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Record W4205282777 · doi:10.31083/j.rcm2301014

Sex differences in ventricular arrhythmia: epidemiology, pathophysiology and catheter ablation

2022· review· en· W4205282777 on OpenAlexfundno aff
Philipp Krisai, Ghassen Cheniti, Takamitsu Takagi, Tsukasa Kamakura, Elodie Surget, Clémentine André, Josselin Duchâteau, Thomas Pambrun, Nicolas Derval, Frédéric Sacher, Pierre Jaı̈s, Michel Haı̈ssaguerre, Mélèze Hocini

Bibliographic record

VenueReviews in Cardiovascular Medicine · 2022
Typereview
Languageen
FieldMedicine
TopicCardiac Arrhythmias and Treatments
Canadian institutionsnot available
FundersMach-Gaensslen Foundation of CanadaUniversität Basel
KeywordsMedicinePathophysiologyCatheter ablationCardiologyEpidemiologyInternal medicineEtiologyAblationRandomized controlled trialDisease

Abstract

fetched live from OpenAlex

Evidence on sex differences in the pathophysiology and interventional treatment of ventricular arrhythmia in ischemic (ICM) or non-ischemic cardiomyopathies (NICM) is limited. However, women have different etiologies and types of structural heart disease due to sex differences in genetics, proteomics and sex hormones. These differences may influence ventricular electrophysiological parameters and may require different treatment strategies. Considering that women were consistently under-represented in all randomized-controlled trials on VT ablation, the applicability of the study results to female patients is not known. In this article, we review the current knowledge and gaps in evidence about sex differences in the epidemiology, pathophysiology and catheter ablation in patients with 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 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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.100
GPT teacher head0.354
Teacher spread0.254 · 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 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

Citations15
Published2022
Admission routes1
Has abstractyes

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