Bibliographic record
Abstract
OBJECTIVE: The authors report the results of a survey of members of the American Otological Society (AOS) and the American Neurotology Society (ANS) regarding their use of prostheses currently available for ossiculoplasty and stapedectomy. These findings are compared with a similar study presented by one of the authors in 1989. METHODS: Questionnaires were sent to the entire membership of the AOS and ANS with questions regarding biomaterial and prosthesis usage for stapes and chronic ear surgery, as well as satisfaction with each type of prosthesis used. Of the 575 questionnaires mailed, 274 (47%) were returned. Only 248 of the respondents performed middle ear surgery (43%), and their responses constitute the database for this study. RESULTS: For those respondents performing stapes surgery in both 1989 and 1999, the mean number of cases per year has increased from 32 to 37 (p < or = 0.004). The mean number of chronic ear cases has also increased from 95 in 1989 to 110 in 1999 (p < or = 0.001). As a biomaterial, hydroxyapatite prostheses are used by most surgeons (82%), followed by autograft and homograft bone (72%), autograft and homograft cartilage (62%), and Plastipore (59%). (Although 62% of respondents use cartilage, only 4.4% ranked it first in preference.) In 1989, bone was used most (93%), followed by cartilage (78%) and Plastipore (81%). Hydroxyapatite, which had just been introduced as a biomaterial, was used by only 9% of respondents. For stapes prostheses in 1999, the majority of respondents used stainless steel/platinum (71%), bucket handle (69%), or partial fluoroplastic (56%) prostheses. There was a high overall satisfaction rate in the use of most of these prostheses (> 85%), with several exceptions. The lowest satisfaction rate was 71% for Plastipore partial ossicular replacement prosthesis and total ossicular replacement prosthesis. Usage and satisfaction rates are presented for specific types of implants and compared with the earlier survey findings. CONCLUSION: The current use of implants in middle ear surgery demonstrates a specific pattern with a high degree of user satisfaction. The preference for implants by respondents has remained stable over the past 10 years; there has been a decrease in the percentage of use of bone, cartilage, and Plastipore with a corresponding increase in the use of hydroxyapatite.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".