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Related Concept Videos

The Cochlea01:13

The Cochlea

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The cochlea is a coiled structure in the inner ear that contains hair cells—the sensory receptors of the auditory system. Sound waves are transmitted to the cochlea by small bones attached to the eardrum called the ossicles, which vibrate the oval window that leads to the inner ear. This causes fluid in the chambers of the cochlea to move, vibrating the basilar membrane.
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Related Experiment Video

Updated: Jul 13, 2025

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages
06:04

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Published on: March 24, 2023

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Evolving a Model for Cochlear Implant Outcome.

Ulrich Hoppe1, Anne Hast1, Joachim Hornung1

  • 1Cochlear Implant Center CICERO, Department of Otorhinolaryngology-Head and Neck Surgery, Uniklinikum Erlangen, Waldstr. 1, D-91054 Erlangen, Germany.

Journal of Clinical Medicine
|October 14, 2023
PubMed
Summary
This summary is machine-generated.

Predicting cochlear implant (CI) success is crucial for adults with hearing loss. A refined model, incorporating duration of unaided hearing loss, improves speech recognition prediction, especially for those with no pre-operative hearing.

Keywords:
CI outcomeadultsgeneralised linear modelpredictionword recognition

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Area of Science:

  • Audiology
  • Otolaryngology
  • Biomedical Engineering

Background:

  • Cochlear implantation (CI) offers significant benefits for postlingually deafened adults.
  • Predicting CI outcomes is essential when speech recognition with a CI is expected to surpass hearing aid performance.
  • Accurate prediction is particularly desired for individuals with existing residual speech recognition.

Purpose of the Study:

  • To enhance a CI outcome prediction model for individuals with preoperative word recognition.
  • To extend the model's applicability to include subjects with no residual hearing.
  • To incorporate additional routine audiological examination results into the prediction model.

Main Methods:

  • Refinement of a pre-existing CI outcome prediction model.
  • Inclusion of duration of unaided hearing loss (DuHL) as a new predictive factor.
  • Validation of the extended model across diverse patient groups, including those with and without preoperative residual hearing.

Main Results:

  • The inclusion of DuHL significantly reduced the prediction error (Median Absolute Error - MAE).
  • For subjects with no residual hearing pre-surgery, the MAE decreased from 23.7% to 17.2% with the enhanced model.
  • The model modification did not alter the MAE for subjects who already had preoperative speech recognition.

Conclusions:

  • Predicting word recognition outcomes with cochlear implants is feasible within clinically meaningful ranges.
  • Outcome prediction is vital for informed preoperative patient counseling.
  • Accurate prediction aids in systematic monitoring and management of CI fitting during aftercare.