Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
European Heart Journal Supplements (2007) 9 (Supplement I), I11–I22 doi:10.1093/eurheartj/sum057 Evolution of pacing for bradycardias: sensors Chu-Pak Lau1*, Hung-Fat Tse1, A. John Camm2, and Serge S. Barold3 1 Cardiology Division, University Department of Medicine, The University of Hong Kong, Queen Mary Hospital, Hong Kong 2 Department of Cardiovascular Sciences, St George’s Hospital, Medical School, London, UK 3 Tampa General Hospital, Tampa, FL, USA KEYWORDS Chronotropic incompetence; Exercise; Pacing; Rate-adaptive pacing; Sensor; Sinus node disease A physiological pacing system should be able to restore normal chronotropic response and optimal conduction within and between the atrial and ventricular pacing. Implantable sensors are initially developed to overcome chronotropic incompetence of the sinus node to exercise and non-exercise requirements. Ideal sensor behaviour includes speed of response, proportionality, specificity, and sensitivity. Sensors can be classified by the method they detect a physiological change: body accelerations, paced QRS, impedance and sensors that require special leads. Rate-adaptive pacing is proven to improve exercise capacity and oxygen consumption over fixed-rated pacing, especially during ventricular pacing. Patients with chronotropic incompetence can derive symptomatic benefit in the rate-adaptive mode. The latest development involves the use of sensors to monitor heart failure, and to best optimize rate and conduction status in cardiac resynchronization therapy. Introduction An ideal pacing system should be able to restore the rate and sequence of normal activation in the presence of abnormal cardiac automaticity and conduction. Although the sinus node is ideal for rate control, a high proportion of pacemaker recipients either have established sinus dysfunction or will develop it over time. Sinus node chronotropic incompetence commonly occurs as a result of medications or as isolated sinus node disease. In addition, in patients whose atria are unreliable for sensing or pacing (such as during atrial fibrillation), an alternative means to simulate sinus node responsiveness is required. Implantable sensors for cardiac pacing are thus developed to address these deficiencies of the sinus node during exercise and in other situations requiring a rise in heart rate (HR). Sensors are now incorporated in most bradycardia pacemakers as a programmable option. In addition, the role of sensors has been expanded * Corresponding author. Fax: þ852 2818 6304. E-mail address: [email protected] to include functions other than rate augmentation—such as detection of atrial and ventricular capture, and monitoring of heart failure, sleep apnoea, and haemodynamic status. Historical perspectives Cammilli1 implanted the first rate-variable singlechamber pacemaker that detected changes in blood pH during exercise. In 1981, a ‘physiologically adaptive’ cardiac pacemaker responding to changes in the QT interval during exercise was described by Rickards and Norman.2 In 1982, Wirtzfeld et al.3 reported the use of central venous oxygen saturation for the control of automatic rate-responsive pacing. Respiratory changes during exercise were proposed as a physiological parameter for a rate-adaptive pacemaker in 1975, and a respiratory rate driven rate-adaptive pacemaker was introduced by Rossi4 in 1982. Physical exercise is accompanied by body movement,5 and this is detected by using either a piezoelectric crystal or an accelerometer, the so-called ‘activity sensing’. With continuing research, the Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2007. For permissions please email: [email protected]. I12 number of sensors available for rate-adaptive pacing steadily increased. In particular, activity and minute ventilation (MV) sensors6 have been extensively used. Although single-chamber ventricular rate-adaptive pacing was originally meant to replace dual-chamber pacing, the additional benefits of atrial sensing and pacing prompted the development of dual-chamber rate-adaptive pacing in 1986, and VDDR rate-adaptive pacing with a single-pass lead in 1992. As none of the sensors could simulate normal sinus node function in all aspects, it is logical to combine sensors for optimal rate adaptation. The first dual-sensor device used a combination of activity and QT interval sensing (1990), and later activity and MV sensing (1995). The increasing sophistication of sensors and their combinations prompted the development of automatic sensor programming. The original three-letter code for pacemaker mode proposed in 1974 was revised to the five-letter pacing code, and the rate-adaptive function is denoted by the use of the letter R in the fourth position in 1987 (VVIR or DDDR). Figure 1 shows several sensor-driven pacemakers introduced before 1990. Most devices nowadays have used standard pacing leads that are similar to conventional pacemakers. The latest development is use of sensors to monitor cardiac haemodynamics. Right ventricular (RV) pressure has been found to be a good estimate of pulmonary arterial diastolic and capillary wedge pressure. A fully implanted device has been used to reduce heart failure hospitalization.7 Transthoracic impedance reflects changes in pulmonary fluid during pulmonary oedema. A device that tracks pulmonary fluid by impedance measurement in an implantable cardioverter defibrillator (ICD) has recently become available.8 C.-P. Lau et al. Metabolic–chronotropic relationship Wilkoff et al.11 defined the normal chronotropic response during exercise, which is dependent on age, resting HR, and peak functional capacity. A linear relationship between percentage of HR reserve and percentage of metabolic reserve should occur during exercise in normal individuals, and is an objective assessment of sensor-driven rate response.12 Exercise response in heart failure Atrial contribution to the resting cardiac output becomes less important in the presence of elevated capillary wedge pressure.13 As the ability to increase stroke volume is limited in a heart working on the flat portion of the Frank–Starling curve, an increase in HR is the only means to increase cardiac output. Furthermore, in a study of patients with VVIR pacemakers, a larger percentage of increase in exercise cardiac output and exercise capacity occurred in those with poorer LV function. In patients with implanted cardiac resynchronization therapy (CRT) devices,14 chronotropic incompetence defined as maximum HR 70% age-predicted maximum was found to be present in about 70% of heart failure patients. In this group of patients, rate-adaptive CRT improved maximum oxygen consumption (VO2) and work capacity compared with CRT pacing, and is independent of AV interval shortening during exercise. Taken together, these data suggest that rate modulation plays a critical role in some patients with impaired LV function who require pacing