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Record W3148892002 · doi:10.12659/ajcr.929816

A Prolonged Time to Diagnosis Due to Misdiagnoses: A Case Report of an Atypical Presentation of Eagle Syndrome

2021· article· en· W3148892002 on OpenAlexaff
P Michaud, Mohamed A. Gebril

Bibliographic record

VenueAmerican Journal of Case Reports · 2021
Typearticle
Languageen
FieldMedicine
TopicOropharyngeal Anatomy and Pathologies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPresentation (obstetrics)EagleCase presentationMedicineSurgeryGeologyPaleontology

Abstract

fetched live from OpenAlex

BACKGROUND Eagle syndrome is an unusual condition in which the styloid process (SP) becomes elongated and causes different clinical symptoms due to pressure on adjacent anatomical structures. The symptoms are non-specific and include severe throat, facial, and ear pain, or headaches. They are usually exacerbated by head rotation, swallowing, yawning, or chewing, but atypical presentations exist. It is a difficult pathology to diagnose and it can take several years before a proper diagnosis is made. CASE REPORT This report describes the case of a dental student presenting with an atypical presentation of Eagle syndrome. His styloid processes were 75 mm long and he was affected with severe pain to his throat, the anterior part of his ears, his submandibular area, and his molar teeth. The pain was exacerbated during maximal mouth opening, yawning, mandibular protrusion, and during downward head tilt, but not during the classically described movements of head rotation, swallowing, yawning, or chewing. Due to the absence of the classic symptoms, even with knowledge of the condition and unusual direct access to several oral and maxillofacial specialists, it took 4 years and multiple misdiagnoses to reach the final diagnosis. Following bilateral styloidectomy, all pain subsided. CONCLUSIONS The clinical presentation of Eagle syndrome varies, and the symptoms are non-specific. This greatly increases the complexity of diagnosing the condition and raises the time to diagnosis and the chances of misdiagnoses. It is, therefore, crucial to recognize the diagnostic tools, applicable imaging, and definitive treatment alternatives to successfully identify and treat patients affected.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.007
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0040.002
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0070.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.308
Teacher spread0.294 · 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

Citations12
Published2021
Admission routes1
Has abstractyes

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