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Record W4415479570 · doi:10.1016/j.jaccas.2025.105782

Recurrent STEMI After Surgical Aortic Valve Replacement

2025· article· en· W4415479570 on OpenAlexaff
Shanjot Brar, Suleman Aktaa, Philipp Blanke, Janarthanan Sathananthan, John Webb

Bibliographic record

VenueJACC Case Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsAortic valve replacementAortic valveCoronary occlusionValve replacementOcclusionHemodynamics

Abstract

fetched live from OpenAlex

BACKGROUND: A 63-year-old man underwent surgical aortic valve replacement with an On-X valve using COR-KNOT suturing to facilitate a mini-sternotomy approach. CASE SUMMARY: The patient presented with recurrent inferior ST-segment elevation myocardial infarctions over a few-year period, despite optimal anticoagulation therapy. Repeated coronary angiography showed no obstructive coronary artery disease or thromboembolic occlusion. Intravascular ultrasound showed a filling defect in the ostium of the right coronary artery (RCA). A cardiac computed tomography confirmed the interference between a COR-KNOT and the RCA. Percutaneous coronary intervention of the RCA ostium was performed with good outcomes. DISCUSSION: This is the first case to report a ST-segment elevation myocardial infarction caused by an automated suturing. The combination of mini-sternotomy with COR-KNOT may have contributed to this rare but serious complication. TAKE-HOME MESSAGES: Multimodality imaging is crucial in establishing unusual diagnoses. COR-KNOT may interfere with coronary flow resulting in transient coronary occlusion when used in surgical aortic valve replacement.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
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)0.0030.001

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 head0.011
GPT teacher head0.299
Teacher spread0.288 · 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
Published2025
Admission routes1
Has abstractyes

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