therapy. Heart rate modulation for non-exercise needs Physiological basis of rate-adaptive pacing Although atrioventricular (AV) synchrony increases stroke volume by 20–30% during exercise, this increase is relatively small compared with the four-fold increase achieved by an increase in rate. Karlof9 studied the relative contribution of AV synchrony and rate increase in patients with complete AV block using an external pacing system capable of programming to VAT and a ratematched ventricular-pacing mode. Although cardiac output during VAT pacing was 18% higher compared with VVI pacing at rest, it was only 8% higher during VAT pacing compared with VVIm pacing. Furthermore, both stroke volume and left ventricular (LV) filling pressure were similar during exercise in the two pacing modes. However, at lower levels of exercise, cardiac output was maintained by an increased arteriovenous oxygen difference and arterial lactate level in the rate matched VVI mode, and a lower blood pressure was observed.10 It should be noted that these early studies were performed in pacemaker-dependent patients with most of them having AV block paced at the RV apex. It remains uncertain if similar exercise benefits can be observed in patients who are less pacemaker dependent and/or those with preserved intrinsic AV conduction. Exercise is but one of the many physiological requirements for variation in HR. For example, emotion such as anxiety may trigger a substantial change in HR. The sinus rate is higher when a person moves from the supine to the upright posture when cardiac output decreases. Isometric exercise also results in an increase in cardiac output and HR in most people. The changes in HR that occur during various physiological manoeuvres (e.g. Valsalva manoeuvre) and baroreceptor reflexes may also be important. An appropriate compensatory HR response is critical in pathophysiological conditions such as anaemia, acute blood loss, hypovolaemia, and during febrile illnesses. Ideal sensor characteristics Based on the physiology of the normal sinus node, a sensor system to overcome chronotropic incompetence needs to be sensitive to both exercise and non-exercise needs. It should be specific such that it is not interfered with by internal or external factors that can erroneously cause an inappropriate rate change. Finally, sensors should achieve rate modulation at an appropriate speed, and its response should be proportional to the Evolution of pacing for bradycardias I13 Figure 1 Some rate-adaptive pacemakers introduced before 1990. (A) pH sensing pacemaker. Santa Maria Nuova in Florence, Italy, reproduced with permission from Cammilli L.1 (B) An oxygen-sensing lead from Oxytrax during light emission for oxygen sampling in vitro (Medtronic Inc., MN, USA). (C ) Activity sensing using a piezoelectric crystal in the ActivitraxTM pacemaker (Medtronic Inc.). (D) Activity-sensing pacemaker Sensolog 703TM (from Siemens AB, Solna, Sweden). (E) A respiratory-rate-sensing BiorateTM pacemaker (Biotec, S.P.A., Bologna, Italy). Note the auxilliary lead with a screw that was positioned subcutaneously across the chest for detecting respiratory rate. (Pacing lead not shown). (F) A minute-sensing Meta-MVTM pacemaker (Telectronics Pacing Systems, Englewood, CO, USA). (G) A QT-sensing Quintech pacemaker (Vitatron Medical BV, Arnhem, NL). (H ) A right ventricular dp/ dt DeltatraxTM pacemaker (Medtronic Inc.). Note the hermetically seated pressure sensor proximal to the distal pacing electrode. I14 C.-P. Lau et al. Table 1 Major sensors for rate-adaptive pacing and monitoring classified according to method of technical realization Methods Physical/physiological parameters Examples models Manufacturers Vibration/acceleration sensing Body movement Sigma, Kappa Diamond, Clarity, Selection AF Talent Miniswing, Neway Insignia, Pulsar Max, Discovery Actos, Protos, Philos Identity, Integrity, Affinity, Vitality Kappa Talent Insignia, Pulsar Max Protos, Inos Precepta Concertob Diamond, Clarity, Selection AF Medtronic Inc. Vitatron Sorin-ELA Impedance sensing Minute ventilation Ventricular-evoked response Ventricular inotropic parameter Pre-ejection interval Pulmonary fluid status Evoked QT interval Sensors on pacing electrode Physical parameters Central venous temperature Right ventricular dp/dt Peak endocardial acceleration Right ventricular pressure Left atrial pressure Chemical parameters pH Mixed venous oxygen saturation Boston Scientific Biotronik St. Jude Medical Medtronic Inc. Sorin- ELA Medical Boston Scientific Biotronik Boston Scientific Medtronic Inc. Vitatron Thermos Deltatraxa Best-Living system Chronide† Biotronik Medtronic Inc. Sorin-ELA Medtronic Inc. OxyElitea Oxytraxa IHMa,b Medtronic Inc. Medtronic Inc. Medtronic Inc. Manufacturers and their locations: Biotronik, GmbH & Co., Berlin, Germany; Boston Scientific., St. Paul, MN, USA; Medtronic Inc., Minneapolis, MN, USA; Sorin-ELA Biomedica, Saluggia, Italy; Vitatron BV, Arnhem, the Netherlands. a Investigational devices. b Sensor for monitoring only. level of exercise load.12,15 Technically, a sensor should be easy to implement in a pacing system (preferably without extra hardware), is stable in the body’s internal environment, and does not consume excessive battery current. programmed automatically today by changing responsiveness to match a ‘rate profile’ or ‘rate target’ of a normal population. Alternatively, the sensor data are adjusted automatically to allow the maximum and minimum sensor data to match the upper and lower rates, respectively, over time (see below). Classification of sensors In a rate-adaptive pacing system, a sensor (or a combination of sensors) must first detect a physical or physiological parameter that is related to metabolic demand. Second, an algorithm is needed to relate changes in the sensed parameter to a change in pacing rate. Third, because the magnitude of the physical or physiological changes that are monitored by a sensor differs between patients, physician input is usually necessary to adjust the ‘algorithm’ (generally by programming one or more rate-responsive variables) to achieve the clinically desired rate response. Most sensors operate in an openloop algorithm: the induced rate changes do not induce a negative feedback on the sensor parameter. In a closed-loop sensor, the induced haemodynamic changes will reduce the level of the sensed parameter that is responsible for the initial rate adaptation, and theoretically, very little programming is needed in such a system. In practice, most sensors and algorithms are Technical classification A practical classification is to categorize the sensors according to the technical methods used to measure the sensed parameter (Table 1). Body movements during exercise result in changes in acceleration forces that are transmitted to the pacemaker casing. Technically, activity sensing can be achieved using a piezoelectric crystal, an accelerometer, a tilt switch, or