Clinical Results of Automatic Slope Adaptation in a Dual Sensor VVIR Pacemaker

Manual slope programming in rate adaptive pacemakers can be time consuming. This may become worse with dual sensor devices. The remedy is to let the pacemaker automatically learn the slopes. Fast learning replaces initial manual slope programming. Daily learning is a continuous process to determine and optimize slopes during daily life. Both methods are known for a QT sensing pacemaker. Fast learning is known for other single sensor devices. The aim of this study was to follow daily learning in a QT and activity dual sensor pacemaker, starting with factory slope settings. Six patients were studied for about 8 weeks. The daily learning algorithm appeared to be elective, showing the desired regulation processes. It took 2–5 weeks to reach full rate response.     

Individual optimization of pacing sensors improves exercise capacity without influencing quality of life

INTRODUCTION: Programmable pacemaker sensor features are frequently used in default setting. Limited data are available about the effect of sensor optimization on exercise capacity and quality of life (QOL). Influence of individual optimization of sensors on QOL and exercise tolerance was investigated in a randomized, single blind study in patients with VVIR, DDDR, or AAIR pacemakers. METHODS: Patients with > or =75% pacing were randomized to optimized sensor settings (OSS) or default sensor setting (DSS). Standardized optimization was performed using three different exercise tests. QOL questionnaires (QOL-q: Hacettepe, Karolinska, and RAND-36) were used for evaluation of the sensor optimization. One month before and after optimization, exercise capacity using chronotropic assessment exercise protocol and the three QOL-q were assessed. RESULTS: Fifty-four patients (26 male, 28 female) with a mean age of 65 +/- 16 years were enrolled in the study. In each group (OSS and DSS) 27 patients were included. One month after sensor optimization, the achieved maximal heart rate (HR) and metabolic workload (METS) were significantly higher in OSS when compared with DSS (124 +/- 28 bpm vs 108 +/- 20 bpm, P = 0.036; 7.3 +/- 4 METS vs 4.9 +/- 4 METS, P = 0.045). Highest HR and METS were achieved in patients with pacemakers with accessible sensor algorithms. In patients with automatic slope settings (33%), exercise capacity did not improve after sensor optimization. QOL did not improve in OSS compared with DSS. CONCLUSION: After 1 month of individual optimization of rate response pacemakers, exercise capacity was improved and maximum HR increased, although QOL remained unchanged. Accessible pacemaker sensor algorithms are mandatory for individual optimization.     

Clinical Evaluation of a Dual Sensor, Rate Responsive Pacemaker

Dual sensor pacemakers should respond more appropriately during differing exercise modes than a single sensor device. The Topaz™ models 515 (QT and activity count [ACT] sensing) pacemaker shows appropriate rate response during treadmill exercise testing. We postulated that adjustments to relative sensor contribution should allow fine tuning of the onset of rate response. Eleven patients with this pacemaker were studied. Three standard exercise tests were performed with adjustment of sensor blending and activity threshold between each one. We also assessed the response to isometric exercise and a false positive activity signal. Results : Times to 100 ppm (3.7 ± 1.3, 4.4 ± 2.0, 5.3 ±1.5 mins), times to peak rate (6.1 ± 1.6, 5.6 ± 1.4, 6.5 ± 1.3 mins) and accelerations to peak (9.0 ± 2.4, 9.2 ± 5.3, 7.7 ± 2.8 ppm/min) were measured in all three different sensor settings (QT = ACT, QT 相似文献   

Clinical Experience with an Activity Sensing DDDR Pacemaker Using an Accelerometer Sensor

The rate adaptive characteristics and pacemaker mediated tachycardia protection algorithm of an accelerometer based DDDR pacemaker were evaluated in 11 patients with bradycardia (seven atrioventricular block, four sick sinus syndrome). Rate adaptive programming was effected by collecting the acceleration level during a 3-minute moderate exercise ("tailoring" of sensor). In comparison with an externally attached piezoelectric sensor, the accelerometer sensor showed lower rate changes during external tapping of the pacemaker (16 +/- 3 vs 29 +/- 4 ppm, P less than 0.02) and applied direct pressure (1 +/- 1 vs 40 +/- 3 beats/min, P less than 0.001) on the pacemaker. At nominal setting, the accelerometer sensor showed improved rate stability and higher rate response to jogging and standing, although responses to other daily activities and treadmill exercise were similar. Apart from changing the rate responsive slope, rate response could be improved by repeat "tailoring" of the sensor at a lower exercise level, resulting in better overall rate response characteristics. The ability of the rate monitoring software to collect acceleration levels for an activity and profile the projected rate response at different rate responsive settings allowed programming to be effected with the minimum amount of exercise testing. The pacemaker also discriminated atrial tachyarrhythmias from normal sinus response using the sensor to judge the appropriateness of the atrial rate, which correctly identified and prevented rapid ventricular tracking in two patients during atrial flutter/fibrillation.     

