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Record W2043691394 · doi:10.2500/ajra.2009.23.3405

Chinook Wind Barosinusitis: An Anatomic Evaluation

2009· article· en· W2043691394 on OpenAlexaff
Luke Rudmik, Adam Muzychuk, Elizabeth Oddone Paolucci, Brad Mechor

Bibliographic record

VenueAmerican Journal of Rhinology and Allergy · 2009
Typearticle
Languageen
FieldMedicine
TopicSinusitis and nasal conditions
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineHeadachesChinook windSinus (botany)Concha bullosaFacial painSurgerySinusitisAnatomy

Abstract

fetched live from OpenAlex

BACKGROUND: Chinook, or föhn, is a weather phenomenon characterized by a rapid influx of warm, high-pressured winds into a specific location. Pressure changes associated with chinook winds induce facial pain similar to acute sinusitis. The purpose of this study was to determine the relationship between sinonasal anatomy and chinook headaches. METHODS: Retrospective computed tomography (CT) sinonasal anatomy analysis of 38 patients with chinook headaches and 27 controls (no chinook headaches). The chinook headache status was blinded from the CT reviewer. Forty-one sinonasal anatomy variants, Lund-Mackay status, and sinus size (cm(3)) were recorded. RESULTS: There were three statistically significant sinonasal anatomy differences between patients with and without chinook headaches. The presence of a concha bullosa and sphenoethmoidal cell (Onodi cell) appeared to predispose to chinook headaches (p = 0.004). Chinook headache patients had larger maxillary sinus size (right, p = 0.015, and left, p = 0.002). The Lund-Mackay score was higher in the control patients (p = 0.003) indicating that chronic sinusitis does not play a role in chinook headaches. CONCLUSION: Chinook winds are a common source of facial pain and pressure. This is the first study to show that sinonasal anatomic variations may be a predisposing factor. Anatomic variants may induce facial pain by blocking the natural sinus ostia, thus preventing adequate pressure equilibrium.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.303
Teacher spread0.291 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2009
Admission routes1
Has abstractyes

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