MétaCan
Menu
Back to cohort
Record W2547944022 · doi:10.1097/hco.0000000000000354

Hybrid ablation for atrial fibrillation

2016· review· en· W2547944022 on OpenAlexaff
Gianluigi Bisleri, Benedict M. Glover

Bibliographic record

VenueCurrent Opinion in Cardiology · 2016
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineAtrial fibrillationAblationCatheter ablationCardiologyInternal medicinePulmonary veinAblation of atrial fibrillation

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Catheter ablation of atrial fibrillation has rapidly evolved during the past decade: although the treatment of paroxysmal atrial fibrillation via a transcatheter approach has been consistently successful, persistent and long-standing atrial fibrillation still represents a major clinical challenge with less favorable outcomes to date. Because novel, minimally invasive surgical approaches have been developed for atrial fibrillation ablation, the aim of the present review is to analyze the current evidence surrounding the integration of surgical and transcatheter strategies in a hybrid fashion for the treatment of atrial fibrillation. RECENT FINDINGS: Long-standing persistent, atrial fibrillation requires further understanding. Wide antral circumferential ablation of the pulmonary veins represents the cornerstone of any ablation therapy. Additional linear lesions and/or targeting complex fractionated atrial electrograms may also be considered. One of the limitations is achieving a transmural lesion. The combined endocardial and epicardial approach may represent a superior approach. SUMMARY: Hybrid ablation of atrial fibrillation represents a novel therapeutic strategy for the treatment of complex scenarios, such as long-standing persistent atrial fibrillation. A specialized team including dedicated surgeons and cardiologists appears to be crucial in order to achieve durable and satisfactory outcomes following hybrid ablation of atrial fibrillation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.239
GPT teacher head0.468
Teacher spread0.229 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Opinion in CardiologySame topicAtrial Fibrillation Management and OutcomesFrench-language works237,207