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Studies on cardiac pacing : emphasis on pacemaker sensors and cardiac resynchronizationtherapy

Yılmaz, A.

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Citation for published version (APA):Yılmaz, A. (2005). Studies on cardiac pacing : emphasis on pacemaker sensors and cardiac resynchronizationtherapy. Amsterdam: Amsterdam University Press.

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Download date: 25 Feb 2020

Individuall optimization of pacing sensorss improves exercise capacity withoutt influencing quality of life

Aytenn Erol-Yilmaz MD. Tim A, Schrama, Jutta Schroeder Tanka*, MD PhD, Jann G. Tijssen PhD, Arthur A. Wilde MD PhD, and Raymond Tukkie MD PhD

Fromm the department of Clinical and Experimental Cardiology, Academic Medical Centerr and the department of Cardiology. Sint Lucas-Andreas hospital*, Amsterdam,

Thee Netherlands.

PACEPACE 2005;28:17-24

Abstract t

Introductio n n

Programmablee pacemaker sensor features are frequently used in default setting.

Limitedd data are available about the effect of sensor optimization on exercise

capacityy and quality of life (QOL). Influence of individual optimization of sensors

onn QOL and exercise tolerance was investigated in a randomized, single blind study

inn patients with WIR. DDDR or AAIR pacemakers.

Materiall and methods

Patientss with >75% pacing were randomized to optimized sensor settings (OSS) or

defaultt sensor setting {DSS). Standardized optimization was performed using three

differentt exercise tests. QOL questionnaires {OOL-q: Hacettepe, Karolinska and

RAND-36)) were used for evaluation of the sensor optimization. One month before

andd after optimization, exercise capacity using CAEP and the three QOL-q were

assessed. .

Results s

Fifty-fourr patients (26 men. 28 female) with a mean age of 65 16 years were

enrolledd in the study. In each group (OSS and DSS) 27 patients were included. One

monthh after sensor optimization the achieved maximal HR and METS were signifi-

cantlyy higher in OSS compared to DSS (124 28 vs. 108 20 bpm, p=0.036; 7.3 4

vs.. 4.9 4 METS, p = 0.045). Highest HRand METS were achieved in patients with

pacemakerss with accessible sensor algorithms. In patients with automatic slope

settingss (33 %). exercise capacity did not improve after sensor optimization. QOL

didd not improve in OSS compared to DSS.

Conclusions s

Afterr 1 month of individual optimization of rate response pacemakers, exercise

capacityy was improved and maximum heart rate increased, although QOL remained

unchanged.. Accessible pacemaker sensor algorithms are mandatory for individual

optimization. .

6 6

Chapterr 4

Introductio n n

Thee normal heart adapts its rate in response to the body's changing metabolic

demandss and is therefore chronotropically competent. Earlier generation of pace-

makerss provided constant rate and were unable to maintain or restore chronotropic

competence.. Since the first permanent pacemaker implantation in 1958, there have

beenn tremendous advances in pacemaker technology with the availability of com-

plex,, multiprogrammable, dual chamber and rate adaptive pacemakers which could

meett the haemodynamic needs of an individual patient.1"3 Rate adaptive pacing

improvess cardiac output, exercise tolerance and a sense of well-being compared to

fixedd rate pacing.4

Normall sinus node function is used as the golden standard for the development of

thee ultimate pacemaker sensor. Sinus node behavior can be described with several

methods:: exercise testing protocols, the mathematical model according to Wilkoff

andd Holter monitoring in daily life. These methods together with evaluation of the

obtainedd quality of lif e (QOL) associated with a given sensor can all be used to

assesss the efficacy of a pacemaker sensor. The American college of cardiology

guideliness of exercise testing used for evaluating rate adaptive pacing advices

adjustmentt of the exercise test for the subjects need and however several exercise

testss (CAEP, LITE, Bruce, six minute walk test, Kaltenbach step test, stair climbing)

aree described, consensus lacks about the ideal exercise test protocol for pacemaker

sensorr optimization. 8"10' I4"19

Programmablee pacemaker sensor features are frequently used in default sensor

settingg (DSS) in daily practice, although rate responsive pacing has been reported to

improvee the physical capacity and QOL compared to fixed rate pacing. It is un-

knownn whether individual optimization of rate response is a necessary factor to

improvee QOL and exercise capacity with the existing sophisticated sensor technolo-

gyy compared to the default sensor setting (DSS) of the manufacturer.8 Therefore,

wee tested the effect of optimized sensor setting (OSS) with a standardized individu-

all optimization protocol and DSS on exercise capacity and QOL in patients with

AAIR,, W1R and DDDR pacemakers in a prospective single blind randomized trial.

