Europace Advance Access originally published online on March 9, 2007
Europace 2007 9(4):233-238; doi:10.1093/europace/eum021
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
PACING
The contribution of rate adaptive pacing with single or dual sensors to health-related quality of life
Rodger Crowson Foundation for Cardiac Arrhythmias Studies, Office: Weteringwaard 5, 3984 PC Odijk, The Netherlands
Manuscript submitted 20 October 2006. Accepted after revision 30 December 2006.
* Corresponding author. Tel: +31 30 6570760; fax: +31 30 603 4420. E-mail address: n.m.vanhemel{at}hetnet.nl
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
Aims The characteristics of sensors to perform rate adaptive pacing are well established but whether their contribution improves health-related quality of life (QoL) remains disputable. To compare the effects on QoL with an integrated dual sensor [minute ventilation (MV) and acceleration, TT sensor] with a single MV sensor, and with no rate adaptive pacing.
Methods and results This Dutch multi centre, prospective, single- (patient) blind study was performed in patients after first pacemaker (PM) implant for sick sinus syndrome or AV block. After a 3-month ‘sensor off’-period following DDD PM implantation, where the latter 2 months permitted the MV sensor to learn the intrinsic rhythm, a 2-month period of DDDR with TT sensor or 2 months of DDDR with MV sensor, subsequently the two modes were crossed over. Quality of life was determined with Aquarel, the disease-specific instrument for PM patients. Heart rate, percentages of sensor driven and intrinsic rhythm were retrieved from PM memories. Sixty-four patients completed the 7-month study. In sick sinus patients, percentages of sensor-driven pacing occurred significantly more frequently than in AV block patients After implant QoL improved significantly: before 71.3 and after 83.5% (P < 0.001) measured with Aquarel and in 3 of 9 SF-36 scales, but no significant additive QoL benefit with dual or MV sensor pacing was observed. Pacing diagnosis, percentages of rate adaptive pacing, and heart rate influencing medication did not influence this result.
Conclusion Pacemaker implantation strongly improves QoL, but neither single- nor dual- sensor-driven pacing offered additional improvement in QoL during the initial 8 months after the first PM implant.
Key Words: Quality of life, Rate adaptive pacing, Pacemaker, Pacemaker sensor, Double sensor, QoL and PM sensor
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
In 1967, rate adaptive pacing was introduced to vary pacing rates during daily physical activities in patients with chronotropic incompetence.1
Although tolerance and symptoms clearly improved, the sensors for body movement activity or acceleration (ACT), minute ventilation (MV), evoked QT interval, and peak endocardial acceleration respond often too fast, too slowly, or disproportionately and hardly mimic the subtle variations of rate of the sinus node.2,3 The integration of single sensors into a double-sensor better imitates sinus node behaviour by shortening of the ACT response time and proportionality of the MV sensor.4–6
In recent years health-related quality of life (QoL) of pacemaker (PM) patients has received more attention. Numerous prospective large-scale studies examined the effects of pacing mode on QoL applying generic and/or PM patient-specific QoL instruments.7–14 However, despite world-wide use of rate adaptive pacing, its effects on health-related QoL have been little reported. This leaves the debate alive whether sensor-driven pacing with one or double sensors plays an indispensable role in health perception and QoL.15–19 We hypothesized that single and mainly double sensor adaptive pacing would improve QoL and tested this assumption in a prospective crossover study of patients after first PM implantation.
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
Study design
The SQL study (Sensor and health-related QoL) was a prospective randomized 2-month-crossover, single blind, Dutch multi-centre study comparing QoL during dual- and single- sensor rate adaptive pacing versus no rate adaptive pacing. The protocol was approved by the local ethical committees and all patients gave their written informed consent to participation.
The primary objective of the study was to determine the difference in QoL with rate adaptive pacing with twin trace (TT, see below), and only MV, and without rate adaptive DDD pacing. The secondary objectives were (i) the comparison of QoL with TT and only MV rate adaptive pacing and (ii) to define the effects of pacing indication, percentages of pacing, and heart rate influencing administered drugs on QoL with TT or MV rate adaptive pacing.
