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Record W2095527298 · doi:10.4103/0976-3147.140005

Giant cell arteritis or tension-type headache?: A differential diagnostic dilemma

2014· article· en· W2095527298 on OpenAlexaff
Abdul Qayyum Rana, Usman Saeed, Osama Khan, Abdul Rashid Qureshi, Dion A. Paul

Bibliographic record

VenueJournal of Neurosciences in Rural Practice · 2014
Typearticle
Languageen
FieldMedicine
TopicVasculitis and related conditions
Canadian institutionsParkinson's Clinic of Eastern Toronto & Movement Disorders Centre
Fundersnot available
KeywordsGiant cell arteritisMedicineDifferential diagnosisArteritisVasculitisDiseaseDermatologyComplicationPathologyPediatricsSurgery

Abstract

fetched live from OpenAlex

Giant cell arteritis (GCA) or Temporal arteritis (TA) is an autoimmune disease and the most common type of vasculitis in the elderly. It causes inflammation of the medium and large arteries in the upper part of the body. GCA is an under-recognized cause of head aches in the elderly, especially when it presents itself with atypical features, resulting in delayed or incorrect diagnosis. Since GCA is a treatable condition, an accurate diagnosis is crucial to prevent the most serious complication of CGA, permanent vision loss. The diagnosis can be further complicated as GCA may present with features of other painful neurological conditions. The present case is an 81-year-old woman diagnosed with GCA, who initially presented with features similar to tension-type headache. Due to overlapping features of these conditions, the diagnosis of GCA was delayed, resulting in irreversible vision loss. Although previous research highlights diagnostic dilemmas featuring GCA and other disease states, this case is exclusive in describing a unique dilemma where tension-type headache mimics GCA.

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)0.008
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 score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0020.005
Open science0.0020.003
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.019
GPT teacher head0.299
Teacher spread0.280 · 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

Citations15
Published2014
Admission routes1
Has abstractyes

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