Ruiter Jacob H, Mulder Elles, Schuchert Andreas, Burri Haran, Stühlinger Markus C, Hartikainen Juha, Sermasi Sergio, Vlasínová Jitka, Mairesse Georges H, Bub Eberhard, Lewalter Thorsten
Medisch Centrum Alkmaar, Alkmaar, The Netherlands.
Pacing Clin Electrophysiol. 2010 May;33(5):605-14. doi: 10.1111/j.1540-8159.2010.02689.x. Epub 2010 Feb 1.
Modern pacemakers continuously store significant cardiac-related events. Interpreting these data and reprogramming the pacemaker can be time-consuming and demands expert knowledge. A software-based expert system, the therapy advisor (TA), was developed, which analyzes stored data and provides reprogramming recommendations. This study addresses whether pacemaker experts consider the messages that are automatically generated appropriate in the management of atrial tachyarrhythmias/atrial fibrillation (AT/AF).
This observational, international, multicenter study follows 150 patients with suspected or documented atrial arrhythmias who received a dual-chamber pacemaker (model Vitatron T-70, Medtronic Inc., Minneapolis, MN, USA) incorporating the TA. The TA summarizes technical and clinical data stored in the pacemaker into key messages and may suggest programming changes. Twenty-five cardiologists examined their patients per normal practice during two follow-up visits. They reported the therapy changes they deemed necessary without initially reviewing the TA messages. Next, they rated their satisfaction with and the clinical relevance of the TA messages and recorded the final therapy changes.
The TA generated (mostly AT/AF-related) main observations in 49% and programming advice in 33% of the patients. The experts rated 95% of the TA messages as satisfactory and deemed therapy changes necessary in roughly half the patients. Pacemaker changes in AT/AF therapy or general settings were prompted primarily by the diagnostic information stored in the device. Medication changes were mostly led by the symptoms reported by the patient.
This study demonstrates that experienced cardiologists agree with 95% of the observations and programming suggestions that the TA automatically generates.
