MétaCan
Menu
Back to cohort
Record W2011010298 · doi:10.1177/10742484050100i403

Antiarrhythmic Action ofβ-Blockers: Potential Mechanisms

2005· review· en· W2011010298 on OpenAlexaff
Paul Dorian

Bibliographic record

VenueJournal of Cardiovascular Pharmacology and Therapeutics · 2005
Typereview
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineBlockadeAfterdepolarizationCardiologyInternal medicineContext (archaeology)ReentryAnti-Arrhythmia AgentsRefractory periodAdrenergic beta-AntagonistsVentricular tachycardiaTachycardiaVentricular fibrillationAnesthesiaElectrophysiologyAtrial fibrillationPropranololRepolarizationReceptor

Abstract

fetched live from OpenAlex

Sympathetic nervous system overactivity has been linked to ventricular tachyarrhythmias and sudden death. It has been hypothesized that the extent and nature of the arrhythmogenic effect of sympathetic stimulation depends on the underlying myocardial substrate, the mechanism of the arrhythmia, and the integrated effects of sympathetic stimulation in the particular individual circumstance. Multiple direct and indirect mechanisms of adrenergic action on the heart may benefit from the known antiarrhythmic actions of beta-blocker therapy and other interventions that decrease sympathetic tone. The antiarrhythmic mechanism of beta-blockade (and possibly alpha-blockade) will depend on the specific mechanism of the individual arrhythmia and will differ for those arrhythmias caused by tachycardia and ischemia, those caused by reentry and promoted by decreased conduction velocity and shortened refractoriness, and those caused by early or delayed afterdepolarizations, usually in the context of prolonged action potential duration. Antagonism of cardiac adrenergic activity by beta-blockade in particular is the best-established drug therapy to prevent ventricular arrhythmias.

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)0.001
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 score0.957
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.037
GPT teacher head0.354
Teacher spread0.316 · 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

Citations62
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cardiovascular Pharmacology and TherapeuticsSame topicCardiac electrophysiology and arrhythmiasFrench-language works237,207