Preliminary Development and Engineering Evaluation of a Novel Cricothyrotomy Device
Bibliographic record
Abstract
Cricothyrotomy is one of the procedures used to ventilate patients with upper airway blockage. This paper examines the most regularly used and preferred cricothyrotomy devices on the market, suggests critical design specifications for improving cricothyrotomy devices, introduces a new cricothyrotomy device, and performs an engineering evaluation of the device's critical components. Through a review of literature, manufacturer products, and patents, four principal cricothyrotomy devices currently in clinical use were identified. From the review, the Cook™ Melker device is the preferred method of clinicians but the device has acknowledged problems. A new emergency needle cricothyrotomy device (ENCD) was developed to address all design specifications identified in literature. Engineering, theoretical, and experimental assessments were performed. In situ evaluations of a prototype of the new device using porcine specimens to assess insertion, extraction, and cyclic force capabilities were performed. The device was very successful in its evaluation. Further discussion focuses on these aspects and a comparison of the new device with established devices. The proposed emergency needle cricothyrotomy device performed very well. Further work will be pursued in the future with in-vitro and in-vivo with canine models demonstrates the capabilities of the ENCD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".