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Record W2155390396 · doi:10.1016/j.joa.2014.03.001

Identifying atrial arrhythmias versus pacing‐induced rhythm disorders with state‐of‐the‐art cardiac implanted devices

2014· article· en· W2155390396 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Arrhythmia · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsNexen (Canada)
Fundersnot available
KeywordsMedicineCardiologyInternal medicineAtrial fibrillationTachycardiaAtrial tachycardiaArtificial cardiac pacemakerP waveCatheter ablation

Abstract

fetched live from OpenAlex

Abstract Repetitive non‐reentrant ventriculo‐atrial synchrony (RNRVAS) is a pacemaker‐induced arrhythmia that must be distinguished from atrial fibrillation (AF). Pacemaker‐induced arrhythmias are commonly detected as atrial high rate episodes (AHRE) by implanted cardiac devices. Two main types of atrial oversensing are recognized: far‐field R‐wave (FFRW) oversensing and pacemaker‐induced arrhythmias, which include pacemaker‐mediated tachycardia and RNRVAS. The presence of ventriculo‐atrial conduction is required for both types of pacemaker‐induced arrhythmias. The incidence of RNRVAS can increase with the use of various device settings and functions, such as long atrioventricular (AV) interval programming, the rate‐adaptive mode, and the atrial overdrive pacing algorithm. The negative aspects of pacemaker‐induced arrhythmias, especially RNRVAS, include (1) loss of optimal AV delay, (2) inappropriate increase in ventricular pacing, (3) induction of atrial arrhythmias, and (4) inaccurate diagnosis of AHRE. We review the incidence of arrhythmias, electrophysiological mechanisms, and the clinical diagnosis of RNRVAS identified by using dual‐chamber implantable cardiac devices.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.654

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
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 head0.019
GPT teacher head0.280
Teacher spread0.261 · 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