After inclusion (Figure 1) and PM implantation, a 4-week-interval was used for mental and physical stabilization and adaptation to the pacing system. Afterwards, a 2-month-period without rate adaptive pacing, and only lower rate pacing followed that permitted the MV sensor to learn the daily variance of intrinsic heart rate and automatically programme the slope and upper pacing rates. This period was defined as the baseline period, and thereafter the 2-month randomized crossover periods with enabled MV sensor or TT sensor followed. Before implantation, patient characteristics were collected and the QoL instrument had to be completed by the included patient. At 4 weeks after PM implantation, at end of baseline before crossover, and after each crossover period, the QoL was assessed, and data were retrieved from device diagnostics and memories.
|
Patient inclusion and exclusion
Entry in the study required a class 1 indication for permanent DDD pacing because of sick sinus syndrome (SSS) or advanced AV conduction block. Presence of permanent atrial tachyarrhythmias, pacemaker replacement, short-life expectancy, unstable psychosociological conditions, pregnancy, and other reasons that preclude a stable mental and/or physical condition over a 1-year-period after informed consent were the reasons for exclusion.
Measurement of QoL
The Aquarel instrument was used for the measurement of QoL.20,21 Briefly, this measure consists of the 36-item Medical Outcomes Study Short-Form General Health Survey (SF-36) to assess generic health-related QoL and four dimensions specific for PM patients. Aquarel is fully validated for sensitivity, reproducibility, and other psychometric requirements.
Pacemaker and sensor description
Talent DR 213, Talent DR233, and Symphony 2550 pacemakers (ELA Medical, Le Plessis Robinson, France) are dual chamber, rate responsive PMs with sensors that record MV and ACT respectively, using the most appropriate sensor for the circumstances. All models are similar in rate response characteristics. In short, to reduce complexity of programmable parameters, activation or deactivation of the automatic sensor adjustment has to be selected. The automatic algorithm continuously calibrates separately the MV and the ACT sensors. The sensor indicated rate at the detection of onset of physical activity is adjusted to an exponential increase, and rate decline has a linear decrease. The ACT sensor influences the heart rate with a fixed slope, and the MV sensor is automatically adjusted to achieve upper sensor rate only with maximal exercise.6
Pacemaker programming after implantation and inclusion
In all patients pacing mode was DDD, atrial and ventricular output >2 diastolic threshold, post-ventricular atrial blanking of 155 ms. The rate response mode was ‘learn’ during baseline before randomization, sensor choice was TT (MV combined with ACT) or MV during randomization, the mode switch for atrial arrhythmias was enabled and the memory functions (AIDA) for atrial and ventricular arrhythmias were engaged.22–24
Rate programming
The lower pacing rate was programmed at 55/min and the upper pacing rate at 80% of the predicted maximal heart rate rounded to the nearest available programmable setting according to Freedman et al.25 The atrioventricular (AV) delay was programmed to be adaptive between 78 and 156 ms. For a sensed event, an additional 63 ms was added to the AV delay. The adaptation of the (suggested) pacing rate due to sensor response was programmed automatic.
Pacemaker data
Mean, SD, lower, and upper boundaries of heart rate, percentages of intrinsic, lower rate, and sensor adaptive pacing of atria and ventricles were stored in the PM memory. Premature atrial and ventricular beats were also collected for the analysis.
Statistical analysis
Data are expressed as mean ± SD. Continuous variables were compared by paired and unpaired Student's t test and proportions by 
2 test or when appropriate Fisher's exact test. Sample size was calculated taking into account that application of Aquarel is associated with a SD of <50% of the mean. Using the paired t-test and presuming a clinical relevant difference of 50% of the SD, a power of >95% could be found in 60 patients, and a clinical relevant outcome of 38% of the SD with 80% power in 60 patients. In view of the age at inclusion and an assumed non-compliance of 25% of the patients during the study, 80 patients had to be included.
