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Record W2799703539 · doi:10.14740/cr661w

Coronary Artery Thromboses, Stent Thrombosis and Antiphospholipid Antibody Syndrome: Case Report

2018· article· en· W2799703539 on OpenAlexvenueno aff
Augusto Ferreira Correia, Dinaldo Cavalcanti de Oliveira, Marcio Sanctos

Bibliographic record

VenueCardiology Research · 2018
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCardiologyInternal medicineThrombosisMyocardial infarctionCoronary artery diseaseAcute coronary syndromeWarfarinAntiphospholipid syndromeArteryStentAnticoagulantAtrial fibrillation

Abstract

fetched live from OpenAlex

The antiphospholipid antibody syndrome (APS) is defined by a state of hypercoagulability secondary to an autoimmune disorder. There are evidences that approximately 2.8-5.5% of cases of acute myocardial infarction (AMI) in young individuals are secondary to APS. In this case report, three coronary artery thromboses occurring within a short period are described. Initially, there was an ST-segment elevation (STEMI) in the presence of coronary artery disease (CAD), with the vessel being treated with stent implantation. Thereafter, a subacute stent thrombosis occurred (high thrombotic load in almost all coronary arteries), which was treated with implantation of two stents. Subsequently, there was a new infarction owing to a new thrombosis in the native coronary artery. The treatment of APS in patients who developed thrombotic events is full anticoagulation from the initial stages maintained throughout life. The standard anticoagulant therapy is administration of vitamin K antagonists, such as warfarin.

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)0.003
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 score0.010
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0040.002
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0100.005
Insufficient payload (model declined to judge)0.0040.002

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 head0.116
GPT teacher head0.431
Teacher spread0.316 · 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

Citations18
Published2018
Admission routes1
Has abstractyes

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