MétaCan
Menu
← Back to cohort
Record W2405279726 · doi:10.14740/jocmr2596w

Acute Myocardial Infarction in a 26-Year-Old Patient With Familial Hypercholesteremia

2016· article· en· W2405279726 on OpenAlexvenueno aff
Takeshi Miyayama, Shin‐ichiro Miura, Tomo Komaki, Takashi Kuwano, Joji Morii, Hiroaki Nishikawa, Keijiro Saku

Bibliographic record

VenueJournal of Clinical Medicine Research · 2016
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineCardiologyMyocardial infarctionChest painThrombolysisPercutaneous coronary interventionAcute coronary syndromeArteryST segmentCulpritDiabetes mellitusRight coronary arteryCoronary arteriesCoronary angiography

Abstract

fetched live from OpenAlex

A 26-year-old male suffered sustained chest pain. Electrocardiogram showed ST-segment elevation in the anteroseptal wall and reciprocal ST-segment change in the inferior wall. The troponin-I level and the white blood cell count were elevated. We gave a diagnosis of acute myocardial infarction. He underwent urgent coronary angiography, which revealed 90% diffuse stenosis in the middle right coronary artery and total occlusion in the proximal left anterior descending coronary artery (LAD). Since the electrocardiogram indicated that the culprit lesion was in the proximal LAD, we performed percutaneous coronary intervention. The coronary flow in the LAD was classified as thrombolysis in myocardial infarction trial 3. His coronary risk factors were obesity, smoking, family history, hypertension and diabetes, in addition to heterozygous familial hypercholesteremia (FH). Herein, we describe the case of a young patient with acute anteroseptal myocardial infarction and discuss the potential importance of controlling cholesterol levels in FH.

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.116
GPT teacher head0.465
Teacher spread0.348 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical Medicine Research→Same topicLipoproteins and Cardiovascular Health→French-language works237,207→