Download Evolution of pacing for bradycardias: sensors

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
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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.
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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
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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.
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