New Algorithms to Increase the Initial Rate Response in a Minute Volume Rate Adaptive Pacemaker

Background : Minute volume is a truly physiological sensor for rate adaptive pacing that correlates with metabolic expenditure throughout the range of physical activity. Criticism has centered on the slow initial response compared to less physiological sensors. A new algorithm, consisting of rate augmentation factor and programmable speed of response, has been incorporated in the 1206 META III pacemaker generator and was designed to improve the rate response at lower levels of exertions. Rate augmentation factor increases the programmed rate response factor by 3, 6, or 10 when set to low, medium, or high, respectively; this augmentation lasting to 50% of the maximum programmed rate. Response time can be programmed to medium or fast. Methods : Nine patients were studied during the first 3 minutes of an exercise test (Bruce protocol) in a single blind manner. The pacemaker generator was randomly programmed with rate augmentation factor at off, low, or high and speed of response to medium or fast, giving six possible combinations. Heart rates were recorded continuously for the duration of the test and until resting heart rate was achieved during recovery. The test was repeated until all six combinations had been tested. Results : During exercise significant differences appeared in response time from 30 seconds onward. Fast response and rate augmentation factor contributed to an improved rate response with greatest speed of response seen with fast response time and high rate augmentation factor. During recovery decreases in recovery time were seen with fast response time but rate augmentation factor prolonged recovery. Conclusions : Rate augmentation factor improves initial rate response in the early stages of exercise. Fast response gives an improved time to initial rate increase and shortens the duration of inappropriate postexercise tachycardia. These features improve the pattern of response of the minute ventilation sensor.     

Effects of Sensor Selection on Exercise Stroke Volume in Pacemaker Dependent Patients

The effects of sensor selection and sensor blending on the cardiovascular response to graded exercise was evaluated in 10 patients (age 74 ± 2 yrs; 7 men and 3 women) implanted with a dual sensor rate adaptive VVIR pacemaker (Vitatron Topaz(tm) model 515). Patients underwent three graded exercise tests (GXT) with sensor programming randomly assigned. For a given graded exercise text the pacemaker was programmed into activity sensing (ACT), QT sensing, or dual sensing (ACT = QT). Data were recorded at rest and during each stage of the graded exercise text. Oxygen uptake (VO₂) was measured continuously using a Q Plex I system. Heart rate (HR), stroke volume (SV), and cardiac output (Qc) were measured by impedance cardiography. Systolic time intervals were calculated from simultaneous recordings of the ECG. phonocardiogram, and the impedance cardiogram. In response to the GXT no differences in peak VO₂ were observed across the three sensor settings. Regardless of the sensor setting Qc increased linearly with each increment in VO₂. The HR response to ACT only pacing was significantly higher than in the other two pacing conditions. During ACT only pacing SV failed to rise in response to exercise. The increased exercise Qc during QT and ACT = QT pacing were mediated by significant increases in both HR and SV. The QT and dual pacing conditions were also associated with longer diastolic filling times. The data indicate that the mechanisms responsible for the increase Qc during exercise were different for ACT versus ACT = QT or QT sensor-driven pacing.     

