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Record W2794344743 · doi:10.1093/europace/euy015.331

686Automatic AVD Programming by SyncAV Improves Electrical Synchronization in a Multicenter Study of CRT Patients

2018· article· en· W2794344743 on OpenAlexaff
Bernard Thibault, Philippe Ritter, Carlo Pappone, Kerstin Bode, Leonardo Calò, Jan O. Mangual, Nima Badie, L. Mcspadden, Niraj Varma

Bibliographic record

VenueEP Europace · 2018
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsMedicineMulticenter studySynchronization (alternating current)Internal medicineElectrical engineeringTopology (electrical circuits)

Abstract

fetched live from OpenAlex

Introduction: SyncAV, a new CRT feature that continually programs atrioventricular delay (AVD) shorter than the intrinsic AV conduction time (by a default or programmable offset), may improve electrical synchrony by fusion of intrinsic, LV-paced, and RV-paced activation wavefronts. However, it is not known how the degree of synchronization achieved depends on the LV pacing vector selected. Objective: Evaluate the electrical benefit of SyncAV by late- vs. early-activated LV pacing vectors. Methods: Ninety patients (74% male, 44% ischemic, 62% LBBB, 32±9% ejection fraction) post-CRT implant (23±28 months) using a quadripolar lead (Quartet™, Abbott) were enrolled prospectively. QRS durations (QRSd) were measured by a blinded observer from 12-lead ECG during: intrinsic conduction, biventricular pacing (BiV) + SyncAV™ OFF (sensed/paced AVD = 140/110 ms), BiV + SyncAV™ ON (nominal 50 ms offset), BiV + SyncAV™ ON (offset optimized to minimize QRSd), RV-only pacing, and LV-only pacing + SyncAV™ ON (nominal 50 ms offset). Each BiV pacing configuration used simultaneous V-V and was compared using the LV electrode along a quadripolar lead with the latest (BiVLateLV) vs. earliest (BiVEarlyLV) during RV pacing. Results: Conduction delay from RV pacing to LV sensing was significantly longer at the BiVLateLV cathode than the BiVEarlyLV cathode (174±29 vs. 154±32 ms, p<0.001). The QRSd associated with intrinsic conduction (155±29 ms) was narrowed with BiVLateLV + SyncAV OFF to 138±27 ms (9±20% reduction, p<0.001). Further QRSd narrowing to 133±25 ms (13±14% reduction, p<0.05 vs. BiV + SyncAV OFF) was achieved by BiVLateLV + SyncAV ON (nominal offset). The greatest QRSd narrowing to 123±22 ms (20±10% reduction, p<0.001 vs. BiV + SyncAV ON (nominal offset)) was achieved by BiVLateLV + SyncAV ON (optimized offset). However, there was no statistical difference between the QRSd narrowing achieved by BiVLateLV vs. BiVEarlyLV using either SyncAV offset (p=0.4-0.9). The optimal SyncAV offsets resulted in an AVD of 81.1±9.4% of the intrinsic AV interval, much longer than what is usually programmed with other optimizing methods. Expectedly, RV-only pacing actually prolonged QRSd by 10±18% relative to intrinsic conduction, and although LV-only pacing + SyncAV ON (nominal offset) narrowed QRSd by 8±16%, the reduction was no greater than BiV + SyncAV OFF with either BiVLateLV or BiVEarlyLV. Conclusion: SyncAV improves acute electrical synchrony beyond conventional CRT, particularly with patient-specific optimization, but is unaffected by the choice of LV pacing vector along a quadripolar lead (i.e., late- or early-activated). Abstract 686 Figure.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.006
GPT teacher head0.266
Teacher spread0.260 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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