Long-Term Stability of Electrical Stimulation in Children with Bilateral Cochlear Implants
Bibliographic record
Abstract
The long-term stability of neural responses to cochlear implant (CI) stimulation and programmed stimulation levels remains unclear. Although smaller cohort studies suggest stabilization within months postimplant, reprogramming still consumes significant clinical time. The aim of this study was to investigate the resilience of the auditory nerve to prolonged stimulation from CIs and identify changes in the clinically provided stimulation levels over time. Stimulation parameters ( n = 14,072 MAPs), electrophysiological auditory nerve thresholds ( n = 23,215), and slopes of amplitude growth functions ( n = 17,849) were obtained from 664 bilaterally implanted children ( n = 1,291 devices) followed between September 2003 and July 2022. Stimulation parameters stabilized within 12 months following implantation for most, but not all, devices (75.3% and 75.4% of devices for C-levels and T-levels, respectively). Electrophysiological measures demonstrated very minor changes per year postimplant (slopes: mean [SE] = 0.03 [0.002] μV/CU/year [95% CI: 0.02–0.03]; thresholds: mean [SE] = 0.35 [0.06] CU/year [95% CI: 0.24–0.47]). While age at implantation did not relate to clinically meaningful changes in electrophysiological measures (slopes: mean [SE] = 0.02 [0.002] μV/CU/year [95% CI: 0.01–0.02]; thresholds: mean [SE] = 0.07 [0.08] CU/year [95% CI: −0.08 to 0.23]), stimulation levels decreased for children implanted at older ages (T-levels before plateau: mean [SE] = −0.47 [0.03] CU/year [95% CI: −0.53 to −0.42]; C-levels before plateau: mean [SE] = −0.78 [0.03] CU/year [95% CI: −0.85 to −0.72]). These findings indicate long-term neural and CI programming stability, suggesting potential for directing clinical time to care in areas other than reprogramming after the first year of implant use.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".