Effectiveness of the heat-activated nitinol smart piston stapes prosthesis in stapedectomy surgery.
Bibliographic record
Abstract
OBJECTIVE: To compare the SMart piston stapes prosthesis to a standard manual crimp prosthesis on operative time and air-bone gap (ABG) closure in stapedectomy. DESIGN: Retrospective chart review. SETTING: Tertiary referral centre. METHODS: The charts of patients undergoing stapedectomy for otosclerosis were analyzed. We compared the results of 76 patients (80 ears) who received the autocrimping SMart piston prosthesis to those of 21 patients (21 ears) who received the conventional manual crimp Fisch-type prosthesis. Data were analyzed using t-test, chi-square, or two-way analysis of variance where appropriate. MAIN OUTCOME MEASURE: Operative time with ABG closure as a secondary outcome measure. RESULTS: There was a significant difference in operative time between the Fisch-type prosthesis and the SMart piston prosthesis groups. The operation required 28.9 ± 3.2 minutes when using the Fisch-type prosthesis, whereas 21.2 ± 2.4 minutes were needed when using the SMart piston (p < .001). There was a significant improvement in postoperative ABG for both the Fisch-type piston (28.1 ± 3.1 to 9.0 ± 1.4, p < .001) and the SMart piston (25.1 ± 3.7 to 8.2 ± 2.5, p < .001) groups. CONCLUSIONS: Use of the SMart piston prosthesis results in ABG closure similar to that of the traditional Fisch-type prosthesis but offers the added advantage of reduced operative time.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".