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Record W2047675956 · doi:10.1016/s1520-765x(01)90139-7

Issues in discharge therapy after hospitalization for UA/NSTEMI

2001· article· en· W2047675956 on OpenAlexaboutno aff
Peter J. L. M. Bernink

Bibliographic record

VenueEuropean Heart Journal Supplements · 2001
Typearticle
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineUnstable anginaMyocardial infarctionAspirinIntensive care medicineCanadian Cardiovascular SocietyAnginaInternal medicine

Abstract

fetched live from OpenAlex

New treatment guidelines for the management of unstable angina and non-ST-segment elevation myocardial infarction were recently issued by the ACC/AHA and the ESC. Both sets of guidelines include recommendations for discharge therapies, and discuss the importance of aggressive risk management, as well as the use of medications, including aspirin, β-blockers, lipid-lowering agents, and angiotensin-converting enzyme (ACE) inhibitors. These new recommendations were the subject of workshops held in September 2000, at the 4th Annual Experts' Meeting of the International Cardiology Forum. In general, workshop participants found the new ACC/AHA and ESC guidelines to be useful and consistent with practice. However, there were conflicting views on a number of topics, such as who should be treated with lipid-modifying medications, and whether the indications for ACE inhibitors should be expanded. The discussions also identified several areas of discharge management where more definitive trial data would be helpful. Some participants felt that the incremental benefit of individual agents in multidrug regimens has not yet been clearly established. There was also concern that, as the number of effective therapies increases, lack of patient compliance and financial constraints may impose greater limitations on guidelines implementation.

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)0.012
metaresearch head score (Gemma)0.038
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.012
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.038
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0100.002

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 head0.030
GPT teacher head0.326
Teacher spread0.295 · 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
GenreCommentary

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
Published2001
Admission routes1
Has abstractyes

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