Role of Surface Electrocardiograms in Patients with Cardiac Implantable Electronic Devices

Surface electrocardiograms, both resting 12-lead electrocardiographs and ambulatory electrocardiograph monitoring, play an essential role in establishing indications for cardiac implantable electronic devices (pacemakers, cardiac implantable defibrillators, and cardiac resynchronization therapies), and in the evaluation of patients already implanted. Current devices have prolonged memory capabilities (defined as Holter functions) and remote monitoring functions, to evaluate the electrical properties and the automatic detection of arrhythmias. Nonetheless, surface electrocardiography remains the critical tool to detect device malfunction, evaluate programming and function, verify the automatic arrhythmia analysis and the delivered electric therapy, and prevent inappropriate intervention.

The reverse mode switch algorithm: how well does it work?

BACKGROUND

The performance of the Reverse Mode Switch (RMS) algorithm, aimed at minimizing right ventricular pacing by operating in the AAI(R) mode with switch to the DDD(R) mode if atrioventricular (AV) conduction loss is detected, is not well known.

OBJECTIVE

To determine the appropriateness of the RMS episodes available from patient follow-up data at our center.

METHODS

Patients with the TELIGEN dual-chamber implantable cardioverter-defibrillator and the RMS algorithm activated were identified. The RMS episodes with available electrograms were analyzed and classified as appropriate (AV conduction loss) or inappropriate (non-AV conduction loss) events. Cumulative percentage of ventricular pacing and amount of premature ventricular complexes (PVCs) were recorded.

RESULTS

Of 21 patients, RMS episodes had occurred in 19 of them, with a mean of 527 episodes per month. Of the 172 RMS episodes available for analysis, 27 (16%) were classified as appropriate and 145 (84%) as inappropriate. Almost all (91%) inappropriate RMS episodes were due to PVC, and there was a positive correlation between the number of total RMS episodes per month and the number of PVCs per month (P < .0005). Considering patients with only inappropriate RMS episodes (n = 11), there was a positive correlation between the percentage of ventricular pacing and the number of RMS episodes per month (P < .05).

CONCLUSIONS

A large majority of the RMS episodes available for analysis inappropriately triggered switch from the AAI(R) mode to the DDD(R) mode owing to PVCs. Patients with the RMS algorithm and elevated PVC burden are probably at risk of a high percentage of unnecessary right ventricular pacing.