A blended sensor restores chronotropic response more favorably than an accelerometer alone in pacemaker patients: the LIFE study results

Background: Adaptive rate sensors used in permanent pacemakers incorporate an accelerometer (XL) to increase heart rate with activity. Limited data exists regarding the relative benefit of a blended sensor (BS) (XL and minute ventilation) versus XL alone in restoring chronotropic response (CR) in chronotropically incompetent (CI) patients. Methods: One thousand five hundred thirty‐eight patients from the limiting chronotropic incompetence for pacemaker recipients (LIFE) study were implanted with a pacemaker and 1,256 patients had data collected at 1 month. Patients performed a treadmill test 1‐month postimplant while programed in nonrate responsive mode (DDD‐60) to determine CI. Only patients who completed at least three exercise stages and achieved a peak perceived exertion ≥16 were included in the analyses. The metabolic chronotropic relationship (MCR) slope was used to evaluate CR in 547 patients. Patients were randomized to XL or BS with a conservative fixed rate response factor (XL = 8, MV = 4). CI patients performed a follow‐up 6‐month treadmill test. Results: CI prevalence in this patient population (n = 547) was 34%. No differences in baseline characteristics existed between groups. Although both groups showed significant within‐group improvements in MCR slope from 1 to 6 months (both P < 0.001), the BS group had a significantly higher MCR slope at 6 months compared to the XL group (P = 0.011). Improvement in quality of life (QOL) did not differ between groups . Conclusions: In this general pacemaker population with CI, a BS programed empirically restores CR more favorably than an XL sensor programed nominally. Further studies are needed to determine if individual sensor optimization would lead to improvement in functional capacity, higher MCR slopes, and QOL.     

The Influence of Sensor Orientation on Activity-Based Rate Responsive Pacing

Piezoelectric activity-based rate responsive pacemakers are commonly implanted with the sensor facing inward. This study was conducted to assess the safe and effective rate response of an activity-based rate responsive pacemaker implanted with the sensor facing outward. A comparison were made to a previously studied patient group with sensor facing inward. Patient and pacemaker data was collected at pre-discharge and 2-month follow-up. Two-minute hall walks in conjunction with programmer-assisted rate response assessment were utilized to standardize initial rate response parameter settings for both patient groups. At 2-month follow-up, sensor rate response to a stage 3 limited CAEP protocol was recorded. Adequate sensor rate response was achieved for both patient groups. No difference was noted in reported patient complications for both groups. A statistically significant difference in programmed rate response curve setting and activity threshold for the two groups was noted at 2-month follow-up. Adequate sensor rate response was achieved for a patient population implanted with an activity-based rate responsive pacemaker with sensor facing outward. In this orientation, one higher rate response curve setting and an activity threshold one value more sensitive were required on average when compared to the normal sensor-orientation group.     

Delayed Exercise Rate Response Kinetics Due to Sensor Cross-Checking in a Dual Sensor Rate Adaptive Pacing System: The Importance of Individual Sensor Programming

By cross-checking the relative sensor activation between a nonspecific and specific sensor during extraneous interference, a multisensor rate adaptive pacemaker may he able to limit inappropriate rate responses. The effects of activity (ACT) sensor programming on rate response kinetics of a QT and ACT dual sensor VVIR pacemaker with sensor cross-checking algorithm were studied in four patients with atrial fibrillation and complete heart block. The rate adaptive setting of each sensor was individually optimized, and an equal rate contribution for the QT and ACT sensors (QT = ACT) was used in the dual sensor VVIR mode. Three maximal treadmill exercise tests were performed in random order in three different VVIR modes driven by QT only, QT = ACT, and in the dual sensor mode with the most sensitive (low threshold) ACT setting. In the two dual sensor modes, the time for onset of rate response (delay time) was reduced (both < 15 sec) compared with QT only VVIR mode (233 ± 70 sec). However, the time to 50% of rate response in the low ACT threshold dual sensor mode was delayed compared with to QT = ACT (450 ± 110 [95% confidence interval 234–666] vs 311 ± 103 [109–513]sec, P < 0.05) and was similar to the QT only mode (401 ± 120 [l66–636]sec). The time to reach 90% of rate response was similar in the three modes tested. The resting activity counts registered by the ACT sensor were < 5 and 16 ± 2 counts/mm in the optimally programmed and low threshold ACT settings, respectively. This resulted in sensor cross-checking at rest in the overprogrammed dual sensor VVIR mode, thereby limiting the rate response. Thus, the combined sensor system provides a faster initial response to exercise than the QT only sensor. Programming the ACT threshold to low will prevent this faster response because of sensor cross-checking.     