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
Patients
From March 2001 to September 2004, 99 patients were enrolled in seven hospitals. The baseline characteristics of 64 patients who completed the study are summarized in Table 1. In 35 patients (35%) death after implant (1
), lead problem (3), carcinoma (1), CVA (1), coronary bypass surgery (1), permanent atrial fibrillation (AF) (5), intolerance or pacing without rate adaptation (1), intolerance of sensor-driven pacing (2), psychological imbalance (1), non-compliance with the study programme (13), or study violation (6) were reasons for withdrawal.
|
Intrinsic and paced heart rates
Retrieval of stored PM data disclosed that 1 month after PM implantation the mean heart rate of all patients was 69.3 ± 10.4 bpm, during the baseline period 67.8 ± 8.5, during the TT period 69.8 ± 6.4, and during MV 71.2 ± 6.3 bpm. The mean heart rate changed significantly (P < 0.001) between baseline and crossover periods but this difference was not of clinical relevance. Patients with SSS had a significantly lower mean heart rate at baseline than those with AV conduction block, but this difference was not observed during the TT and MV crossover periods (Table 2). The mean percentage of lower atrial pacing during baseline and afterwards during TT and MV pacing was two-fold higher in patients with SSS than in patients with AV conduction block; this difference was significant (P < 0.05). The percentages of sensor-driven atrial pacing were also significantly greater in SSS patients than in patients paced for AV conduction block (Table 2), but no clear difference between TT and MV rate adaptive atrial pacing was observed. Notably, if an arbitrary bisection of >50% sensor-driven atrial pacing was carried out, SSS patients had more rate adaptive pacing than patients with AV conduction block: during MV pacing this difference was significant (P = 0.04) but not during TT pacing (P = 0.06). Because more lower rate atrial pacing and more sensor-driven atrial pacing occurred in patients with SSS, the percentages of intrinsic atrial rhythm was significantly smaller than in patients with AV conduction block. These findings underscore that SSS patients, indeed, needed more use of the sensor(s) than those paced for AV conduction block. Because the sensor(s) are atrial directed, the percentages of ventricular pacing will be determined by the pacing indication, the programmed AV interval (see Methods) and percentages of atrial pacing. As expected, the percentage of lower rate ventricular pacing was significantly lower, and the percentage of intrinsic ventricular rhythm was significantly larger in SSS patients than in patients with AV conduction block (Table 2), but this difference was not detected during TT and MV pacing. The percentages of atrial premature beats (varying from 0.3 to 0.6%) and ventricular premature beats (varying from 0.7 to 2%) did not differ during the baseline and the crossover periods.
|
QoL outcomes
All patients experienced at 3 months after PM implantation, at end of the baseline period a significant improvement of QoL manifest in 3 of 9 SF 36 scales and in all Aquarel scales (Table 3). Primary objective: TT rate adaptive pacing produced no additional improvement of QoL compared with baseline, except for the scale ‘chest discomfort’ of Aquarel (P = 0.01) (data not presented). Secondary objectives: after 2 months of MV sensor rate adaptive pacing, no further improvement of QoL could be observed compared with no rate responsive pacing (baseline condition). Differences in QoL between the 2 month MV and TT rate adaptive pacing periods could not be detected (Table 3). Improvement in QoL after PM implantation, and QoL with enabled TT or MV sensor in patients with SSS and AV block did not differ with respect to SF 36 and Aquarel instruments. When pacing percentages were divided into <25%, 25–60%, and >60% during the crossover periods with enabled TT and MV sensor, QoL also did not differ. Finally, comparison of the 15 patients with and 49 patients without at least 1 anti-arrhythmic drug could not disclose any differences in QoL during the periods studied.
|
|
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
This study demonstrated a significant improvement in QoL after PM implantation without incremental effects of dual sensor or single MV sensor rate adaptive pacing on QoL. Pacemaker indication, percentages of rate adaptive atrial pacing, or prescribed heart rate influencing drugs did not influence this outcome. To appreciate these results, several issues need to be discussed.
Improved well-being after first pacemaker implantation
A significant improvement in QoL after PM implantation is a well recognized observation.8–10,12–14 This favourable result can be attributed to the restoration of chronotropic competence or AV conduction. Further refinement of pacing mode and programming appear not to add much benefit due to a ceiling effect of pacing as such.11,13
Sufficient sensor-driven pacing?
One might question whether rate adaptive pacing in this study suffices to affect QoL at all (Table 2). In a model, to compare the intrinsic heart rate variation with exercise in the standard clinical range of 60–120 ppm, and rate adaptation with various sensors, Lass et al.3 showed that the QT sensor had better accuracy than MV or the acceleration sensor, whereas dual sensors, and specifically the combination of MV and acceleration, achieved a heart rate reconstruction with an error of <10%. This error is compatible with clinical requirements.3 Evaluation of the TT dual sensor showed that rate responsive pacing showed a close reproduction of the sinus rate of patients with preserved sinus rhythm (correlation coefficient >0.90).6 These observations make highly unlikely, an insufficient rise or variation of sensor-driven pacing due to technical shortcomings as a cause of lack of increment in QoL.
