Effect of cochlear implant electrode insertion on middle-ear function as measured by intra-operative laser Doppler vibrometry
Bibliographic record
Abstract
HYPOTHESIS: The aim of this study was to investigate the impact of cochlear implant electrode insertion on middle-ear low frequency function in humans. BACKGROUND: Preservation of residual low frequency hearing with addition of electrical speech processing can improve the speech perception abilities and hearing in noise of cochlear implant users. Preservation of low frequency hearing requires an intact middle-ear conductive mechanism in addition to intact inner-ear mechanisms. Little is known about the effect of a cochlear implant electrode on middle-ear function. METHODS: Stapes displacement was measured in seven patients undergoing cochlear implantation. Measurements were carried out intra-operatively before and after electrode insertion. Each patient acted as his or her own control. Sound was delivered into the external auditory canal via a speaker and calibrated via a probe microphone. The speaker and probe microphone were integrated into an individually custom-made ear mould. Ossicular displacement in response to a multisine stimulus at 80 dB SPL was measured at the incudostapedial joint via the posterior tympanotomy, using an operating microscope mounted laser Doppler vibrometry system. RESULTS: Insertion of a cochlear implant electrode into the scala tympani had a variable effect on stapes displacement. In three patients, there was little change in stapes displacement following electrode insertion. In two patients, there was a significant increase, while in a further two there was a significant reduction in stapes displacement. This variability may reflect alteration of cochlear impedance, possibly due to differing loss of perilymph associated with the electrode insertion. CONCLUSION: Insertion of a cochlear implant electrode produces a change in stapes displacement at low frequencies, which may have an effect on residual low frequency hearing thresholds.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".