Use of Sonography for Airway Assessment
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to evaluate the feasibility of sonography in identifying the anatomic structures of the upper airway and to describe their appearance on sonography. METHODS: We enrolled 24 healthy volunteers, placed them supine with their head extended and neck flexed (the "sniffing" position), and performed a systematic sonographic examination of their upper airway from the floor of the mouth to the suprasternal notch. RESULTS: We were able to visualize all relevant anatomic structures in all of the participants using either a linear or curved transducer oriented in 1 of 3 planes: sagittal, parasagittal, and transverse. Bony structures (eg, the mandible and hyoid) were brightly hyperechoic with an underlying hypoechoic acoustic shadow. Cartilaginous structures (eg, the epiglottis, thyroid cartilage, cricoid cartilage, and tracheal rings) were hypoechoic, and their intraluminal surface was outlined by a bright air-mucosa interface. The vocal cords were readily visualized through the thyroid cartilage. However, the posterior pharynx, posterior commissure, and posterior wall of the trachea could not be visualized because of artifacts created by an intraluminal air column. CONCLUSIONS: Sonography of the upper airway is capable of providing detailed anatomic information and has numerous potential clinical applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.004 | 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".