Quantitative Comparison of Rate Response and Oxygen Uptake Kinetics Between Different Sensor Modes in Multisensor Rate Adaptive Pacing

Although multisensor pacing may mitigate the inadequacy of rate adaptation in a single sensor system, the clinical role of multisensor driven rate adaptive pacing remains unclear. The cardiopulmonary performance of six patients (mean age 63.5 ± 10 years) who had undergone the implant of combined QT and activity VVIR (Topaz®) pacemakers was assessed during submaximal and maximal treadmill exercise with the rate response sensor randomly programmed to either single sensor mode. QT and activity (ACT), or dual sensor mode, with equal contribution of QT and ACT (QT = ACT). The rate of response, the proportionality, oxygen kinetics, and maximal exercise performance of the various sensor modes during exercise were measured and compared. The ACT sensor mode “overpaced” and the QT and QT = ACT sensor modes “underpaced” during the first three quartiles of exercise (P < 0.05). The ACT sensor mode also gave the fastest rate of response with the shortest delay (13 ± 1.5 sec vs 145 ± 58 sec and 41 ± 17 sec, P < 0.05), time to 50% rate response (39 ±2.7 sec vs 275 ± 48 sec and 203 ± 40 sec, P < 0.05), and time to 90% of rate response (107 ± 21 sec vs 375 ± 34 sec and 347 ± 34 sec, P < 0.05) and a smaller oxygen debt (0.87 ± 0.16 L vs 1.10 ± 0.2 L and 1.07 ± 0.18 L, P < 0.05) compared to the QTand QT = ACT sensor modes, respectively. These differences were most significant at low exercise workloads. Thus, different sensor combinations resuh in different rate response profiles and oxygen delivery, especially during low level exercise. However, the observed oxygen kinetics difference was workload dependent, and its clinical relevance remains to be tested. Despite the marked difference in exercise rate profile and oxygen kinetics, there was no difference in the maximal oxygen uptake, anaerobic threshold, and exercise duration between the various sensor modes during maximal exercise.     

Rate Responsive Cardiac Pacing Using a Minute Ventilation Sensor

A minute ventilation sensing rate responsive pacemaker was implanted in 15 patients (8 males and 7 females)with bradycardia. The mean age was 72.8 ± 8.7 years. The single chamber system measures transthoracic impedance between the tip electrode of a standard bipolar lead and the pulse generator case. In the adaptive mode the pulse generator calculates a rate responsive factor or slope during maximal exercise but /unctions as in the VVI mode. The patients exercised maximally on an upright cycle ergometer with the pacemaker programmed to VVI mode, adaptive mode, and rate responsive mode. Exercise and gas exchange data were collected continuously and analyzed using an automated breath-by-breath system. The slope, heort rate, and ventilation were measured every 20 seconds. Heart rate in pacemaker dependent patients correlated well to minute ventilation (correlation coefficient ranging from 0.72–0.95, P < 0.0001). This study demonstrates that minute ventilation is a good metabolic sensor in rate responsive pacing.     

Clinical Study of a New Activity Sensor for Rate Adaptive Pacing Controlled by Electrical Signals Generated by the Kinetic Energy of a Moving Magnetic Ball

A new rate adaptive pacemaker (Sensorithm) controlled by an activity sensor providing electrical signals induced by a magnetic ball moving freely in an elliptical cavity surrounded by two copper coils, was implanted in ten patients; mean age of 75 years (range 64–89). Six patients had atrioventricular block and four had sinus node disease. In auto-set testing procedure during a 1-minute walk in the corridor, a slope resulting in a maximum rate of 95 beats/min was selected in every patient, and a medium reaction time was programmed. During graded treadmill exercise tests the heart rate increased 63 ± 7 beats/min to 135 ± 6 beats/min in rate adaptive pacing mode (VVIR), and 15 ± 6 beats/min (P < 0.0001) in ventricular pacing mode (VVI). The symptom-limited exercise time was 9.1 ± 1.1 minutes and 8.2 ±1.2 minutes (P = NS), and the exercise distance was 501 ± 95 meters and 428 ± 92 meters (P < 0.05) in VVIR and VVI pacing mode, respectively. The maximum oxygen uptake was 20.6 ± 2.6 mL/kg per minute in VVIR pacing and 18.1 ± 2.1 mL/kg per minute (P < 0.05) in VVI pacing. The delay time until the pacing rate increased 10% of the total rate increase at onset of treadmill exercise was 4.4 ± 0.7 seconds. Assuming a linear relation between metabolic workload and heart rate response from rest to the age predicted maximum heart rate, a deviation of heart rate ranging from 13.5 ± 11.2% to –1.6 ± 5.2% from the expected heart rate at mid-point and endpoint of each quartile of workload was observed during treadmill testing. Conclusions : By using a 1 -minute walk test for selecting an appropriate slope setting, Sensorithm provided a significant and proportional heart rate increase during exercise resulting in an improvement of exercise capacity during VVIR pacing compared to VVI pacing.     

