ABSTRACT
Aim of this study was to present a P-wave model, based on a linear combination of Gaussian functions, to quantify morphological aspects of P-wave in patients prone to atrial fibrillation (AF). Five-minute ECG recordings were performed in 25 patients with permanent dual chamber pacemakers. Patients were divided into high-risk and low-risk groups, including patients with and without AF episodes in the last 6 mo preceding the study, respectively. ECG signals were acquired using a 32-lead mapping system for high-resolution biopotential measurement (ActiveTwo, Biosemi, The Netherlands, sample frequency 2 kHz, 24-bit resolution). Up to 8 Gaussian models have been computed for each averaged P-wave extracted from every lead. The P-wave morphology was evaluated by extracting seven parameters. Classical time-domain parameters, based on P-wave duration estimation, have been also estimated. We found that the P-wave morphology can be effectively modeled by a linear combination of Gaussian functions. In addition, the combination of time-domain and morphological parameters extracted from the Gaussian function-based model of the P-wave improves the identification of patients having different risks of developing AF.
Subject(s)
Algorithms , Atrial Fibrillation/diagnosis , Atrial Fibrillation/physiopathology , Diagnosis, Computer-Assisted/methods , Electrocardiography/methods , Models, Cardiovascular , Pattern Recognition, Automated/methods , Aged , Artificial Intelligence , Computer Simulation , Female , Humans , Male , Models, Statistical , Normal Distribution , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
A large number of patients implanted with dual-chamber pacemakers exhibit symptoms of recurrent or new atrial fibrillation. Scheduling follow-up visits for every 6-12 months in this setting may be disadvantageous on three grounds. First, delayed information about the onset of atrial fibrillation does not allow an immediate reaction with pharmacological or dedicated pacing therapy. Second, the efficacy of the chosen therapy cannot be evaluated until the next scheduled follow-up. Third, real-time awareness of a significant atrial fibrillation burden is critical to use appropriate anticoagulation therapy for the prevention of thromboembolic events. The new Home Monitoring technology (Biotronik, Berlin) offers real-time transmission of diagnostic data stored in the pacemaker memory to the physician. This may represent a useful tool for the detection and treatment of patients with atrial fibrillation. Daily documentation of atrial rhythm via Home Monitoring allows a quick reaction to the onset of atrial fibrillation and real-time control of the therapeutic efficacy. The ongoing, international, randomized Home-PAT clinical trial aims at defining and quantifying the importance of Home Monitoring for the diagnosis and treatment of atrial fibrillation in patients with dual-chamber pacemakers.
Subject(s)
Atrial Fibrillation/diagnosis , Atrial Fibrillation/therapy , Cardiac Pacing, Artificial , Electrocardiography, Ambulatory , Pacemaker, Artificial , Telemetry , Anti-Arrhythmia Agents/therapeutic use , Atrial Fibrillation/complications , Atrial Fibrillation/drug therapy , Clinical Trials as Topic , Computer Systems , Defibrillators, Implantable , Early Diagnosis , Electrocardiography, Ambulatory/instrumentation , Humans , Telemetry/instrumentation , Telemetry/standards , Thromboembolism/etiology , Thromboembolism/prevention & controlABSTRACT
Aim of this study was to present a P-wave model, based on a linear combination of Gaussian functions, to quantify morphological aspects of Pwave in patients prone to atrial fibrillation. Five minutes ECG recordings were performed in 25 patients with permanent dual chamber pacemakers set at 40/min in order to have spontaneous beats. ECG signals were acquired using a 32-lead mapping system for high-resolution biopotential measurement (ActiveTwo, Biosemi, The Netherlands, sample frequency 2 kHz, 24 bit resolution). Four healthy subjects were also recorded as a control group. Up to 8 Gaussian models have been computed for each averaged P-wave extracted from every lead. The P-wave morphology is then evaluated by the following parameters: best model orders @ degrees of freedom adjusted R-square (AdjRsq) =97.5%; minimum (sigmamin) and maximum (sigmamax) standard deviation of the Gaussians included in the model, number of relative maxima and minima (max+min), and zeroes of the fit. Significant differences in the best model order were obtained between the control group and patients group. Accordingly, the number of relative maxima and minima was higher in the patient group. These parameters might all be markers of the fractionated electrical activity that characterizes paroxysmal AF patients in sinus rhythm.
