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Record W2786412880 · doi:10.14740/cr654w

Massive Hemorrhagic Pericardial Effusion With Cardiac Tamponade as Initial Manifestation of Mixed Connective Tissue Disease

2018· article· en· W2786412880 on OpenAlexvenueno aff
Ashraf Abugroun, Osama Hallak, Fátima Ahmed, Safwan Gaznabi

Bibliographic record

VenueCardiology Research · 2018
Typearticle
Languageen
FieldMedicine
TopicPericarditis and Cardiac Tamponade
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCardiac tamponadePericardial effusionMixed connective tissue diseasePericarditisTamponadePericardial fluidCardiologyInternal medicinePericardial windowConnective Tissue DisorderConnective tissuePathologyDisease

Abstract

fetched live from OpenAlex

Mixed connective tissue disease (MCTD) is a distinct entity of connective tissue disorders characterized by overlapping clinical features of various autoimmune diseases along with the presence of antibodies to ribonucleoprotein (anti-RNP). The prevalence of cardiac involvement in MCTD varies from 13% to 65% and accounts for approximately 20% of MCTD related mortality. In this case, we describe an elderly female patient with multiple complaints without a clear etiology on presentation. Echocardiogram revealed severe rapidly accumulating pericardial effusion causing tamponade necessitating pericardial window. Laboratory investigations showed positive ribonucleoprotein antibodies. Biopsy of pericardial tissue revealed fibrinous pericarditis. While pericarditis is commonly associated with MCTD, pericardial tamponade on the other hand is rarely described. This case highlights a very rare complication of the disease. Early recognition, prompt treatment, and regular follow-up with serial echo are essential for treatment.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
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 head0.040
GPT teacher head0.397
Teacher spread0.357 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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