Effect of Adhesion on the Acoustic Functioning of Partial Ossicular Replacement Prostheses in the Cadaveric Human Ear
Bibliographic record
Abstract
BACKGROUND: Adhesion formation following ossiculoplasty surgery has been implicated as a cause of the progressive deterioration of an initially good postoperative hearing result. Scar tissue between the partial ossicular reconstruction prosthesis (PORP) and adjacent middle ear structures is a common finding at revision surgery. OBJECTIVES: This study aims to investigate the effects of simulated scarring on the microacoustic transmission characteristics of a PORP in the fresh cadaveric human temporal bone. METHODS: Cortical mastoidectomy and extended posterior tympanotomy permitted access to reflective markers placed on the stapes footplate. A sound stimulus at 80 to 95 dB was presented to the closed external ear canal and displacements were measured with the laser Doppler vibrometer. PORPs were placed in cadaveric specimens, and the shaft of the prosthesis was cemented to the adjacent promontory using dental cement. Serial measurements were made from the stapes footplate as the adhesive was allowed to harden, a process that we have taken to simulate the gradual fixation of the prosthesis by scarring in the live patient. RESULTS: There was a consistent reduction in stapes footplate displacement as the cement hardened. CONCLUSION: The gradual adhesion of a PORP to the promontory produces a consistent reduction in microacoustic transfer to the stapes footplate in the fresh human cadaveric model.
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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 | 0.001 |
| 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) | 0.003 | 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".