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Related Concept Videos

Language Development01:22

Language Development

Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...

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Related Experiment Video

Updated: Jun 29, 2026

Performing Intracochlear Electrocochleography During Cochlear Implantation
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Early Cochlear Implant Outcomes Predict Long-Term Speech Recognition.

Isabelle J Chau1,2,3, Ansley J Kunnath4,5,3, Andrew Gothard6

  • 1Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Charleston, South Carolina, USA.

Ear and Hearing
|December 17, 2025
PubMed
Summary
This summary is machine-generated.

Early cochlear implant (CI) speech recognition predicts long-term outcomes. A logistic regression model using 3-month scores accurately estimates 12-month performance, aiding timely interventions for CI users.

Keywords:
Cochlear implantsModelingPredicting outcomesSpeech recognition

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Area of Science:

  • Audiology
  • Otolaryngology
  • Biostatistics

Background:

  • Early identification of cochlear implant (CI) users at risk for poor audiological outcomes is crucial for timely intervention.
  • Optimizing long-term CI benefit requires predicting speech recognition performance early in the post-implantation period.

Purpose of the Study:

  • To develop and evaluate logistic regression models for predicting 12-month speech recognition performance in CI users.
  • To assess the predictive value of early speech recognition scores and patient factors for long-term CI outcomes.

Main Methods:

  • A retrospective cohort study of 625 postlingually deafened adult CI users.
  • Logistic regressions were used to model the likelihood of significant improvement in consonant-nucleus-consonant (CNC) word scores at 12 months.
  • Models incorporated baseline demographics, duration of deafness, pre-CI CNC scores, and early post-activation CNC improvement at 1 or 3 months.

Main Results:

  • 82% of patients showed improved CNC scores at 12 months post-implantation.
  • Early improvement (1 or 3 months) was a strong predictor of 12-month outcomes (ORs 45.72 and 22.22, respectively).
  • The model using 3-month data achieved the highest predictive accuracy (AUC = 0.92) in the validation cohort.

Conclusions:

  • Models incorporating early CNC score improvements demonstrate strong predictive discrimination for 12-month outcomes.
  • A regression model utilizing 3-month post-CI speech recognition data can provide reliable early estimates of long-term performance.
  • This tool can assist clinicians in identifying patients who may benefit from early intervention to optimize CI outcomes.