Pacing indication and QoL
Patients were categorized into indication for pacing SSS (72%) and AV conduction disorder (28%). Both the categories showed a low prevalence of concomitant cardiac disease, comorbidity, and prescribed medication (Table 1). The percentages of sensor-driven pacing was significantly larger in SSS patients than in AV block patients (Table 2). This parameter demonstrated adequately sinus node incompetence in SSS patients compared with a single exercise test to evaluate the function of the sinus node. Despite differences in percentages of sensor-driven pacing of SSS and AV block patients, no further increase in QoL was observed with enabled sensors.
Previous studies of effects of sensors on QoL
Oto et al.16 observed a markedly improved QoL when rate adaptive pacing was enabled in VVI patients. Lau et al.17 comparing pacing modes in the same patient with sinus node disease and intact AV conduction observed the lowest QoL scores with VVIR pacing. However, except palpitations, no significant differences in other symptoms, physical status or subjective symptoms could be observed during AAIR, DDDR, and VVIR; this lack of improvement was ascribed to the high-health perception at baseline. Erol-Yilmaz et al.18 examined the impact of optimization of PM sensors on exercise capacity and QoL in patients with >75% daily pacing. Despite optimized maximal heart rate and exercise capacity, QoL measured with the generic instruments SF 36 and Hacettepe16 and 4 domains of the Karolinska instruments,28 did not improve; specific patient groups that derived benefit could not be defined. The prospective, randomized, 2 arm, DUSILOG study with dual sensor (MV and ACT) and single MV or ACT sensor in patients requiring DDD PM implantation for SSS, assessed QoL, walking distance, and daily activity.19 In the 64 patients who completed the study, single sensor pacing significantly improved QoL and other parameters, whereas dual sensor pacing did not provide additional benefit compared with DDD pacing. Patients with most severe SSS (17% had intrinsic atrial rhythm <60 bpm) showed most benefit of single as well as dual sensor rate adaptive pacing. The difference in outcome of that study with ours has to be ascribed to patient selection, definition of chronotropic incompetence, programming of the single sensors, and the use of the generic SF 36 QoL instrument.
Limitations
The rigors of the study, reflected in the withdrawal of 23 patients due to non-medical reasons, could have affected health perception. Because TT and MV sensors drive atrial pacing, a normal programmed AV delay (see Methods) will result in more ventricular pacing. This might have affected negatively the QoL. However, although the percentages of ventricular pacing before and after crossover significantly differed, the differences are trivial (Table 2) and cannot explain the absent increment in QoL during the two periods of rate responsive pacing. Because this study was performed in patients in the first 7 months after their first PM implantation, the effect of rate–response pacing on QoL could be different after long-term pacing therapy when PM dependency becomes more evident. Finally, because of the low proportionality to metabolic demands, the activity scale derived from the PM storage was not compared with the QoL data in this study.
Clinical implications
We prospectively studied the QoL by comparing changes of patient group and no changes of paced individuals.26 Because our study demonstrates that with DDD pacing single- and dual- rate adaptive pacing did not offer additional QoL benefit, PM accumulated information about intrinsic and paced rates and patient's symptoms are needed to guide sensor programming in order to achieve individually optimized rate adaptive pacing.27,28 Patients with frank SSS or bradytachycardia syndrome with intrinsic rates <60/m need specific attention because they will most likely profit from rate adaptive pacing.19
Conclusion
Health-related QoL improved substantially after PM implantation for conventional indications as shown by other prospective PM studies. Dual sensor or MV sensor rate adaptive pacing, however, produced no additional improvement in QoL in the first 7 months after PM implantation. Pacing indication, percentage of pacing, and influence of heart rate reducing medication were not associated with this result.
|
Acknowledgements |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
We thank the cardiologists, pacemaker technicians, and support personnel of the Departments of Cardiology, St Elisabeth Ziekenhuis, Tilburg, Maxima Medisch Centrum, Veldhoven, Vlietland Ziekenhuis, Schiedam, Medisch Spectrum Twente, Enschede, VieCuri Medisch Centrum, Venlo, the Netherlands for care of patients included in this study. The Research and Development Department of the Department of Cardiology, St Antonius Hospital, Nieuwegein, the Netherlands is acknowledged for statistical assistance.