Usefulness and Adequacy of Sensor Data Storage and Retrieval for Rate Response Simulation

The usefulness of sensor data storage for rate response simulation was evaluated using a new dual chamber rate modulated pacemaker sensitive to acceleration forces (Relay 294–03 [lntermedics Inc.]). The pacemaker can store the sensor output during routine exercise and those values can be used to simulate rate profiles for other rate response settings. The predictive value of this feature was evaluated in three studies (mechanical, external pacemaker, and implanted pacemaker). In the first study, the pacemaker was submitted to three runs of eight different mechanical calibrated to-and-fro movements. In the second study, nine external pacemakers were strapped on healthy volunteers who performed three jogging tests. Finally, the predictive value of the simulation was studied in five implanted patients during three successive walking tests. In each study, the pacemaker was submitted three times to the same activity. The responsiveness was successively set to 5, 1, and 10, and the pacemaker outputs were continuously recorded on a Holter monitor. At the end of the first run, rate profile simulations for slopes 1 and 10 were performed; slope 5 rate response was simulated after the second run. A regression analysis was used to establish the correlation between predicted and achieved pacing rates for each study. The coefficients of correlation between predicted and measured pacing rates for the mechanical, external, and clinical studies were 0.999, 0.985, and 0.823, respectively. The corresponding slopes of regression lines were 1.005, 0.971, and 0.935. Calculated rate profile has a high predictive value and could be used to optimize rate responsive settings without serial exercise testings.     

Initial Experience with a New Single Chamber, Dual Sensor Rate Responsive Pacemaker

In August 1991, a new single chamber pacemaker became available that utilizes information from two sensors, activity and stimulus-to-T wave (QT) interval. We are reporting on the first 90 implants in 21 centers. T wave sensing was adequate at implantation in 88/90 patients, with a safety margin of > 100% in 86/90, Activity sensing was adequate in all patients. The contribution of each sensor fsensor blending) is programmable for each patient. Of 75 patients assessed at 1 month after implant, three have been programmed to "Activity-Only" mode, and 72 to dual sensor mode. Of these, 18 have been programmed to "QT < Activity," 48 to "QT = Activity," and 6 to "QT > Activity." Forty-five patients underwent exercise testing in dual sensor mode and a subgroup of 15 also underwent exercise testing in Activity-Only mode. The dual sensor mode produced a more gradual increase in pacing rate. Sensor Cross Checking^tmsatisfactorily prevented a sustained high pacing rate in tests of false-positive activity sensing (tapping, vibrating pacemaker, or static pressure). The maximum pacing rate on walking downstairs (94.2 ± 7.2 ppm) was similar to that produced by walking upstairs (91.6 ± 5.9 ppm). We conclude that initial assessment of this dual sensor, single chamber, rate responsive pacemaker confirms that the algorithm for combining data from two sensors functions satisfactorily. Dual sensor rate responsive pacing may offer significant advantages over single sensor devices, and further studies of this novel device are indicated.     

Comparison of Normal Sinus Rhythm and Pacing Rate in Children with Minute Ventilation Single Chamber Rate Adaptive Permanent Pacemakers

