Currently, clinical research combining Neural Response Telemetry (NRT) and Electrically Evoked Auditory Brainstem Responses (EABR), for the prediction of cochlear implant (CI) fitting parameters remains scarce. OBJECTIVES: To investigate the correlations between NRT thresholds, EABR thresholds, and subjective behavioral threshold T/C-levels in CI recipients, and to develop an artificial neural network-based...
✦ The floor
Discussion
Signed responses from readers of the wire.
Promising early-stage model for predicting cochlear implant dynamic range from NRT and EABR data, but clinical adoption requires prospective validation before changing fitting workflows.
Automating dynamic range prediction from objective measures could reduce the burden of behavioural fitting sessions, particularly for paediatric or non-cooperative CI recipients.
- 01Dual-data-driven model combines Neural Response Telemetry (NRT) and electrically evoked ABR (EABR) thresholds to predict CI dynamic range.
- 02Study published in Hearing Research (PMID 42874450; DOI 10.1016/j.heares.2026.109832).
- 03Approach is data-driven, aiming to reduce reliance on behavioural responses during fitting.
- 04Could be especially useful for paediatric or difficult-to-test cochlear implant recipients.
- 05Findings require prospective external validation before clinical implementation.
A dual-data-driven model combining NRT and EABR thresholds can predict cochlear implant dynamic range parameters for clinical fitting.
studypartially supportedThe model is suitable for clinical fitting applications.
studyunclear- PMID
- 42874450
- DOI
- 10.1016/j.heares.2026.109832.
- Journal
- Hearing Research
- Publication type
- research_article
- Evidence level
- 4
- Population
- Cochlear implant recipients (population details not stated in abstract)
- Intervention
- Dual-data-driven model using Neural Response Telemetry and EABR thresholds to predict CI dynamic range parameters
Primary outcomes
Predicted cochlear implant dynamic range parameters (T-levels and C/M-levels)