Cochlear Implant Programming: A Global Survey on the State of the Art
Bibliographic record
Abstract
The programming of CIs is essential for good performance. However, no Good Clinical Practice guidelines exist. This paper reports on the results of an inventory of the current practice worldwide. A questionnaire was distributed to 47 CI centers. They follow 47600 recipients in 17 countries and 5 continents. The results were discussed during a debate. Sixty-two percent of the results were verified through individual interviews during the following months. Most centers (72%) participated in a cross-sectional study logging 5 consecutive fitting sessions in 5 different recipients. Data indicate that general practice starts with a single switch-on session, followed by three monthly sessions, three quarterly sessions, and then annual sessions, all containing one hour of programming and testing. The main focus lies on setting maximum and, to a lesser extent, minimum current levels per electrode. These levels are often determined on a few electrodes and then extrapolated. They are mainly based on subjective loudness perception by the CI user and, to a lesser extent, on pure tone and speech audiometry. Objective measures play a small role as indication of the global MAP profile. Other MAP parameters are rarely modified. Measurable targets are only defined for pure tone audiometry. Huge variation exists between centers on all aspects of the fitting practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".