an inductive sensor. These devices transduce body motion into a voltage or into measurable changes in the electrical resistance of a piezoresistive crystal. Impedance is a measure of all factors that oppose the flow of electric current and is derived by measuring resistivity to an injected electric current across a tissue. The impedance principle has been used extensively for measuring respiratory parameters and parameters associated with RV contractility, such as relative stroke volume Evolution of pacing for bradycardias or the preejection interval, and for changes in pulmonary fluid status. The paced intracardiac ventricular electrogram provides information on depolarization and repolarization, which reflect changes in HR and circulating catecholamines. The Stimulus-T interval is used in a ‘QT’ sensing pacemaker. The last group of sensors are those that are incorporated into the pacing lead. Examples of these specialized leads include thermistors (used to measure blood temperature), piezoelectric crystals (used to measure RV pressure), optical sensors (used to measure venous oxygen), and accelerometers at the tip of pacing leads (peak endocardial acceleration or PEA sensor). Some of these sensors measure highly physiological parameters. For example, oxygen saturation is closely related to oxygen consumption during exercise.3 Physical activities increase cardiac output and oxygen extraction from the blood, and a widening of the tissue arteriovenous oxygen difference occurs if the cardiac output does not match the requirements of increased tissue oxygen consumption. With the exception of the PEA sensor, these sensors are used mainly for monitoring, and the stability of chronic implants is a critical issue to address. Clinical applications of sensors A detailed update of current single and dual sensors has been published.15 The following is a summary of recent devices available with details of dual-sensor devices and automatic programming summarized in Table 2. Activity sensing Activity sensing is the commonest sensor in use alone or in combination with other sensors. It does not require a special sensor outside the pulse generator casing, works with any type of pacing lead (uni- or bipolar), has excellent long-term stability, and reliability. Implantation is no different from that of conventional pacemakers. Although they may not be excellent proportional sensors, they react promptly to the beginning and end of physical exercise. The first activity sensors were piezoelectric crystals that responded mostly to the frequency of vibrations (ActivitraxTM , TheraTM , Medtronic Inc., Minneapolis, MN, USA). Subsequent activity sensors are accelerometers that detect body accelerations and have less interpatient variability and better proportionality. For example, in the St Jude Medical, St Paul, MN, USA, activity-sensing devices (AffinityTM, IntegrityTM, IdentityTM, Vitality TM ), acceleration detected by the ‘Omnisense’ accelerometer above a programmable threshold are integrated and translated to a rate response using a rate response slope. In the ‘AUTO’ setting, the device measures the sensor activity level over the preceding 18 h to determine the threshold parameter, and the slope is then adjusted to achieve an appropriate rate response. Acute programming can be achieved with the ‘Prediction Model’: HR during a structured activity such as 6 min hall walk is measured, and rate response during this exercise for different slopes can be projected. A I15 ‘beam accelerometer’ sensor is used in the Medtronic KappaTM , EnPulseTM and EnRhythmTM . In the Boston Scientific (St Paul, MN, USA) activity-sensing devices (InsigniaTM , Pulsar MaxTM ), four parameters are used to determine the rate response: Response factor; Activity threshold, Reaction, and Recovery times. Other activity sensors Sorin-ELA Biomedica (Saluggin, Italy) has introduced a gravitational sensor that uses the vibration of a mercury ball to sense activity, used either alone (SwingTM ) or in combination with PEA sensor (MiniLivingTM ). In addition, the Sorin-ELA has an accelerometer activity sensor (Opus G) that uses a half-bridge variable capacitance accelerometer. Clinical experience Benditt et al.16 compared VVI and VVIR pacing using cardiopulmonary treadmill exercise tests. VVIR pacing prolonged exercise duration by 35%, improved VO2 and anerobic threshold, reduced the patient’s perception of exertion. The benefit was sustained when exercise testing was repeated. Reversion of the pacing system from VVIR to VVI resulted in deterioration of these benefits. Compared with DDD pacing, activity-based VVIR pacing resulted in similar exercise capacity, symptom scores, plasma concentrations of epinephrine, norepinephrine, and atrial natriuretic peptide. Limitations of activity-sensing devices Environmental vibrations, such as those induced by driving, air travel or the use of vibrational appliances or machinery can increase pacing rate. The piezoelectric sensor also responds to the application of static pressure on the pulse generator, which may be important when the patient lies on it. Activity-initiated rate response is dependent on the manner in which activity is being carried out, rather than on the exercise workload, and proportionality is generally limited. Patients may manifest a paradoxically slower HR during walking uphill than during walking downhill. Non-exercise-related stresses such as emotional changes will not be detected. Minute ventilation sensing The original respiratory-sensing pacemaker was limited by a need for an auxiliary subcutaneous electrode. All subsequent generations of respiratory sensor detect MV for rate adaptation from the impedance to a current injected from the proximal electrode of the lead in the heart to the pacemaker case. The advantages of this sensor are that no additional hardware (except for a bipolar-pacing lead in either the right atrium or ventricle) is required. It is highly proportional to work load and responds at a reasonable speed. Both VO2 and HR are correlated with MV during exercise, but MV will increase disproportionately relative to VO2 and the sinus rate above anaerobic threshold. Thus, a special rate-adaptive algorithm to avoid overpacing is needed. The utility of MV sensors in patients with heart failure and CRT remains to be tested, but theoretically I16 C.