Conflict of interest: H.A.M.S. is currently conducting research sponsored by Medtronic, Biotronic and Sorin Group. N.M.V.H. is an occasional advisor for Vitalin Company and Guidant Netherlands. P.V.D.K. holds stocks of Medtronic and Sorin Group and has a financial interest in Sorin Group.
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionAcknowledgementsReferences |
|---|
[1] Voukydis PC and Krasner JL. A physiologically regulated cardiac pacemaker. Br J Exp Pathol 1967; 48: 118–23.[Web of Science][Medline]
[2] Israel CW and Hohloser SH. Current status of dual-sensor pacemaker systems for correction of chronotropic incompetence. Am J Cardiol 2000; 86:Suppl., 86K–94.[CrossRef][Web of Science][Medline]
[3] Lass J, Kalk J, Meigas K, Hinrikus H, Blinowska A. Evaluation of the quality of rate adaptation algorithms for cardiac pacing. Europace 2001; 3: 221–8.
[4] Alt E, Theres H, Heinz M, Matula M, Thilo R, Blomer H. A new rate-modulated pacemaker system optimized by combination of two sensors. Pacing Clin Electrophysiol 1988; 11: 1119–29.[CrossRef][Medline]
[5] Leung SK, Lau CP, Tang MO. Cardiac output is a sensitive indicator of difference in exercise performance between single and dual sensor pacemakers. Pacing Clin Electrophysiol 1998; 21: 35–41.[CrossRef][Medline]
[6] Bonnet JL, Geroux L, Cazeau S. Evaluation of a dual sensor rate responsive pacing system based on a new concept. Pacing Clin Electrophysiol 1998; 21: 2198–203.[CrossRef][Medline]
[7] Linde-Edelstam C, Nordlander R, Undén AL, Orth-Gomer K, Rydén L. Quality-of-life in patients treated with atrioventricular synchronous pacing compared to rate modulated ventricular pacing: a long-term, double-blind, crossover study. Pacing Clin Electrophysiol 1992; 15: 1467–76.[CrossRef][Medline]
[8] Lamas GA, Orav EJ, Stambler BC, Ellenbogen KA, Sgarbossa EB, Huang SKS, et al. Quality of life and clinical outcome in elderly patients treated with ventricular pacing as compared with dual-chamber pacing. N Engl J Med 1998; 338: 1097–104.
[9] Connolly SJ, Kerr CR, Gent M, Roberts RS, Yusuf S, Gillis AM, et al. Effects of physiologic pacing versus ventricular pacing on the risk of stroke and death due to cardiovascular causes. Canadian Trial of Physiologic Pacing. N Engl J Med 2000; 342: 1385–91.
[10] Lamas GA, Lee KL, Sweeney MO, Silverman R, Leon A, Yee R, et al. Mode selection trial in sinus node-dysfunction. Ventricular pacing or dual-chamber pacing for sinus-node dysfunction. N Engl J Med 2002; 346: 1854–62.
[11] Newman D, Lau C, Tang ASL, Irvine J, Paquette M, Woodend K, et al. Effect of pacing mode on health-related quality of life in the Canadian trial of physiologic pacing. Am Heart J 2003; 145: 430–7.[CrossRef][Web of Science][Medline]
[12] Gribbin GM, Kenny RA, McCue P, Toff WD, Bexton RS, McComb JM. Individualised quality of life after pacing. Does mode matter? Europace 2004; 6: 552–60.
