Effects of Cartilage Overlay on the Tympanic Membrane: Lessons From a Temporal Bone Study for Cartilage Tympanoplasty
Bibliographic record
Abstract
HYPOTHESIS: Placing cartilage grafts on different tympanic membrane (TM) locations will affect sound transfer function, and the effects will differ according to the part of the TM modified. BACKGROUND: Cartilage tympanoplasty is increasingly popular because of lower reperforation rates, and better long-term stability. In this temporal bone study, we investigated the effect of placing cartilage grafts over different parts of the normal TM on sound transmission. METHODS: In 10 human fresh frozen temporal bones, umbo and stapes vibrations to acoustic stimuli from 250 to 8000 Hz were measured at multiple points using a scanning laser vibrometer. Four different cartilage arrangements were measured in each temporal bone. 1) Overlay condition leaving an umbo rim of normal TM (Umbo Rim). 2) Overlay condition leaving annular rim of normal TM (Annular Rim). 3) Overlay condition leaving both rims of normal TM (Two Rims). 4) Overlay condition leaving no normal TM exposed (No Rims). RESULTS: At low frequencies, there was a statistically significant decrease in velocity from baseline for the No Rims (umbo mean -4 dB; stapes -6 dB) and Umbo Rim (umbo -4 dB; stapes -3.7 dB) conditions. All conditions showed significant decreases for middle frequencies (umbo -4.0, -5.9, -7.4 and -6.3 dB; stapes -10.8, -6.6, -6.3 and -7.7 dB) and high frequencies (umbo -13.2, -3.0, -3.1 and -5.5 dB; stapes -4.6, -2.4, -2.6 and -3.5 dB). Results are in order for No Rims, Umbo Rim, Two Rims, and Annular Rim conditions. CONCLUSION: In the low frequencies, it seems to matter where the cartilage is placed, and in particular the annular rim of the TM seems to be important for the low-frequency acoustic transfer function. In the higher frequencies, all graft placements caused some drop at all frequencies. In all frequencies, effects were modest by clinical standards.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".