-P. Lau et al. Table 2 Types of dual-sensor devices in current use and automatic sensor programming Sensors Manufacturers Models Sensors ACTþMV Medtronic KappaTM 400 ACT ¼ piezoelectric MV ¼ impedance Boston Scientific Pulsar maxTM InsigniaTM ELA-Sorin ChorusTM TalentTM SymphonyTM RhapsodyTM Vitatron TopazTM DiamondTM SelectionTM ACTþQT CLSþACT Biotronik InosTM ProtosTM PEAþACT Sorin-ELA MiniLivingTM Algorithms Cross-checking Blending † ACT(0) and † ADL range: MV(þ): up to ACTþMV; ADL rate; † ADL-ER † ACT (þ) and range: Mainly MV(0): up ACT to ADL rate ACT ¼ accelerometer Blending † ACT(0) and MV ¼ impedance † Low heart MV(þ): MV rate: ACT 80%, rate MV 20% † ACT(þ)and † High heart MV(0): rate: ACT 40%, Limited rate MV 60% ACT ¼ Accelerometer No Blending: MV † ACT(þ) and MV(0): initial QT ¼ Unipolar ventricular determined limited rate rate response lead response if ACT QT ¼ Unipolar ventricular † ACT(0) and indicates lead MV(þ): rate exercise recovery † ACT(0) and ACT ¼ Accelerometer Blending QT(þ): QT ¼ Unipolar evoked QT † ACT.QT limited rate † ACT ¼ QT † ACT(þ) and † ACT,QT QT(0): decrease to LRL CLS ¼ Unipolar ventricular No blending: † ACT(0) and impedance No ACT rate CLS(þ): ACT ¼ Accelerometer contribution limited Rate response rate response determined by † ACT(þ) and CLS only CLS(0): no rate response Blending Nil PEA ¼ accelerometer at † Up to Middle ventricular lead tip rate: ACT ¼ gravitational sensor PEAþACT † .Middle rate: PEA only Automaticity Rate profile optimization AutoLife style Automatic matching MV sensor to LRL and SURL Automatic matching QT sensor to LRL and SURL ‘Auto response factor’ adjusts CLS data to reach rate distribution determined by the programmed ‘Exertion threshold Rate’ Manual adjustment to match peak PEA from trend data to the desired SURL ACT, Activity; MV, Minute ventilation; ADL, Activity of daily living; ER, Exertion range; LRL, Lower rate limit; SURL, Sensor upper rate limit; CLS, Closed loap simulation; PEA, Peak endocardial acceleration. MV monitoring may be useful to detect heart failure decompensation. Clinical experience Compared with VVI pacing, MV-driven VVIR pacing increased exercise capacity by 33%,6 and VO2 and cardiac output are significantly better. MV driven-VVIR pacing rate was highly correlated with measured MV, respiratory quotient, VCO2, tidal volume, and VO2 and (correlation coefficient .0.8 in all cases). Improvement in symptoms was also documented in the VVIR mode.17 MV has good long-term stability, programming of the sensor is relatively simple, and the rate response was appropriate during daily activities. Compared with activity pacing, MV is significantly better in achieving a near normal HR–workload relationship, whereas activity sensing tends to overpace (too fast) at low levels of exercise, underpace (too slow) at peak exercise and in the recovery period. When metabolic–chronotropic relations are studied,12 MV gives a better proportionality and rate recovery pattern compared with activity sensing. The Medtronic MV pacer (KappaTM 400) is combined with activity and only the combined sensor or activity alone rate-adaptive modes are used (Table 2). In the Evolution of pacing for bradycardias Boston MV devices (Pulsar MaxTM and InsigniaTM ), MV or activity can be used either alone or blended with the accelerometer. In the Sorin-ELA MV Devices (ChorusTM , TalentTM , OpusTM , SynphonyTM, RhapsodyTM ) the automatic slope algorithm allowed a good correlation coefficient between the sensor rate and programmer derived sensor rate at 0.983 + 0.005, and a linear relationship was observed between the HR and MV reserves.17 Limitations MV sensor devices are not recommended for patients with lung disease or in the paediatric age range, and the sensor should be inactivated in ventilator-dependent patients. A bipolar atrial/ventricular lead is needed for MV sensing. The battery current for MV sensing may take up to about 2% of the total current of a dualchamber pacemaker. There is a possibility of the small impedance pulses interfering with ECG machines, false detection of electrical signals such as diathermy mimicking an increase in MV. Respiration is also potentially influenced by phonation and coughing, which have no relevance to cardiac output. I17 condition after about 1 min, the pacing rate will decrease towards the QT-indicated rate. Conversely, when the QT interval shortens, while no activity is detected, mental stress or isometric exercise is most probable. Under these circumstances, the pacemaker is designed to increase the pacing rate, although the magnitude of the response is limited. The combined sensor has been shown to predict normal sinus activity especially in the range of daily activities. Unipolar ventricular impedance (‘closed-loop stimulation’ sensor) Contractility of the ventricle will increase during catecholamine stimulation, as occurs during exercise and emotional stresses. In the absence of an adequate rate response, exercise will induce a higher contractility that will decrease when rate response is adequate, thus establishing a negative feedback loop and a new steady contractile state.19 Evoked QT interval-based pacemakers QT interval shortening during exercise consists of two components: an effect induced by exercise alone and an effect of increased HR. The advantages of the QT sensor are that it requires no additional hardware and as QT reflects the level of adrogenic stimulation, it is potentially a highly sensitive sensor. The main limitation is the relatively slow response of QT to exercise, which often results in post-exercise tachycardia.15 Baig et al.18 found that the degree of QT interval shortening is least at low HRs, thus the QT-HR slope should be highest at low HRs and decrease gradually as the HR increases. The slope setting for low rates is adjusted automatically every night by measuring the QT interval at two different rates near the lower rate limit (daily learning). At the upper rate, the slope is adjusted in such a way that pacing at the upper rate occurs at the patient’s shortest QT interval. Further shortening of the QT interval while pacing at the upper rate, an indication that the patient reached the upper rate at submaximal exercise levels causes the slope at high rates to decrease. Clinical experience Only Vitatron (Medical BV, Arnhem, NL) combined QT-activity devices (TopazTM , DiamondTM , SelectionTM ) were available using QT and activity sensors together. In addition to improving the pattern of QT rate adaptation using the quick initial response by the piezoelectric sensor, the overall sensor specificity can be improved by cross-checking of the information between the two sensors. If the two sensors provide consistent information, either exercise or recovery is confirmed, and the pacing rate will increase or decrease respectively. If false-positive activity signals are received (increases in the activity counts without a change in the QT interval), the pacemaker will initially start to increase the pacing rate. If the QT interval still does not indicate an exercise Sensor and algorithm The closed-loop stimulation (CLS) sensor is based on unipolar impedance at the tip of a pacing lead.19,20 Subthreshold pulses of automatically selected outputs (ranging from 100 to 400 mA), biphasic duration of 46 ms are emitted 50–300 ms after a sensed or paced ventricular event. As two pulses are required for an impedance measurement, eight samples are taken per cardiac cycle. During diastole [immediately after ventricular pace (Vp) or ventricular sense (Vs)], there