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Record W4379768166 · doi:10.7759/cureus.38570

Type I Spontaneous Coronary Artery Dissection in a 33-Year-Old Male With Clinically Suspected Myopericarditis

2023· article· en· W4379768166 on OpenAlexaff
Cullen Nisson, Yeily Hernandez Mato, Nimisha Lingappa, James Abraham

Bibliographic record

VenueCureus · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Issues in Pregnancy
Canadian institutionsBrandon Regional Health Authority
Fundersnot available
KeywordsMedicineChest painInternal medicineCardiologyMyopericarditisCoronary artery diseaseAcute coronary syndromeMyocardial infarctionSurgeryPericarditis

Abstract

fetched live from OpenAlex

We report a 33-year-old male with uncontrolled type II diabetes, and tobacco and marijuana use who presented with chest pain after a night of binge drinking and vomiting. ECG changes were consistent with acute pericarditis. Troponin levels were found to be significantly elevated and rising. The patient was immediately treated with acetylsalicylic acid (ASA), morphine, nitroglycerin drip, and heparin drip. Echocardiogram showed preserved ejection fraction (EF) without effusion. Coronary angiography demonstrated a type I spontaneous coronary artery dissection (SCAD) of the mid-left anterior descending artery (LAD) without significant coronary artery disease. Diagnostic intravenous ultrasound (IVUS) confirmed a type I SCAD with penumbra and a minimal luminal area of 10 mm2 of the mid-LAD without significant luminal narrowing. Percutaneous intervention was performed with ultrasound-guided penumbra aspiration thrombectomy. Medical therapy was started with aspirin and ticagrelor, high-intensity statin, metoprolol tartrate, lisinopril, colchicine, and insulin. A biopsy or cardiac MRI was not performed due to the resolution of the patient's symptoms. We conclude that the development of a type I SCAD in this patient was multifactorial in nature, including clinically suspected acute myopericarditis, uncontrolled type II diabetes mellitus, and binge drinking associated with vomiting.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.280
Teacher spread0.264 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2023
Admission routes1
Has abstractyes

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