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Intravenous antiarrhythmic agents

2001· review· en· W2070916339 on OpenAlexaff
Arnold Pintér, Paul Dorian

Bibliographic record

VenueCurrent Opinion in Cardiology · 2001
Typereview
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsMedicineBretyliumAmiodaroneIbutilideProcainamideCardiologyDofetilideSinus rhythmDefibrillationFlecainideCardioversionInternal medicineLidocaineSotalolAntiarrhythmic agentVentricular tachycardiaAnesthesiaVentricular fibrillationAtrial fibrillationAdrenergicHeart disease

Abstract

fetched live from OpenAlex

Intravenous antiarrhythmic drugs can be used as diagnostic tools; for example, adenosine can be used to reveal the underlying rhythm in narrow QRS tachycardia. Newer class III antiarrhythmic agents, like ibutilide and dofetilide, are effective at the conversion of acute atrial fibrillation; however, electrical cardioversion is still the most effective method for restoration of sinus rhythm in persistent atrial fibrillation. Lidocaine and bretylium in the treatment and prevention of ventricular tachyarrhythmia are de-emphasized because of inefficacy, safety concerns (lidocaine), or shortage of drug (bretylium). Procainamide is effective for stable ventricular tachycardia, and amiodarone is effective in the treatment of shock-refractory ventricular fibrillation. Adrenergic blockade is likely important in the management of tachyarrhythmias, particularly in electrical storm, but more data will be necessary to establish its role.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.095
GPT teacher head0.403
Teacher spread0.308 · 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 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

Citations14
Published2001
Admission routes1
Has abstractyes

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