Rate adaptive pacemakers are used to achieve a better cardiac performance during exercise by increasing the heart rate and cardiac output. The ideal rate adaptive sensor should be able to mimic sinus node modulation under various degrees of exercise and other metabolic needs. Minute ventilation sensing has proven to be one of the most accurate sensor systems. In this study, alterations in sinus rhythm and pacing rates during daily life conditions in 11 children (median age 11 years, range 6–14 years) with minute ventilation single chamber pacemakers were investigated. Correlation of sinus rhythm with pacing rates was assessed. ECG records were obtained from 24–hour Holter monitoring. Average rates of five consecutive P waves and pace waves were determined every half hour. The average of the two values was then used to determine hourly rates. Correlation coefficients between the sinus rhythm and pacing rates were calculated. In nine patients, pacing rates correlated well to sinus rhythm (range 0.6793–0.9558. P < 0.001 and P < 0.05), whereas in two cases correlation was not sufficient (P > 0.05). Most of the patients, in whom rate response factor (RRF) measurements during peak exercise by treadmill with cnronotropic assessment exercise protocol were performed and pacemakers were programmed to these parameters, had more appropriate ventricular rates compared to spontaneous sinus rates. In these patients mean RRF value was 15.3 ± 2.7 (range 12–20, median 15). This study shows that during daily activities minute ventilation rate adaptive pacemakers can achieve pacing rates well correlated to sinus rhythm that reflects the physiological heart rate in children.     

Comparison of Externally Strapped Versus Implanted Accelerometer- or Vibration-Based Rate Adaptive Pacemakers During Various Physical Activities

The ability of externally strapped accelerometer(Excel [Cardiac Pacemakers, Inc.]) and vibration-based (Activitrax [Medtronic, Inc.]) rate adaptive pacemakers to reproduce the rate response of the same implanted devices with identical programming was evaluated in ten patients by ambulatory Holter monitoring. The resting and postexercise external pacemaker rates closely resembled those of the respective implanted devices. During short bursts and more prolonged exercise, both types of strapped-on devices underestimated maximal implanted pacemaker rate response by4%-10% when programmed to nominal rate adaptive settings. Studies evaluating chronotropic responses from either type of externally strapped activity sensor appear valid, provided the modest attenuation in maximal rate increase by this method is appreciated.     

Is Accurate Rate Response Programming Necessary?

Exercise capacity and general well-being are improved by appropriately programmed rate responsive pacemakers when compared to fixed rate units. Ten patients had activity sensing DDDR units implanted for combined AV block and sinus node incompetence. Ten patients had Sensolog activity sensing VVIR units implanted for complete heart block. The effects of over and under programming of rate response in both dual and single chamber activity sensor rate adaptive pacemakers has been assessed subjectively by visual analog scales and specific activity questionnaires and objectively by graded treadmill testing and the performance of standardized daily activities. Patients were randomly programmed to absent rate response (VVI in the Sensolog group), hyporesponsive (DDD in the dual chamber group), appropriate response (VVIR, DDDR according to Manufacturer's instructions) and over responsive (VVIR+, DDDR+) in a double-blind crossover design. Thirty percent of patients demanded early crossover from VVI, 30% from DDDR+ and 50% from VVIR+. Perception of Exercise Capability was similar to objective exercise treadmill times which were shorter in VVI than in VVIR or VVIR+ (P less than 0.05) or control subjects (P less than 0.001). There was no difference between any dual chamber mode or control subjects. General well-being was poorest in DDDR+ and VVIR+ modes despite objective improvement in exercise capacity. Symptoms were least in VVIR and DDDR and all but one patient chose appropriate programming as their overall preferred mode. Thus, even inaccurate rate response programming results in similar and improved exercise capacity compared to absent rate response but overprogramming is unacceptable to most patients, confirming that appropriate programming and sensor specificity is critical in rate responsive pacing.     

Cardiac Output Is a Sensitive Indicator of Difference in Exercise Performance Between Single and Dual Sensor Pacemakers

