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Record W4405667058 · doi:10.14740/jmc4311

Gastric Antral Vascular Ectasia Syndrome With Aortic Stenosis: A Twist on Heyde Syndrome?

2024· article· en· W4405667058 on OpenAlexvenueno aff
Lefika Bathobakae, Noman Khalid, Sacide S. Ozgur, Devina Adalja, Rajkumar Doshi, Gabriel Melki, Kamal Amer, Yana Cavanagh, Walid Baddoura

Bibliographic record

VenueJournal of Medical Cases · 2024
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Bleeding Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEctasiaGastric antral vascular ectasiaStenosisCardiologyInternal medicineEndoscopyArgon plasma coagulation

Abstract

fetched live from OpenAlex

Heyde syndrome is a triad of aortic stenosis (AS), gastrointestinal (GI) bleeding from angiodysplasia, and acquired von Willebrand disease (vWD). It is hypothesized that stenotic aortic valves cleave von Willebrand factor (vWF) multimers, predisposing patients to bleeding from GI angiodysplasias. This hypothesis is supported by the observation that aortic valve replacement often leads to the resolution of GI bleeding. Heyde syndrome is typically described in the context of AS and small bowel angiodysplasias (Dieulafoy's lesion, intestinal vascular malformation, and arteriovenous malformations). However, data on AS and gastric antral vascular ectasia (GAVE) association are scarce. GAVE is a vascular anomaly characterized by ectatic capillaries, arterioles, and venules, which can lead to upper GI bleeding. The paucity of data on GAVE-AS association may lead to underdiagnosis and/or under-reporting. Herein, we describe two cases of GAVE-AS that were diagnosed and treated at our institution. This case series focuses on patient presentations and clinical outcomes and aims to raise awareness about this rare association.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
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)0.0020.000

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 head0.021
GPT teacher head0.287
Teacher spread0.266 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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