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Record W2257159382 · doi:10.1186/s40463-016-0121-y

Upper airway obstruction due to a change in altitude: First report in fifty years

2016· article· en· W2257159382 on OpenAlexaff
Oleksandr Butskiy, Donald W. Anderson

Bibliographic record

VenueJournal of Otolaryngology - Head and Neck Surgery · 2016
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Anomalies
Canadian institutionsStornoway Diamond (Canada)Vancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsAirway obstructionAirwayAltitude (triangle)MedicineSurgeryMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: Air travel mostly causes minor ear, nose and throat complaints. We describe a second report in literature of airway obstruction caused by a drop in atmospheric pressure during a routine commercial flight. CASE PRESENTATION: A 54-year-old male was referred to a head and neck surgeon with a 2 cm left submandibular mass that would enlarge during commercial flights. As the plane gained elevation, the mass would grow and cause him to become stridorous and short of breath. The shortness of breath and stridor would only resolve upon landing of the plane. A CT scan showed a large air sac extending from the larynx at the level of the true vocal cords up to the angle of the mandible. Based on the history and the CT findings a diagnosis of a laryngocele was made. The laryngocele was excised using an external approach, resolving the patient's difficulty with flying. CONCLUSION: This article reports a rare case of upper airway obstruction caused by atmospheric pressure changes during air travel. The reported case is of significance as only a few uncomplicated laryngoceles have been reported to cause airway distress in the literature. This report highlights the epidemiology, presentation, complication and management of laryngoceles.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.028
GPT teacher head0.289
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2016
Admission routes1
Has abstractyes

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