Total Ossicular Replacement Prosthesis: A New Fat Interposition Technique
Bibliographic record
Abstract
Objective: To compare audiometric results between the standard total ossicular replacement prosthesis (TORP-S) and a new fat interposition total ossicular replacement prosthesis (TORP-F) in pediatric and adult patients and to assess the complication and the undesirable outcome. Study design: This is a retrospective study. Methods: This study included 104 patients who had undergone titanium implants with TORP-F and 54 patients who had undergone the procedure with TORP-S between 2008 and 2013 in our tertiary care centers. The new technique consists of interposing a fat graft between the 4 legs of the universal titanium prosthesis (Medtronic Xomed Inc, Jacksonville, FL, USA) to provide a more stable TORP in the ovale window niche. Normally, this prosthesis is designed to fit on the stapes’ head as a partial ossicular replacement prosthesis. Results: The postoperative air-bone gap less than 25 dB for the combined cohort was 69.2% and 41.7% for the TORP-F and the TORP-S groups, respectively. The mean follow-up was 17 months postoperatively. By stratifying data, the pediatric cohort shows 56.5% in the TORP-F group (n = 52) compared with 40% in the TORP-S group (n = 29). However, the adult cohort shows 79.3% in the TORP-F group (n = 52) compared with 43.75% in the TORP-S group (n = 25). These improvements in hearing were statistically significant. There were no statistically significant differences in the speech discrimination scores. The only undesirable outcome that was statistically different between the 2 groups was the prosthesis displacement: 7% in the TORP-F group compared with 19% in the TORP-S group ( P = .03). Conclusions: The interposition of a fat graft between the legs of the titanium implants (TORP-F) provides superior hearing results compared with a standard procedure (TORP-S) in pediatric and adult populations because of its better stability in the oval window niche.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".