When do we choose the ‘better balance’ ear for cochlear implants?
Bibliographic record
Abstract
OBJECTIVES: In cochlear implant planning, the ear with poorer vestibular function, as determined through electronystagmography (ENG), is often selected as the site for implantation since surgery carries a low risk of iatrogenic labyrinthine injury. We sought to determine reasons for placing a cochlear implant in the 'better balance' ear. METHODS: A retrospective cohort study of patients implanted with a cochlear implant at a tertiary care center from 1984 to June 2009 was performed. Based on ENG results, patients with asymmetric caloric reduction were identified. Of these patients, those who were implanted in the 'better balance' ear were selected for chart review. The charts were reviewed to determine rationale for ear selection. RESULTS: Of the 724 cochlear implant patients implanted from 1984 to June 2009, ENG tests demonstrated that 130 (18%) had asymmetric abnormal responses. Thirty five (27%) of the patients with asymmetric abnormal responses were implanted in the 'better balance' ear. Review of these 35 patient charts revealed that reasons for selection of the 'better balance' ear fell into four categories: anatomical contraindications, attempting to attain binaural hearing, avoiding implantation of an ear with marked auditory deprivation, and patient preference. DISCUSSION: Based on our current practice, we have identified four situations in which patients were implanted in the 'better balance' ear, and subsequently developed an algorithm to aid surgeons in side selection for cochlear implantation. Further study and validation of this algorithm is recommended.
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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 | 0.000 |
| 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) | 0.005 | 0.001 |
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; both teacher heads agree on what is shown here.
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".