[13] Newman D. Relationships between pacing mode and quality of life: evidence of randomized clinical trials. Card Electrophysiol Rev 2003; 7: 401–5.[CrossRef][Medline]
[14] Lopez-Jimenez F, Goldmann L, Orav EJ, Ellenbogen K, Stambler B, Marinchak R, et al. Health values before and after pacemaker implantation. Am Heart J 2002; 144: 687–92.[Web of Science][Medline]
[15] Sulke N, Dritsas A, Chambers J, Sowton E. Is accurate rate response programming necessary? Pacing Clin Electrophysiol 1990; 13: 1031–44.[CrossRef][Medline]
[16] Oto MA, Muderrisoglu H, Ozin MB, Korkmaz ME, Karamehmetoglu A, Oram A, et al. Quality of life in patients with rate responsive pacemakers: a randomized, cross-over study. Pacing Clin Electrophysiol 1991; 14: 800–6.[CrossRef][Medline]
[17] Lau C-P, Tai Y-T, Leung W-H, Wong C-K, Lee P, Chung FL-W. Rate adaptive pacing in sick sinus syndrome: effects of pacing and intrinsic conduction on physiological responses, arrhythmias, symptomatology and quality of life. Eur Heart J 1994; 15: 1445–55.
[18] Erol-Yilmaz A, Schrama TA, Tanka JS, Tijssen JG, Wilde AA, Tukkie R. Individual optimization of pacing sensors improves exercise capacity without influencing quality of life. Pacing Clin Electrophysiol 2005; 28: 17–24.[CrossRef][Medline]
[19] Padaletti L, Pieragnoli P, Di Biase L, Colella A, Landolina M, Moro E, et al. Is a dual sensor pacemaker appropriate in patients with sino-atrial disease? Results from the DUSISLOG study. Pacing Clin Electrophysiol 2006; 29: 34–40.[CrossRef][Medline]
[20] Stofmeel MAM, Post MWM, Kelder JC, Grobbee DE, van Hemel NM. Psychometric properties of Aquarel: a disease specific health related quality of life questionnaire for pacemaker patients. J Clin Epidemiology 2001; 54: 157–65.[CrossRef][Web of Science][Medline]
[21] Stofmeel MAM, Post MWM, Kelder JC, Grobbee DE, van Hemel NM. Changes in health related quality of life after pacemaker implantation: responsiveness of the Aquarel questionnaire. Pacing Clin Electrophysiol 2001; 24: 288–95.[CrossRef][Medline]
[22] Lascault G, Nitzsche R, Ritter P, Remy M, Limousin M. Assistant programming software: a new tool for an improved programming of pacemakers. Pacing Clin Electrophysiol 1990; 13: 1732–6.[Medline]
[23] Limousin M, Geroux L, Nitzsche R, Cazeau S, Pioger G, Victor J, et al. Value of automatic processing and reliability of stored data in an implanted pacemaker: initial results in 59 patients. Pacing Clin Electrophysiol 1997; 20: 2893–8.[CrossRef][Medline]
[24] Limousin M, Pioger G, Bonnet JL, Geroux L. Automatic adaptation of the basic pacing rate in response to minute ventilation. Pacing Clin Electrophysiol 1998; 21: 1405–9.[CrossRef][Medline]
[25] Freedman RA, Hopper DL, Mah J, Hummel J, Wilkoff BL. Assessment of pacemaker chronotropic response: implementation of the Wilkoff mathematical model. Pacing Clin Electrophysiol 2001; 24: 1748–54.[CrossRef][Medline]
[26] Linde C. How to evaluate quality-of-life in pacemaker patients: problems and pitfalls. Pacing Clin Electrophysiol 1996; 19: 391–397.[CrossRef][Medline]
[27] Lukl J, Doupal V, Sovova E, Lubena L. Incidence and significance of chronotropic incompetence in patients with primary pacemaker implantation or pacemaker replacement. Pacing Clin Electrophysiol 1999; 22: 1284–91.[CrossRef][Medline]
[28] Greco EM, Guardini S, Ferrario M, Romano S. How to program rate responsive pacemakers. Pacing Clin Electrophysiol 2000; 23: 165–73.[CrossRef][Medline]
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  E. Pilat, R. Mlynarski, A. Wlodyka, and W. Kargul Influence of DDD rate response pacing with integrated double sensors on physical efficiency and quality of life Europace, October 1, 2008; 10(10): 1189 - 1194. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. W.M. van Eck, N. M. van Hemel, W. G. de Voogt, J. G. Meeder, H. A. Spierenburg, H. Crommentuyn, R. Keijzer, D. E. Grobbee, K. G.M. Moons, and on behalf of the FOLLOWPACE investigators Routine follow-up after pacemaker implantation: frequency, pacemaker programming and professionals in charge Europace, July 1, 2008; 10(7): 832 - 837. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||