is more blood around the electrode tip, and the impedance is low. On the other hand, as contraction occurs, the walls surrounding the electrode tip get closer and impedance rises. A baseline waveform will occur depending on the conduction state of the heart: As Vs, AsVp, ApVs, ApVp, the timing of the cardiac cycle, and the chronotropic state. As the field strength falls off rapidly away from the lead tip, approximately 90% of impedance measured will be within 1 cm from tip. Thus the effect of respiration is limited. Baseline CLS waveforms will only be acquired when the associated accelerometer indicates no activity, and a waveform will be discarded within 48 h if not referenced. An average template of the baseline CLS waveform will take 2–3 days to optimize. As contractility increases during exercise, unipolar impedance will change. In the Biotronik CLS devices (InosTM , ProtosTM ), physiological rate adaptation was possible in 93 and 96% of patients with these devices, respectively.20 Apart from exercise rate response, a moderate level of rate response was documented in some patients with CLS pacemakers during these non-exercise stresses, such as colour word matching and during infusion of inotropes. Studies are underway to determine the benefit of CLS sensor pacing on cognitive function and recognition of vasovagal syncope. The use of CLS in the LV as in a CRT device for hemodynamic optimisation or monitoring would be of interest. I18 Advantages and limitations As a contractility sensor, CLS is sensitive not only to exercise but also to non-exercise requirements, and it may therefore be used for monitoring cardiac contractility for non-rate augmentation purposes. Like the QT sensor, CLS can only be used in a pacing mode that incorporates a ventricular lead. It is likely that CLS is affected by RV ischaemia or cardioactive medications. Peak endocardial acceleration Peak endocardial acceleration (PEA) detects the endocardial vibration during isovolumetric contraction by an accelerometer incorporated into the tip of a pacing lead. This signal is in close relationship with the intensity of the first heart sound. The one developed by Sorin ELA Biomedica is termed the BEST sensor (Biomechanical Endocardial Sorin Transducer); an acceleration sensor is built into an indeformable capsule located on the tip of a standard unipolar ventricular-pacing lead.21 This system has a frequency response up to 1 kHz and a sensitivity of 5 mV/G (1 G ¼ 9.8 m/s per second). PEA-1 occurs at 150 ms after the R wave, and is proportional to the positive dp/dt during inotropic stimulation (r ¼ 0.83).21 A smaller signal also occurs in the 100 ms period after the T wave, the so-called PEA-2, which corresponds to the isovolumetric LV relaxation, and may relate to negative dp/dt and aortic diastolic pressure. A good correlation between the sinus rate and PEA sensor-indicated rate during daily life activities and submaximal stress testing occurred.22 During maximal treadmill exercise testing, the increase in PEA was found to correlate with exercise intensity, whereas the changes at lower levels of exercise are less discriminative. PEA signals have been used to monitor haemodynamic function. A minimum PEA level occurs at the optimal AV interval, and this has shown some promise in automatically optimizing the AV interval. An increase in PEA during head up tilt has been observed, and the use of PEA-driven overdrive pacing in patients with vasovagal syncope has been reported. C.-P. Lau et al. input. Thus, it is logical to enhance their rate response profile by combining two or more sensors. There are two principles of sensor combination, sensor blending and sensor cross-checking. Sensor blending involves combining of the sensor-driven rates from individual sensors in a certain ratio. This can be the ‘faster wins’ method in which the higher rate is chosen as the dual-sensor rate, or ratios of the individual rates are added together to compile the ultimate rate response. Sensor cross-checking enhances the specificity of each sensor. Details of the combined QT and activity, CLS and activity, and PEA and activity devices have been presented above and in Table 2. Medtronic Kappa 400TM A piezoelectric sensor is used for activity sensing, and MV is sensed from a bipolar ventricular lead. Differential sensor blending is used. Up to the activity of daily living (ADL) rate such as 90 b.p.m., activity input predominates, whereas MV-driven pacing will predominate at the upper rate. Activity and MV sensors are checked against one another. In the absence of piezoelectric sensor indicating exercise, MV pacing will only reach the ADL rate, and vice versa. Only when both MV and activity signify exercise will pacing above the ADL rate occur. In the dual-sensor mode, rate adaptation is achieved automatically using the ‘rate profile optimization’. This requires the input of the ADL and exertion rates, together with the percentage of time spent in each rate (range 1–5). The sensors will adjust to fit the changes. The dual-sensor rate response has been reported to be reliable for both maximal and submaximal activities, and resistant to non-physiological interference Compared with a MV sensor alone, dual-sensor mode reduces oxygen deficit acquired during exercise by enhancing the initial rate response and ‘rate profile optimization’ was found to be a useful method for rateadaptive programming, and comparable with manual programming. Advantages and limitations Boston Scientific InsigniaTM , Pulsar MaxTM PEA is a proportional sensor that shows good correlation with workload especially at the higher ranges. The PEA sensor is limited by the need for a specialized lead, and there remains a concern over its longer-term stability. Concern also exists over this lead at pacemaker replacement with a conventional pacemaker. An accelerometer activity sensor is integrated with the MV sensor. Differential sensor blending is used. At low HR, the blended sensor rate receives contributions of approximately 80% by the accelerometer, and 20% by MV sensor. In a recent study,23 120 patients with InsigniaTM were randomized to the accelerometer single sensor, MV single sensor, and dual-sensor modes, each for a 3 month period. Using the implanted ‘Activity Log’ to determine the mean percentage and intensity of activity, quality of life and NYHA classes were assessed at the end of each period. Overall, either single sensor DDDR mode improved ‘Activity Log’, quality of life, and NYHA scores compared with DDD pacing, but there was no difference between the two sensors and dual-sensor mode. This study may be limited by the prolonged triple crossover design. Current combined sensor devices Experience with sensors has suggested that fast responding sensors such as activity are not proportional at higher levels of workload, whereas a proportional sensor is usually slow in response.15 Furthermore, single sensors may be limited by insensitivity