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Related Experiment Video

Updated: Dec 26, 2025

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Optimization of Chronic Cardiac Resynchronization Therapy Using Fusion Pacing Algorithm Improves Echocardiographic

Ahmed AlTurki1, Pedro Y Lima1, Martin L Bernier1

  • 1Division of Cardiology, McGill University Health Center, Montreal, Quebec, Canada.

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Reprogramming cardiac resynchronization therapy (CRT) with SyncAV algorithm significantly improved heart function. This optimization increased left ventricular ejection fraction and reduced end-systolic volume in patients with existing CRT devices.

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Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Medical Device Technology

Background:

  • Cardiac resynchronization therapy (CRT) aims to improve synchrony but its reprogramming benefits are unclear.
  • The SyncAV algorithm fuses intrinsic conduction with biventricular pacing.
  • Assessing echocardiographic improvements after SyncAV reprogramming in chronic CRT patients is crucial.

Purpose of the Study:

  • To evaluate if reprogramming existing CRT devices with the SyncAV algorithm improves echocardiographic parameters.
  • To determine the impact of SyncAV optimization on cardiac function.

Main Methods:

  • Retrospective analysis of 34 patients with implanted CRT devices programmable with SyncAV.
  • SyncAV optimization performed during routine device clinic visits.
  • Echocardiography conducted before and 6 months after SyncAV optimization.

Main Results:

  • SyncAV optimization led to a significant increase in left ventricular ejection fraction (LVEF) (30.9% to 36.5%).
  • A significant reduction in left ventricular end-systolic volume (LVESV) was observed (110.5 mL to 89.6 mL).
  • Improvements were noted in patients with chronic CRT devices compared to baseline programming.

Conclusions:

  • Reprogramming CRT devices with SyncAV significantly enhances biventricular fusion pacing.
  • This optimization improves key echocardiographic measures like LVEF and LVESV.
  • Further research is needed to confirm long-term clinical benefits and identify ideal patient candidates.