Long-Term Audiometric Outcomes of a Self-Crimping Stapes Prosthesis With CO2 Laser Stapedotomy
Bibliographic record
Abstract
OBJECTIVE: To evaluate our experience with a self-crimping stapes prosthesis. STUDY DESIGN: Retrospective case review. SETTING: Tertiary referral center. PATIENTS: All patients diagnosed with otosclerosis who underwent surgery between June 2013 and June 2020. Inclusion criteria were 18 years or older, isolated stapes ankylosis, and at least 1 year of postoperative audiologic data. INTERVENTIONS: CO 2 laser stapedotomy undertaken by the same surgeon using the same CO 2 laser stapedotomy technique and the same prosthesis. MAIN OUTCOME MEASURES: Preoperative and postoperative audiologic data including air-bone gap (ABG) measurements, average speech discrimination score and pure-tone averages (PTAs). Postoperative hearing assessments were performed at 3 weeks, 3 months, 6 months, 1 year, and annually thereafter. RESULTS: Two hundred fourteen patients were included in the study, of whom 17 had bilateral sequential surgery for a total of 231 ears. Mean preoperative air conduction-PTA was 58.8 dB and mean preoperative bone conduction-PTA 24.2 dB, a preoperative ABG of 34.6 dB. One year postoperatively, mean air conduction-PTA improved to 31.2 dB ( p < 0.0001). ABG showed a significant improvement from 34.6 to 5.5 dB ( p < 0.0001). Closure of the ABG to within 10 dB was achieved in 87% ears at 3 months, in 91% at 6 months, and in 93% at 1 year. There was no significant difference in preoperative and postoperative average speech discrimination score. CONCLUSION: The current study demonstrates favorable audiologic outcomes in a large cohort of patients using a self-crimping stapes prosthesis. These results were stable for up to 7 years on follow-up.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".