to non-exercise stress, and are liable to be interfered with by non-physiological Evolution of pacing for bradycardias I19 Programming of rate-adaptive sensors Symptoms and quality of life Early studies on sensors have used treadmill or bicycle testing for assessing sensor programming. These give objective assessment of metabolic–chronotropic relationship.12 However, most pacemaker recipients are elderly and are unlikely to perform endurance exercise. Rather, they are engaged in activities of daily living, which are often brief activities such as walking and stair climbing.6 In these activities, rapidity in rate onset and a reliable rate response are important, and different sensors may give different responses depending on how the activity is carried out (e.g. walking upstairs has a lower rate in activity sensor than that achieved in going downstairs). Programming should thus be individualized based on patient daily activities. Manual programming according to daily activities appears to be effective and durable for many sensors.6,16 Progamming softwares such as the ‘Prediction Model’ and ‘Fast Learn’ are useful to assess acute rate response. With time constraints during follow-up, most sensors are now programmed automatically. Automatic programming is effective in general, although this has not been extensively studied. Rate profile optimization and ADL programming in MV and activity sensors have been found to be reliable, but a more aggressive setting is often required over time. Similarly, matching of QT and activity sensor to sinus rate can be achieved, although the maximum rate is less often attained using the automatic algorithm. It appears that the current automaticity approaches are effective although somewhat conservative. Additional programming will be needed when an accurate sensor response is needed for those with symptoms. Sensor overpacing should be considered after a period of patient inactivity, as the baseline sensor level may become very low. Many exercise studies have reported an improvement in exertional dyspnoea during graded exercise in the rateadaptive modes. In one study, a strong non-significant trend of better quality of life was observed in the VVIR mode compared with VVI pacing using a non-diseasespecific measure.25 A significant improvement in shortness of breath and energy occurred during daily activities. In 22 patients with AV block and chronotropic incompetence randomized to DDDR, DDD, DDIR, and VVIR modes,26 most patients preferred the DDDR mode and perceived ‘general well being’ and ‘functional status’ symptoms were worse with VVIR pacing. MV sensor pacing was compared with accelerometerdriven pacing in 105 patients.27 There is no significant difference in exercise capacity, symptoms, quality of life and 6 min walking distance, and similar percentage of physical activity scores as registered with the accelerometer sensor. However, in 17% of these patients with a high level of chronotropic incompetence, dualsensor pacing improved quality of life over single sensor pacing. Proven benefits and indications of rate-adaptive pacing Exercise benefits Compared with VVI pacing, VVIR pacing has been shown to increase maximum exercise duration by 69% (34– 114%), by achieving an increase in pacing rate of 32% (range 15–59%).24 The changes appear not to depend on the types of sensors used. Several studies have also documented an increase in anaerobic threshold and peak level of oxygen consumption. Oxygen transport kinetics is improved using a fast responding sensor such as activity compared with a slowly responding sensor such as QT, resulting in a lower oxygen debt during short bursts of exercise. Cardiac output is also higher in the VVIR mode compared with VVI pacing. The benefit of DDDR vs. VVIR in terms of exercise capacity is less obvious. One study has suggested that in patients with severe chronotropic incompetence, DDDR resulted in a better cardiac output at peak exercise without significant difference in exercise capacity compared with VVIR pacing. Cardiovascular outcomes None of the existing trials are large enough to assess the benefit of rate adaptation on cardiovascular outcomes. Pacing trials so far have focused on comparing atrial vs. ventricular pacing modes, with rate adaptation used in both arms.28 A meta-analysis shows no significant reduction in mortality or heart failure in DDDR vs. VVIR mode. However, there is a significant reduction in atrial fibrillation together with a borderline reduction in stroke. A post hoc analysis of the effect of sensor types in the MOST trial has been recently reported.29 This study is a comparison of DDDR vs. VVIR pacing in sinus node disease followed up for 6 years. Of these, 449 patients had accelerometer pacemaker sensor, 682 with piezoelectric sensor, and 114 with blended sensor (piezo electric and MV) in either the DDDR or VVIR mode. The median ventricular pacing frequency was 80%. Over a follow-up of 33.1 months, the risk of death, heart failure hospitalization, atrial fibrillation and the combined endpoint of mortality, and stroke were similar between the different sensor types after adjusting for baseline differences. However, dual-sensor pacing might be associated with significantly worse physical function than other sensor types. Although the baseline difference may explain the differences observed, it is reasonable to conclude that sensor difference seen on exercise may not be significant enough to affect cardiovascular outcomes and a major improvement in quality of life. Should all pacemakers be rate modulated? Taken together, the obvious and large exercise benefit of VVIR over VVI pacing is not reflected by a similar degree of improvement in symptoms, quality of life, and major cardiovascular outcomes. AV synchrony I20 remains important in the prevention of AF, and clinically important differences between major sensors and their combinations are not observed. These apparent incongruities may be due to the differences in patient populations studied, the degree of chronotropic incompetence, sub-optimal sensor programming, and the LV function. There is a possibility that the benefit of rateadaptive pacing may be offset by a higher percentage of RV apical pacing induced by the sensor. In a study of 15 patients with intact AV conduction capacity,30 AAIR and DDDR pacing were both superior to VVIR pacing during acute and ambulatory blood pressure monitoring, and an improvement in symptoms was observed. Interestingly, AAIR pacing by preserving intrinsic conduction, resulted in a strong trend to better haemodynamics over DDDR pacing with rate-adaptive AV interval in the same study. Thus, the role of rate adaptation without introducing unnecessary ventricular pacing may be an important rate-adaptive mode to address. In the 1998 AHA/ACC guideline for Pacemaker and ICDs (and its 2002 update), rate-responsive prescription is indicated in either VVIR or DDDR mode over VVI pacing