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Record W2899819524 · doi:10.4236/wjcd.2018.811049

Myocardial Infarction: An Overview of STEMI and NSTEMI Physiopathology and Treatment

2018· article· en· W2899819524 on OpenAlexaff
John G. Kingma

Bibliographic record

VenueWorld Journal of Cardiovascular Diseases · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Ischemia and Reperfusion
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMedicineCardiologyMyocardial infarctionInternal medicinePerfusionAcute coronary syndromePercutaneous coronary interventionPercutaneous

Abstract

fetched live from OpenAlex

Patients with myocardial infarction resulting from acute coronary syndrome are classified by electrocardiographic presentation: 1-acute ST-segment elevation myocardial infarction (STEMI) or 2-non-ST-segment elevation myocardial infarction (NSTEMI). Prompt reperfusion of an infarct-related artery by percutaneous coronary interventions provides some relief of symptoms; long-term prognosis appears to be worse in STEMI compared to NSTEMI patients but clinical findings remain controversial. Reduced myocardial perfusion to the infarct area, caused in part by microvascular obstruction, is a privileged target for diverse pharmacologic or non-pharmacologic interventions (or combinations thereof) to improve clinical outcomes. To date, benefits of both pharmacologic and non-pharmacologic strategies to either limit microvascular obstruction and myocardial injury or improve myocardial perfusion are inconsistent. This review focuses on the physiopathological aspects of myocardial infarction in relation to development of STEMI/NSTEMI and on potential cardioprotective strategies.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.024
GPT teacher head0.290
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 designNot applicable
Domainnot available
GenreReview

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

Citations33
Published2018
Admission routes1
Has abstractyes

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