MétaCan
Menu
Back to cohort
Record W2005325533 · doi:10.1001/archinte.161.12.1484

Low-Molecular-Weight Heparins in the Treatment of Acute Coronary Syndromes

2001· review· en· W2005325533 on OpenAlexaff
Alexander G.G. Turpie, Elliott M. Antman

Bibliographic record

VenueArchives of Internal Medicine · 2001
Typereview
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsHamilton General Hospital
Fundersnot available
KeywordsMedicineAntithromboticHeparinLow molecular weight heparinMyocardial infarctionAcute coronary syndromeAspirinInternal medicineCardiologyAnticoagulantIntensive care medicine

Abstract

fetched live from OpenAlex

Platelet aggregation and activation of coagulation are key events in the development of acute coronary syndromes. Patients with an acute coronary syndrome are at high risk of death or myocardial infarction, and hence there is a strong rationale for the use of antithrombotic agents. Heparin has been shown to reduce the risk of death or myocardial infarction in aspirin-treated patients with acute coronary syndromes, but it has a number of limitations, including the need for regular monitoring and the risk of hemorrhage and thrombocytopenia. Low-molecular-weight heparins offer a number of practical and clinical advantages over unfractionated heparin, such as higher bioavailability and administration by subcutaneous injection. Several low-molecular-weight heparins are available that differ in their biochemical and pharmacologic properties, and it is not possible to predict their clinical efficacy from their pharmacologic profile. The decision regarding the use of a specific low-molecular-weight heparin should be based on the efficacy and safety data available for each product. In clinical trials comparing low-molecular-weight heparin with heparin, only enoxaparin sodium has been shown to reduce the risk of coronary events in patients with non-ST segment elevation acute coronary ischemia.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score0.960

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.382
Teacher spread0.340 · 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 designOther design
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

Citations31
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueArchives of Internal MedicineSame topicAcute Myocardial Infarction ResearchFrench-language works237,207