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Record W2072900479 · doi:10.1001/archinte.160.6.749

Beyond Heparin and Aspirin

2000· review· en· W2072900479 on OpenAlexaff
Jeffrey I. Weitz, Shannon M. Bates

Bibliographic record

VenueArchives of Internal Medicine · 2000
Typereview
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsMcMaster UniversityMcMaster Children's HospitalHamilton General Hospital
Fundersnot available
KeywordsMedicineAspirinUnstable anginaClopidogrelFibrinHeparinDiscovery and development of direct thrombin inhibitorsPharmacologyThrombinPlateletCardiologyMyocardial infarctionLow molecular weight heparinInternal medicineImmunology

Abstract

fetched live from OpenAlex

The goals of therapy for unstable angina and non-Q-wave myocardial infarction (MI) are to maintain myocardial perfusion by inhibiting platelet aggregation and fibrin deposition at sites of plaque rupture, thereby preventing ongoing or new myocardial ischemia and cardiac death. Although aspirin and heparin sodium are cornerstones in the management of unstable angina and non-Q-wave MI, both have significant limitations that have prompted the development of new agents. The thienopyridines, ticlopidine hydrochloride and clopidogrel, appear to be at least as effective as aspirin in the management of unstable angina. Glycoprotein IIb/IIIa receptor antagonists are a new class of platelet inhibitors that are more potent than aspirin, because they target the final common pathway of platelet aggregation. Low-molecular-weight heparins provide a more stable pharmacodynamic response and are more convenient to use than unfractionated heparin. Direct thrombin inhibitors show promise for inhibiting thrombin-mediated platelet aggregation and fibrin deposition. We focus on the opportunities presented by these agents, detailing mechanisms of action, advantages over aspirin and heparin, and performance in recent clinical trials.

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 categoriesMeta-epidemiology (narrow)
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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.385
Teacher spread0.343 · 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.

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

Citations40
Published2000
Admission routes1
Has abstractyes

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