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

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

119 participants

Study Classification

INTERVENTIONAL

Study Start Date

2021-06-15

Study Completion Date

2022-12-30

Brief Summary

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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.

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Detailed Description

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Conditions

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Spine Disease Spinal Fusion Surgery Spine Degeneration

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

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.

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

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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.

Group Type EXPERIMENTAL

SuMO Patient

Intervention Type DIAGNOSTIC_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.

Interventions

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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.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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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

Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No