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Record W3103492053 · doi:10.1016/j.cjco.2020.11.006

Review of Stereotactic Arrhythmia Radioablation Therapy for Cardiac Tachydysrhythmias

2020· review· en· W3103492053 on OpenAlexaff
Michael Chiu, L. Brent Mitchell, Nicolas Ploquin, Salman Faruqi, Vikas Kuriachan

Bibliographic record

VenueCJC Open · 2020
Typereview
Languageen
FieldMedicine
TopicCardiac Arrhythmias and Treatments
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsMedicineAblationVentricular tachycardiaCardiologyCardiac AblationCatheter ablationInternal medicineRefractory (planetary science)Atrial fibrillationVentricular fibrillationCardiac arrhythmiaAblative caseCardiac electrophysiologyImplantable cardioverter-defibrillatorRadiation therapyElectrophysiology

Abstract

fetched live from OpenAlex

Cardiac tachyarrhythmias are a major cause of morbidity and mortality. Treatments for these tachyarrhythmias include antiarrhythmic drugs, catheter ablation, surgical ablation, cardiac implantable electronic devices, and cardiac transplantation. Each of these treatment approaches is effective in some patients but there is considerable room for improvement, particularly with respect to the most common of the tachydysrhythmias, atrial fibrillation, and the most dangerous of the tachydysrhythmias, ventricular tachycardia (VT) or ventricular fibrillation. Noninvasive stereotactic ablative radiation therapy is emerging as an effective treatment for refractory tachyarrhythmias. Animal models have shown successful ablation of arrhythmogenic myocardial substrates with minimal short-term complications. Studies of stereotactic radioablation involving patients with refractory VT have shown a reduction in VT recurrence and promising early safety data. In this review, we provide the background for the application of stereotactic arrhythmia radioablation therapy along with promising results from early applications of the technology.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.069
GPT teacher head0.395
Teacher spread0.327 · 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 designSystematic review
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

Citations13
Published2020
Admission routes1
Has abstractyes

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