Performance evaluation of a right atrial automatic capture verification algorithm using two different sensing configurations.

• BACKGROUND: This acute data collection study evaluated the performance of a right atrial (RA) automatic capture verification (ACV) algorithm based on evoked response sensing from two electrode configurations during independent unipolar pacing. METHODS: RA automatic threshold tests were conducted. Evoked response signals were simultaneously recorded between the RA(Ring) electrode and an empty pacemaker housing electrode (RA(Ring)-->Can) and the electrically isolated Indifferent header electrode (RA(Ring)-->Ind). The atrial evoked response (AER) and the performance of the ACV algorithm were evaluated off-line using each sensing configuration. An accurate threshold measurement was defined as within 0.2 V of the unipolar threshold measured manually. Threshold tests were designed to fail for small AER (< 0.35 mV) or insufficient signal-to-artifact ratio (SAR < 2). Manual threshold measurements were obtained during RA unipolar and bipolar pacing and compared across device indications. RESULTS: Data were collected from 38 patients with RA bipolar leads from four manufacturers. AER signals were analyzed from 34 patients who were indicated for a pacemaker (five), implantable cardioverter-defibrillator (11), or cardiac resynchronization therapy pacemaker (six) or defibrillator (12). The minimum AER amplitude was larger (P < 0.0001) when recorded from RA(Ring)-->Can (1.6+/-0.9 mV) than from RA(Ring)-->Ind (1.3+/-0.8 mV). The algorithm successfully measured the pacing threshold in 96.8% and 91.0% of tests for RA(Ring)-->Can and RA(Ring)-->Ind, respectively. No statistical difference between the unipolar and bipolar pacing threshold was observed. CONCLUSIONS: The RA(Ring)-->Can AER sensing configuration may provide a means of implementing an independent pacing/sensing method for ACV in the RA. RA bipolar pacing therapy based on measured RA unipolar pacing thresholds may be feasible.

Nyckelord

Aged

Algorithms

Atrial Fibrillation

diagnosis

prevention & control

Cardiac Pacing

Artificial

methods

Diagnosis

Computer-Assisted

methods

Electrocardiography

methods

Female

Humans

Male

Pattern Recognition

Automated

methods

Reproducibility of Results

Sensitivity and Specificity

Therapy

Computer-Assisted

methods

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