with respect to quality of life in the elderly. However, the choice of rate response or not is left to the clinical decision of the implanting physician, and optimal programming of the sensor is recommended. It should be remembered that in most, if not all, pacing mode trials have used rateadaptive mode as the control arm in comparison with DDD(R) pacing, showing a lack of major benefit of AV synchrony over conventional VVIR mode. A cost issue of the sensor is probably unimportant as a sensor is incorporated in most modern devices. Sensors for monitoring Although sensors used for rate adaptation are a mature art, the use of sensors to monitor pacemaker function and cardiovascular conditions is becoming an increasingly important field. For example, the ability to detect the evoked intracardiac R wave may provide a means for capture detection and allow automatic regulation of the stimulus amplitude based on threshold measurements. AV interval optimization using PEA, a stroke volume sensor, and oxygen saturation sensor have also been proposed. Heart failure monitoring The most important monitoring role of sensors is in heart failure management. Heart failure is emerging as a major cause of morbidity and mortality. Hospitalization entails a 22% mortality in the next 9 months and 46% of survivors were readmitted. Specialized heart failure clinics with nursing supervision can reduce hospitalization, leading to reduced cost and mortality. The onset of symptoms, change in body weight, and external monitors have poor sensitivity and specificity for out-patient assessment of heart failure. An implantable sensor is ideal to track the pathophysiological consequences of heart failure (Figure 2). Although a large number of sensors have C.-P. Lau et al. been suggested, use of a RV pressure sensor has been tested.7 A piezoelectric crystal is incorporated in the tip of a pacing lead positioned in the RV outflow tract. RV diastolic pressure at its maximum negative derivative is used as a surrogate of pulmonary diastolic pressure, and reflects fluid overload status. RV pressures were elevated in 9/12 heart failure hospitalizations and may antedate clinical symptoms by 4 days. In the Chronicle Offers Management to Patients with Advanced Signs and Symptoms of Heart Failure trial presented as a late breaking trial at the 2005 American College of Cardiology Meeting, the use of RV pressure data resulted in a reduction of 22% heart failure events (P ¼ NS) and a 21% reduction in hospitalization (P , 0.05), over conventional heart failure clinic supervised treatment. Central venous oxygen measurement has been used to monitor heart failure and showed good correlation with invasive measurement, although the long-term sensor stability remains an issue. Heart rate variability and night time HR are useful surrogates of worsening heart failure. A standard deviation of 5 min median atrial rate interval of ,50 ms is associated with heart failure decompensation. This has similar sensitivity in predicting heart failure compared with a reduction in accelerometer-recorded activity level. Cardiac failure will increase pulmonary venous congestion and oedema, and results in a reduction in impedance level measured across the chest. In some devices (Insynch Sentry or Concerto, Medtronic Inc.), impedance currents are injected between the ICD RV coil and the ICD at 12 to 5 p.m. to intermittently sample impedance values. An increase impedance of 60 V/day over a 30 days’ average is indicative of fluid overload. In the original algorithm this change in impedance correlated with the invasively measured pulmonary capillary wedge pressure.31 More importantly, during 26 hospitalizations a reduction of 13.1 + 7% impedance was observed at 11 days before admission. At the expense of 1.5 falsepositive hospitalizations each year, the algorithm has an 80% sensitivity in predicting heart failure. However, in a larger series, the algorithm set at 60 V/day has been found to be too sensitive, and 120 V/day is suggested to reduce false-positive heart failure detection. Importantly, the absence of OptivolTM alert usually suggests freedom from heart failure. Other heart failure monitors that have been suggested include invasively measured left atrial pressure (through an atrial transeptal device), implanted ultrasound crystals, PEA, and CLS to monitor cardiac contractility. Orthostatic hypotension and neurocardiogenic syncope Orthostatic hypotension may cause syncope, and change in posture can be detected by triaxial accelerometers, preejection interval, and PEA changes. Interestingly, orthostatic hypotension was present in 30% of elderly patients with pacemakers, and especially in those with chronotropic incompetence.31 The use of overdrive pacing may ameliorate the fall in blood pressure in these individuals. Evolution of pacing for bradycardias I21 Figure 2 Pathophysiological changes during left ventricular failure open the opportunity for monitoring. See text for further discussion. CLS, closed loop stimulation sensor; HR, heart rate; HRV, heart rate variability; PEA, peak endocardial acceleration; LV, left ventricular; LVEDP, left ventricular enddiastolic pressure; LAP, left atrial pressure; PAP, pulmonary arterial pressure; RVP, right ventricular pressure; PCWP, pulmonary capillary wedge pressure. Sleep apnoea Sleep-disordered breathing can occur in up to 30% of patients with pacemakers and 50% in those with CRT. This can be detected with pacemaker-recorded MV impedance.32 In 42 patients with a pacing system that automatically detected transthoracic impedance, severe apnoea/ hypopnoea was identified with 75% positive predictive accuracy. Activity sensing has also been suggested to be useful to monitor the low-frequency chest wall motion during sleep to identify apnoea. Pacemaker detection of apnoea allows automatic intervention such as by atrial pacing, and respiratory muscle stimulation to be applied. Other applications The change in evoked R wave has been suggested to correlate with the onset of heart transplant rejection. PEA II and sensors implanted in the pulmonary artery have been suggested to monitor arterial pressure in hypertensive subjects. It is entirely possible that chemical levels such as glucose and electrolytes can be monitored by implanted sensors. Conclusion Since its conception 30 years ago, rate-adaptive pacing is now a standard parameter in modern pacemakers and ICDs. Sensors in use include the sensing of activity, MV, QT, and a variety of special lead sensors. These sensors differ in sensitivity, specificity, speed of response, and proportionality to exercise. Rate adaptation has shown improvement in exercise physiology particularly over the VVI pacing mode. It is clinically indicated in patients with chronotropic incompetence. There is no major observable difference in clinical outcomes and symptom benefit between different sensors and their combinations. The use of rate-adaptive sensors in CRT, and appropriate rate adaptation without excessive RV apical pacing remain to be evaluated. Haemodynamic and other monitored parameters are becoming an area of major innovation in sensor technology. Conflict of interest: none declared. References 1. Cammilli L. Initial use of a PH triggered pacemaker. Pacing Clin Electrophysiol 1989;12:1000–1007. 