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Record W4414629814 · doi:10.58931/cct.2025.127

Role and Indications for Device Therapies in Heart Failure: Condensed Summary

2025· article· en· W4414629814 on OpenAlexafffund
Eileen O’Meara, Blandine Mondésert

Bibliographic record

VenueCanadian Cardiology Today · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsMontreal Heart Institute
FundersCanadian Cardiovascular Society
KeywordsHeart failureCardiac resynchronization therapyLeft bundle branch blockEjection fractionBundle branch blockSudden cardiac deathElectrical conduction system of the heart

Abstract

fetched live from OpenAlex

Over the past decade, the substantial benefits associated with current guideline-directed medical therapy for heart failure with reduced ejection fraction (HFrEF) have been brought into the light, as emphasized in a recent publication from our institution. Despite these advances, device therapy continues to hold an important place in treating heart failure (HF), both for left ventricular (LV) remodeling (and associated prognosis) as well as for preventing sudden cardiac death (SCD). Cardiac resynchronization therapy (CRT) is a key intervention in heart failure (HF) management, particularly for patients with left bundle branch block (LBBB), which is observed in 15–25% of patients with HF, and is associated with reduced left ventricular function. CRT helps in correcting dyssynchronous ventricular contraction leading to impaired cardiac output. Although less prevalent, right bundle branch block (RBBB) and nonspecific interventricular conduction delay (IVCD) are also associated with adverse remodelling, including increased right ventricular volumes and reduced function.

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)0.002
metaresearch head score (Gemma)0.008
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: Editorial · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.003

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 head0.013
GPT teacher head0.280
Teacher spread0.267 · 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
GenreEditorial

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

Citations0
Published2025
Admission routes2
Has abstractyes

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