Bibliographic record
Abstract
Objective The objective of this study was to provide a proof of concept and to assess the success and safety of stapes surgery for otosclerosis under local anesthesia in an office‐based setting (OBS) as compared with a hospital operating room setting (ORS). Study Design Retrospective cohort study. Setting We reviewed all patients who underwent stapes surgery by the same surgeon from October 2014 to January 2017 at our tertiary care center (ORS, n = 36, 52%) and in an OBS (n = 33, 48%). Subjects and Methods The surgical technique was identical in both groups. All patients had a temporal bone computed tomography scan and audiogram within the 6 months prior to surgery. Air‐bone gaps (ABGs), bone conduction, and air conduction pure tone average values were calculated. Preoperative results for pure tone average, bone conduction, ABG, and word recognition scores were compared with early (4 months) and late (12 months) follow‐up audiograms. Intra‐ and postoperative complications were compared. Results Both groups were comparable in terms of demographic characteristics and severity of disease. The mean 1‐year postoperative ABG was 5.66 dB (95% CI = 4.42‐6.90) in the ORS group and 6.30 dB (95% CI = 4.50‐8.10) in the OBS group (P =. 55). ABG improved by 24.27 dB (95% CI = 21.40‐27.13) in the ORS group and 23.15 dB (95% CI = 18.45‐27.85) in the OBS group (P =. 68). Complication rates did not differ, although this study remains underpowered. Conclusions In this small group of patients, the success of stapes surgery performed in an OBS and its complications were comparable to those of an ORS, thus providing an alternative to patients on long operating room waiting lists.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".