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Record W2330803558 · doi:10.1097/hco.0b013e32835b59db

Electrical storm

2012· review· en· W2330803558 on OpenAlexaff
Dongsheng Gao, John L. Sapp

Bibliographic record

VenueCurrent Opinion in Cardiology · 2012
Typereview
Languageen
FieldMedicine
TopicCardiac Arrhythmias and Treatments
Canadian institutionsSaint Mary's UniversityQueen Elizabeth II Health Sciences Centre
Fundersnot available
KeywordsMedicineVentricular tachycardiaCatheter ablationIntensive care medicineTachycardiaStormPsychological interventionRefractory (planetary science)Implantable cardioverter-defibrillatorCardiologyAblationPsychiatry

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: With increasing use of implantable cardioverter defibrillators, physicians are increasingly called upon to manage recurrent ventricular tachycardia, sometimes in the form of frequent recurrences known as electrical storm (or ventricular tachycardia storm). RECENT FINDINGS: Standard antiarrhythmic drug therapy may suppress storms, but, when refractory, interventions such as catheter ablation or in some cases surgical cardiac denervation may be helpful. Earlier interventional management may confer better outcomes than persisting with antiarrhythmic pharmacologic therapy. SUMMARY: The clinical syndrome of electrical storm has been defined empirically. An outcome-derived definition may better guide clinicians on when and how to treat this emergent problem. When available, an early interventional approach is preferred.

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 score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.175
GPT teacher head0.444
Teacher spread0.269 · 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

Citations66
Published2012
Admission routes1
Has abstractyes

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