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Record W2329298601 · doi:10.1258/smj.2012.012111

Delay in diagnosis of Churg–Strauss syndrome: a case report

2012· article· en· W2329298601 on OpenAlexaff
Ankit Rana, A Adlul

Bibliographic record

VenueScottish Medical Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicVasculitis and related conditions
Canadian institutionsParkinson's Clinic of Eastern Toronto & Movement Disorders Centre
Fundersnot available
KeywordsMedicineChurg-strauss syndromeIntensive care medicineInternal medicineVasculitisDisease

Abstract

fetched live from OpenAlex

Churg-Strauss syndrome (CSS) is a well established disorder of the blood vessels. However, it is still sometimes not diagnosed early enough to avoid serious complications. It is the later stage that carries the more serious complications. Therefore, we emphasize the ways in which the diagnosis can be made early enough to avoid this stage of the disease. We report a case of CSS that was not diagnosed early and so the patient went on to develop severe cardiac and neurological manifestations. In this report we discuss the techniques and the methods to diagnose CSS and discuss their effectiveness in establishing the diagnosis. We also explore late cardiac and neurological complications because these are particularly serious complications later in the disease. We conclude that the criteria established by the American College of Rheumatology for CSS is the best tool available for early diagnosis and that late stage manifestations of CSS carry high rates of morbidity and mortality.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.127
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.015
GPT teacher head0.299
Teacher spread0.284 · 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.

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

Citations0
Published2012
Admission routes1
Has abstractyes

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