortexx Medical Intelligence (Industry)

Overall Status

Recruiting

CT.gov ID

NCT05166018

Collaborator

Ramsay Générale de Santé (Other), Elsan (Other), Malakoff-Humanis (Other)

220

Enrollment

Locations

Arm

11.5

Anticipated Duration (Months)

110

Patients Per Site

9.6

Patients Per Site Per Month

Study Details

Study Description

Brief 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 medical care up to 6 months.

Condition or Disease	Intervention/Treatment	Phase
Spine Disease Spinal Fusion Surgery Spine Degeneration	Diagnostic Test: SuMO Patient	N/A

Study Design

Study Type:

Interventional

Anticipated Enrollment :

220 participants

Allocation:

N/A

Intervention Model:

Single Group Assignment

Intervention 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.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)

Primary Purpose:

Diagnostic

Official 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

Actual Study Start Date :

Jun 15, 2021

Anticipated Primary Completion Date :

Apr 30, 2022

Anticipated Study Completion Date :

May 30, 2022

Arms and Interventions

Arm	Intervention/Treatment
Experimental: SuMO Patient 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.	Diagnostic Test: SuMO Patient 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.

Arm

Intervention/Treatment

Experimental: SuMO Patient

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.

Diagnostic Test: SuMO Patient

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.

Outcome Measures

Primary Outcome Measures

Optimization of a tool for predicting the postoperative clinical course after lumbar surgery [14 months]
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).

Secondary Outcome Measures

Collection of optimized data in the patient operative long terms care [14 months]
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

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years and Older

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

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

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Polyclinique Jean Villar	Bruges	Nouvelle Aquitaine	France	33520
2	Clinique Geoffroy Saint-Hilaire	Paris		France	75005

Sponsors and Collaborators

Cortexx Medical Intelligence
Ramsay Générale de Santé
Elsan
Malakoff-Humanis

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Additional Information:

Mobile application for collecting patient's data

Publications

None provided.

Responsible Party:

Cortexx Medical Intelligence

ClinicalTrials.gov Identifier:

NCT05166018

Other Study ID Numbers:

DeepSurgeryMH_01

First Posted:

Dec 21, 2021

Last Update Posted:

Mar 22, 2022

Last Verified:

Mar 1, 2022

Individual Participant Data (IPD) Sharing Statement:

Plan to Share IPD:

Studies a U.S. FDA-regulated Drug Product:

Studies a U.S. FDA-regulated Device Product:

Additional relevant MeSH terms:

Spinal Diseases

Study Results

No Results Posted as of Mar 22, 2022