Predictive Study on Hearing Rehabilitation After Cochlear Implant

Sponsor
University Hospital, Grenoble (Other)
Overall Status
Recruiting
CT.gov ID
NCT06086041
Collaborator
(none)
50
1
36.5
1.4

Study Details

Study Description

Brief Summary

The aim of this study is to display the predictive factors of hearing rehabilitation after cochlear implant surgery in severely to profoundly deaf adults.

Condition or Disease Intervention/Treatment Phase
  • Procedure: cochlear implant

Detailed Description

Cochlear implants are indicated in France in cases of severe to profound bilateral sensorineural hearing loss with an audiometric threshold of less than or equal to 50% speech discrimination in silence in the Fournier list (or equivalent) at 60 dB, in the free field, with well-fitted hearing aids. Cochlear implant represents a major advance in the management of severe to profoundly deaf patients and has also shown a benefit in the prevention of neurodegenerative diseases.

An average of 1800 cochlear implants are placed in France per year, 58% of which are placed in patients over 18 years of age.

The results of cochlear implants are in favour of a benefit in speech comprehension compared to hearing aids in cases of severe to profound deafness. However, there is a strong disparity in hearing performance after cochlear implantation from one patient to another, whether in silence or in noise.

Several factors influencing the results of the implant have been identified. Some of them are linked to the patient: etiology of the deafness, duration of auditory deprivation, age at implantation, residual hearing, pre- or post-lingual status of the deafness, some others are related to implant surgery (insertion of the electrode in the tympanic ramp, complete insertion, presence of a translocation, depth of electrode insertion).

Finally, there are factors related to the quality of the settings of the implant and to the brain plasticity of the patients.The 4 main factors seem to be the duration of the deafness, the age of onset of the deafness, its etiology and the duration of the patient's experience with the implant. It is assumed that the performance of cochlear implantation is strongly related to the individual's auditory processing abilities and the integrity of the central nervous system from the auditory nerve to the cortex.

At present, it is very difficult to predict the outcome of cochlear implants in deaf patients with a cochlear implant indication prior to implantation. The results remain variable from one patient to another and, to date, both the etiology and the state of the central auditory pathways are not taken into account in the indication for cochlear implantation. Animal studies have demonstrated anterograde degenerative neural damage in cochlear deafness (presbycusis, endolymphatic hydrops) and such damage is likely to explain the functional variability observed in humans in the case of neural stimulation with cochlear implants. Multiple integration of clinical data to propose a predictive model can now be done using both supervised (Deep Learning) and unsupervised (Manifold Learning) Machine Learning techniques, including for predicting auditory recovery. It is now possible to extend machine learning models to include quantitative data from diffusion MRI with the goal of providing an objective functional parameter from the central auditory pathways, then combined with clinical parameters and genetic to obtain a predictive model of hearing recovery after cochlear implantation. This study will allow us, through the study of brain tractography, to specify the role of the central auditory pathways in the results of cochlear implantation, a role that has not been determined to date, and to evaluate their correlation with clinical and genetic in order to create a predictive model of good auditory rehabilitation in artificial intelligence. The objective is to better select patients who can benefit from a cochlear implant in order to implant them in an optimal timing and to improve indications for cochlear implant.

Study Design

Study Type:
Observational
Anticipated Enrollment :
50 participants
Observational Model:
Cohort
Time Perspective:
Prospective
Official Title:
Predictive Factors of Hearing Rehabilitation After Cochlear Implant Surgery in Deaf Patients
Actual Study Start Date :
Jan 17, 2022
Anticipated Primary Completion Date :
Feb 1, 2025
Anticipated Study Completion Date :
Feb 1, 2025

Arms and Interventions

Arm Intervention/Treatment
severely to profoundly deaf patients with cochlear implantation indication

Severely to profoundly deaf patients consulting in Grenoble University Hospital with cochlear implantation indication. Patients are followed according to current care during 1 year after cochlear implantation.

Procedure: cochlear implant
cochlear implant

Outcome Measures

Primary Outcome Measures

  1. Identification of the predictive factors of hearing rehabilitation after cochlear implantation in severely to profoundly deaf adults. [1 year post-surgery]

    Correlation between a diffusion MRI biomarker extracted from preoperative brain tractography (fractional anisotropy) and the postoperative hearing performance in silence and noise after cochlear implantation.

Secondary Outcome Measures

  1. Evaluate the correlation between several predictive factors like clinical parameters, genetics ... with the MRI biomarker. [3 months, 6 months and 1 year post-surgery.]

    Correlation between clinical predictive factors (age, age at onset of deafness , etiology and genetic) and the postoperative hearing performance in silence and noise after cochlear implantation.

Eligibility Criteria

Criteria

Ages Eligible for Study:
18 Years and Older
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
No
Inclusion Criteria:

Patient severely to profoundly deafed according French National Authority for Health (HAS) recommendations followed in Grenoble University Hospital.

Exclusion Criteria:
  • cochlear malformation making impossible the cochlear implantation

  • IRM contraindications

  • Patient opposed to the use of their data in the context of the research

Contacts and Locations

Locations

Site City State Country Postal Code
1 Grenoble University hospital Grenoble France 38043

Sponsors and Collaborators

  • University Hospital, Grenoble

Investigators

  • Principal Investigator: raphaĆ«le QUATRE, University Hospital, Grenoble

Study Documents (Full-Text)

None provided.

More Information

Publications

Responsible Party:
University Hospital, Grenoble
ClinicalTrials.gov Identifier:
NCT06086041
Other Study ID Numbers:
  • 38RC23.0020
First Posted:
Oct 17, 2023
Last Update Posted:
Oct 17, 2023
Last Verified:
Oct 1, 2023
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No
Keywords provided by University Hospital, Grenoble
Additional relevant MeSH terms:

Study Results

No Results Posted as of Oct 17, 2023