Design, prototype development and pre-clinical validation of a novel instrument with a compliant steerable tip to facilitate endoscopic ear surgery
Bibliographic record
Abstract
This work presents the design of a novel compliant steerable tip (CST) instrument to facilitate transcanal (or totally) endoscopic ear surgery (TEES). The evolution of the instrument’s design is shown, where prototypes were evaluated by surgeons and their feedback was used to inform the design changes for the next prototype iteration. The final prototype enables the surgeon to articulate the compliant tip to achieve the desired bending curvature while automatically locking in place and providing dissection and suction capabilities. Pre-clinical validation testing was performed in goat and human cadaver models by two surgeons who successfully removed an allograft from the middle ear. Time and the number of blockages while suctioning saline in both cadaver models were measured and compared with current instruments used during TEES. The CST took significantly less time to suction saline within a flooded middle ear compared to the Panetti suction dissector (PSD) for atticus and underwent less blockages than the PSD for atticus, ear drum and sinus tympani instruments, Wilcoxon Method p < .05. Our study demonstrates the development and successful clinical evaluation of a minimally invasive surgical instrument designed to facilitate endoscopic approaches to the ear.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".