2. Rickards AF, Norman J. Relation between QT interval and heart rate: new design of physiologically adaptive cardiac pacemaker. Br Heart J 1981;45:56–61. 3. Wirtzfeld A, Goedel-Meinen L, Bock T, Heinze R, Liss HD, Munteanu J. Central venous oxygen saturation for the control of automatic rate responsive pacing. Pacing Clin Electrophysiol 1982;5:829–835. 4. Rossi P. The birth of the respiratory pacemaker. Pacing Clin Electrophysiol 1990;13:812–815. I22 5. Humen DP, Kostuk WJ, Klein GJ. Activity-sensing, rate-responsive pacing: improvement in myocardial performance with exercise. Pacing Clin Electrophysiol 1985;8:52–59. 6. Lau CP, Antoniou A, Ward DE, Camm AJ. Initial clinical experience with a minute ventilation sensing rate modulated pacemaker: improvements in exercise capacity and symptomatology. Pacing Clin Electrophysiol 1998;11:1815–1822. 7. Adamson PB, Magalski A, Braunschweig F, Böhm M, Reynolds D, Steinhaus D, Luby A, Linde C, Ryden L, Cremers B, Takle T, Bennett T. Ongoing right ventricular hemodynamics in heart failure: clinical value of measurements derived from an implantable monitoring system. J Am Coll Cardiol 2003;41:565–571. 8. Yu CM, Wang L, Chau E, Chan RH, Kong SL, Tang MO, Christensen J, Stadler RW, Lau CP. Intrathoracic impedance monitoring in patients with heart failure: correlation with fluid status and feasibility of early warning preceeding hospitalisation. Circulation 2005;112: 841–848. 9. Karlof I. Haemodynamic effect of atrial triggered versus fixed rate pacing at rest and during exercise in complete heart block. Acta Med Scand 1975;197:195–206. 10. Kristensson BE, Arnman K, Ryden L. The haemodynamic importance of atrioventricular synchrony and rate increase at rest and during exercise. Eur Heart J. 1985;6:773–778. 11. Wilkoff BL, Corey J, Blackburn G. A mathematical model of the cardiac chronotropic response to exercise. J Electrophysiol 1989;3: 176. 12. Kay GN. Quantitation of chronotropic response: comparison of methods for rate-modulating permanent pacemakers. J Am Coll Cardiol 1992;20:1533–1541. 13. Greenberg B, Chatterjee K, Parmley WW, Werner JA, Holly AN. The influence of left ventricular filling pressure on atrial contribution to cardiac output. Am Heart J 1982;49:687–692. 14. Tse HF, Siu CW, Lee KLF, Fan K, Chan HW, Tang MO, Tsang V, Lee SW, Lau CP. The incremental benefit of rate-adaptive pacing on exercise performance during cardiac resynchronization therapy. J Am Coll Cardiol 2005;46:2292–2297. 15. Lau CP, Tse HF, Kay N. Sensor driven pacing: device specifics. In: Ellenbogen K, Kay N, Lau CP, Wilkoff B, eds. Clinical Cardiac Pacing Defibrillation, and Resynchornization Therapy. 3rd ed. Philadelphia: Saunders Elsevier, 2007. Ch. 16, pp. 499–530. 16. Benditt DG, Mianulli M, Fetter J, Benson DW, Jr, Dunnigan A, Molina E, Gornick CC, Almquist A. Single-chamber cardiac pacing with activity-initiated chronotropic response, evaluation by cardiopulmonary testing. Circulation 1987;75:184–191. 17. Bonnet JL, Geroux L, Cazeau S, on behalf of the French Talent DR Pacemaker Investigators. Evaluation of a dual sensor rate responsive pacing system based on a new concept. Pacing Clin Electrophysiol 1998;25:2198–2203. 18. Baig MW, Wilson J, Boute W, Begemann MJ, Cobbold JP, Perrins EJ. Improved pattern of rate responsiveness with dynamic slope setting for the QT sensing pacemaker. Pacing Clin Electrophysiol 1989;12: 311–320. 19. Schaldach M, Hutten H. Intracardiac impedance to determine sympathetic activity in rate responsive pacing. Pacing Clin Electrophysiol 1992;15:1778–1786. C.-P. Lau et al. 20. Witte J, Reibis R, Pichlmaier AM et al. ANS-controlled rate-adaptive pacing: clinical evaluation. Eur J Cardiac Pacing Electrophysiol 1996;6:53–59. 21. Plicchi G, Marcelli E, Parlapiano M, Bombardini T. PEA I and PEA II based implantable haemodynamic monitor: pre-clinical studies in sheep. Europace 2002;4:49–54. 22. Clementy J. Dual chamber rate responsive pacing system driven by contractility: final assessment after 1-year follow-up. The European PEA Clinical Investigation Group. Pacing Clin Electrophysiol 1998; 21:2192. 23. Charles RG, Heemels JP, Westrum BL. Accelerometer-based adaptiverate pacing: a multicenter study. European EXCEL Study Group. Pacing Clin Electrophysiol. 1993;16:418–425. 24. Lau CP. Comparative hemodynamic studies between different rate adaptive modes. In: Lau CP (ed.), Rate Adaptive Cardiac Pacing. Armonk, NY: Futura Publishing Co Inc, 1993. Ch. 5, pp. 51–62. 25. Lau CP, Rushby J, Leigh-Jones M, Tam CY, Poloniecki J, Ingram A, Sutton R, Camm AJ. Symptomatology and quality of life in patients with rate-responsive pacemakers a double blind cross-over study. Clin Cardiol 1989;12:505–512. 26. Sulke N, Chambers J, Dritsas A, Sowton E. A randomised double-blind crossover comparison of four rate-responsive pacing modes. J Am Coll Cardiol 1991;17:696–706. 27. Padeletti L, Pieragnoli P, di Biase L, Colella A, Landolina M, Moro E, Orazi S, Vicentini A, Maglia G, Pensabene O, Raciti G, Barold SS. Is a dual-sensor pacemaker appropriate in patients with sino-atrial disease? Results from the DUSISLOG study. Pacing Clin Electrophysiol 2006;29:34–40. 28. Healy JS, Toff WD, Lamas GA, Andersen HR, Thorpe KE, Ellenbogen KA, Lee KL, Skene AM, Schron EB, Skehan JD, Goldman L, Roberts RS, Camm AJ, Yusuf S, Connolly SJ. Cardiovascular outcomes with atrial-based pacing compared with ventricular pacing with meta analysis of randomized trials, using individual patient data. Circulation 2006;114:11–17. 29. Shukla HH, Flaker GC, Hellkamp AS, James EA, Lee KL, Goldman L, Orav EJ, Lamas GA. Clinical and quality of life comparison of accelerometer, piezoelectric crystal, and blended sensor in DDD-R paced patients with sinus node dysfunction in the mode selection trial (MOST). Pacing Clin Electrophysiol 2005;28:762–770. 30. Lau CP, Tai YT, Leung WH, Wong CK, Lee P, Chung FL. Rate adaptive pacing in sick sinus syndrome: effects of pacing modes and intrinsic conduction on physiological responses, arrhythmias, symptomatology and quality of life. Eur Heart J 1994;15:1445–1455. 31. Tse HF, Lau CP, Park E, Bornzin GA, Yu C, Benser ME, Bloomfield DM, Padeletti L. Transient overdrive pacing upon standing prevents orthostatic hypotension in elderly pacemaker patients with chronotropic incompetence. Pacing Clin Electrophysiol 2007;30: 188–192. 32. Scharf C, Cho YK, Bloch KE, Brunckhorst C, Duru F, Balaban K, Foldvary N, Liu L, Burgess RC, Candinas R, Wilkoff BL. Diagnosis of sleep-related breathing disorders by visual analysis of transthoracic impedance signals in pacemakers. Circulation 2004;27;110: 2562–2567.