Although multisensor pacing may compensate the inadequacy of rate adaptation in a single sensor system, the clinical role of multisensor driven rate adaptive pacing remains unclear. We compared the performance between single sensor and dual sensor driven pacemakers using exercise cardiac output (CO) as a marker of cardiac performance. Eight patients with a mean age of 63 ± 3 years implanted with a dual sensor pacemaker driven by combined activity (ACT) and QT interval sensors were studied in the ACT-, QT- only and the dual QT+ACT-VVIR modes. Patients performed submaximal and maximal exercise tests with CO assessed by carbon dioxide rebreathing method. Comparing the HR response based on the change in metabolic workload, the ACT- VVIR “overpaced,” the QT'VVIR “underpaced,” and the QT+ACT-VVlR achieved the best approximation to normal. The percentages of CO increase in ACT-WIR and QT+ACT-VVIR modes over resting CO were higher at 1 minute of exercise (295 ± 85% and 165 ± 49%, respectively) compared to the QT-VVIR mode (81 ± 40%, P ≤ 0.05). During exercise, stroke volume cbanges from baseline were similar between ACT-VVIR and QT + ACT-VVIR modes, but a compensatory increase in stroke volume occurred in the QT-VVIR mode during submaximal exercise (50 ± 11 mL vs 24 ± 17 mL in the QT+ACT-VVlR and 14 ± 4 in ACT-VVIR, P ≤ 0.003). There was no difference in the maximal exercise workload, exercise duration and CO at the submaximal and maximal exercise between the 3 sensor modes. Thus, exercise capacity is a poor indicator of sensor performance while CO measurement is a sensitive indicator of sensor mode differences especially at low workload exercise. The ACT- VVIR gave the fastest increase in CO at start of exercise at the expanse of overpacing, whereas the “under-paced” QT-VVIR compensated for the slower rate increase by utilizing contractility reserve during submaximal exercise. Dual sensor pacing, by achieving the best heart rate to workload relationship, provided a CO response without overpacing or using contractility reserve during exercise.     

An Integrated Dual Sensor System Automatically Optimized by Target Rate Histogram

The use of combined sensors and advanced algorithms using different principles can improve rate performance over a single sensor system. Combinations of sensors and more sophisticated algorithms, however, invariably increase the complexity of pacemaker programming. An automatically optimized combined minute ventilation and activity DDDR pacemaker was developed to minimize repeated sensor adjustment. The device used subthreshold (below cardiac stimulation threshold) lead impedance to detect lead configuration at implantation automatically, followed by "implant management," including setting of lead polarity and initiation of DDDR pacing. Automatic sensor adaptation was achieved by programming a "target rate histogram" based on the patient's activity level and frequency of exertion, and the rate profile optimization process matched the recorded integrated sensor response to the target rate histogram profile. In nine patients implanted with the DX2 pacemakers, the implant management gave 100% accuracy in the detection of lead polarity. Rate profile optinuzation automatically increased the pacing rate during exercise between discharge and 3-month follow-up (hall walk: 78 ± 3 vs 98 ± 3 beats/min, and maximal treadmill exercise: 89 ± 6 vs 115 ± 5 beats/min, P < 0.001) with a significant increase in exercise duration during maximal exercise (7.18 ± 1 min vs 9.56 ± 2 min, P = 0.05). The accuracy of rate profile optimization versus manual programming was assessed at 1 month, and there was no significant difference between pacing rate kinetics and maximal pacing rate between the two methods of programming. In conclusion, pacemaker automaticity can be initiated at implantation and the self-optimized rate adaptive response appeared to be comparable to that derived from a manual programming procedure, which may reduce the need to perform time consuming sensor programming.     

Evaluation of a Dual Sensor Rate Responsive Pacing System Based on a New Concept

The minute ventilation is known to be one of the most physiological indicators of exercise. A curvilinear relationship between VE and the normal sinus rhythm (NSR) has been demonstrated in healthy patients. The aim of this study is to show that a pacemaker based on a VE sensor can reproduce such a relationship. Eighty-one patients received a Talent DR 213 (ELA Medical, Montrouge, France) pacemaker with a third-generation rate responsive algorithm. At 1-month follow-up, the patients underwent a treadmill exercise test, after which three groups were defined: group 1 had 6 patients who were 100% paced throughout the exercise test; group 2 had 10 patients who maintained NSR throughout the test; and group 3 had 12 patients who had cardiopulmonary recording during the exercise test. In group 1 patients, the simulation function computed the simulated rate (sim-rate), which was compared to the sensor-driven rate (SDR). In group 2 patients, sim-rate was compared to the NSR. In group 3 patients, cardiac and metabolic reserves were compared to determine the appropriateness of the rate response to exercise (HRR% vs MR%). The results showed that the mean correlation coefficient between sim-rate and SDR was 0.983 ± 0.005 (P < 0.001); the mean correlation coefficient between NSR and SDR was 0.92 ± 0.07 (P < 0.001); and a linear relationship was found between HRR% and MR%, with a mean slope of 1.1 ± 0.2 that was significantly equal to the theoretical value of 1 (P = NS). In conclusion, combining an activity-driven sensor with a physiological sensor allows the preservation of a physiological rate response during exercise.