Innovations in pacing technology, which include the addition of rate-responsive features to programmable pacemakers, can improve the quality of life of patients suffering from sick sinus syndrome. Among the strategies providing rate-adaptive cardiac pacing, the most attractive is the physiological restoration of closed-loop chronotropic control. This paper describes how autonomic nervous system (ANS) control information is extracted from dynamic measures of myocardial contractile performance obtained from unipolar conductance measurements using the stimulation electrode in the right ventricular cavity. The pacemaker uses the ANS information to modulate pacing rate and restore normal physiological control of heart rate. A new algorithm, regional effective slope quantity (RQ), for isolating the ANS signal was developed. The resulting signal, ventricular inotropic parameter (VIP), is a normalized parameter proportional to the strength of the ANS inotropic signals to the myocardium. The efficacy of the ANS control concept was evaluated in multi-centre studies. Patients with AV block and VIP-controlled pulse generators performed defined exercise protocols. The ANS-controlled pacing rate and the spontaneous sinus rate were closely correlated. Blood pressure and subjective patient reports further indicated that good control of the cardiovascular circulation was achieved.
In 10 heart transplant patients different hemodynamic states have been forced by randomized changes of pacing rate (PR) and postural variations (overall 40, 4 k1 per patient). Cardiac output assessed with thermodilution technique was compared to the ventricular evoked response (VER) recorded with telemetric pacemakers from epimyocardial leads. Linear regression analysis between the negative extremum during the depolarization phase of the'VER (Ramp) and the stroke volume (SV=CO/PR) resulted in the equation: Rmp[%] = 140 -0.4*SV[%] with r = 0.89 and p < 0.00001.This result confirms previously reported results [I] of a distinct relation between the negative extremum of paced epimyocardial ECGs and geometrical variations of the heart. Introduction: At the Department of Transplantation, University of Graz, Austria heart transplant patients routinely receive telemetric pacemakers and epicardial leads for noninvasive patient monitoring [2]. The aim of this study has been to find out whether there is a significant correlation between the right ventricular stroke volume and the depolarization amplitude of paced epimyocardial ECGs in heart transplants. Method: Paced ECGs, so called ventricular evoked responses (VER) were recorded noninvasively using a telemetric pacemaker (Physios CTM 01, Biotronik, Germany) and epicardial leads implanted at the right ventricular outflow tract. Cardiac outputs (CO) were assessed in the course of routine endomyocardial biopsy procedure with a Cardiac Monitoring System (M1166S, Hewlett Packard, U.S.) using a Swan-Ganz catheter and the thermodilution method. Different hemodynamic states were forced by randomized changes of pacing rate and postural variations. For hemodynamic adaptation a waiting time of three minutes was applied. The CO for each hemodynamic state was measured 5 times. Mean value and standard deviation were used for further evaluation. Simultaneously, the VER was recorded. After examination standard signal analysis was performed excluding deviant events, averaging and finally calculating the negative extremum during the depolarization phase of the VER (Ramp) which corresponds to the R-wave of the surface ECG. Ramp and the averaged stroke volume (SV = COPR) were normalized to the respective mean value of each patient. Linear regression analysis between normalized SV and normalized Rmp were calculated. A p-value lower than 0.05 was assumed to be significant.Results: 10 healthy patients (age: 46 212 years) have been examined not earlier than 6 months after heart transplantation.Overall, 40 hemodynamic states (4 k1 per patient) have been assessed (a reference state for each patient as well as 18 different pacing rates and 12 different postural positions). Linear regression analysis resulted in the equation: Rmp[%] = 140 -0.4*SV[%] with r = 0.89 and p < O. OOOO1.
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