Material ss and Methods

Patientt population

Fifty-fourr consecutive patients with >75% pacemaker sensor driven HR with mean

agee of 65 16 years (range 27 to 89 years), New York Heart Association (NYHA) class

I-- II. stable medication, stable psychosocial conditions and commercially available

pacemakerss (Medtronic Minneapolis USA. Guidant Minnesota USA, Vitatron Arn-

hemm The Netherlands) were included at least 3 months after pacemaker implanta-

tion.. Pacemaker type and pacing indication are described in table 1.

Fromm our existing institutional database of exercise testing in healthy controls (HO

withoutt co-morbidity and medical therapy , we selected nineteen age and exercise

typee matched individuals (mean age 66.5 6). All patients gave written informed

Tablee 1. Demographics and clinical variables

Patients s

Numberr of patients Agee (year) Sexx Imale/femalel [%) BMII ikg/m2} NYHAA class \l-4) LVEFF (normal/reduced. %) History y

CoronaryCoronary artery disease (%' HeartHeart valve insufficiency (%) Atria!Atria! fibrillation {%)

Medication n DigoxwDigoxw (%l ^-blocker^-blocker (%) CalciumCalcium antagonist {%} AmiodaroneAmiodarone {%)

Facemakerr type VitatronVitatron \%) MedtronicMedtronic (!fci GuidantGuidant i%1

Pacemakerr indication SSSW SSSW AVV nodal block (%i AFAF with AV nodal disease [%) AFAF with His bundle ablation iV Other Other

DSS S

27 7 066 16

59/41 1 299 6

1.77 0.9 89/11 1

4 4 6 6 42 2

4 4 10 0 6 6 2 2

41 1 33 3 26 6

15 5 15 5 11 1 52 2 7 7

OSS S

27 7 655 15 37/63 3 266 4 1.88 9 89/11 1

6 6 12 2 58 8

4 4 14 4 10 0 2 2

60 0 29 9 11 1

22 2 15 5 18 8 42 2

3 3

Tablee 1. DSS= default sensor setting: OSS= optimal sensor setting: BMI - body mass index: NYHAA = New York Heart Association: LVEF= left ventricular ejection fraction: SSS~sick sinus syndrome.. AV = atrioventricular: AF = atrial fibrillation.

78 8

Chapterr 4

consentt and the ethics committee of our institutio n approved the study.

Randomizationn protocol and study design

I nn thi s s ingle bl in d prospect ive randomized trial , pat ients were firs t randomized to

OSSS or DSS. Primar y endpoint of the study is exercise capacity. Patients in OSS were

thenn randomized to one of three exercise protocols used for opt imizat ion of the

sensor.. The three exercise tests were the six minut e hall walk test (6-HWT) , six

m inu t ee hall walk test wi t h stair c l imbin g (6-HWT+SC) and the chronotropi c assess-

mentt exercise protocol (CAEP) according to Wilkoff. 11

Al ll pat ients underwent at basel ine a CAEP exercise test wi t h posture change (PC)

andd sui tcase lift in g (SL) wi t h their pacemakers programmed in default sett ing. The

pacemakerss of the pat ients in OSS group were individual l y opt imized 1 month after

basel ine.. The CAEP test was repeated after 2 mon ths in OSS and DSS groups.

Qual i t yy of l i f e quest ionnaires (QOL-q) were assessed in all pat ients, 1 month before

andd after sensor opt imizat ion (see figur e 1).

Patients s

Baseline: : Groupp OSS (n = 271

CAEPP + PC+ SL in default

Groupp DSS (n = 27)

22 months

Afterr I month optimization using ++ QOL

Afterr 2 months: QOL +

t t

HWT T

t t

HWTT + SC

CAEPP + PC+ SL CAEP++ PC+ SL

Figuree 1. Randomization and flowchart of the study. OSS- optimalized sensor setting: DSS-defaultt sensor setting: CAEP- chronotropic assessment exercise protocol; PC- posture change:: SL- suitcase lifting: QOlq = quahty of lif e questionnaires: 6-HWT= 6 minute hall walk lest: SC== staircase ascent and descent.

79 9

Sensorr optimization

Alll sensor optimizations were done by one investigator (A-E.Y). The optimized

pacemakerr sensor setting was individually determined by 3 parameters: 1) detailed

analysiss of HR curve obtained with the exercise test after 1 month (onset of exer-

cise,, slope, total exercise time, time to peak HR, maximal HR). One of the three

exercisee tests (depending on randomization) were used for optimization (CAEP, 6-

HWTT or 6-HWT+SC). HR curves of 19 age matched HC (see figure 2) and the availa-

blee literature about normal HR during exercise were used as reference.12 2) upper

ratee limi t was programmed according to Astrand (220 - age)13 and 3) development of

complaints,, Threshold, lower rate limi t (LRL), upper rate limi t (URL), slope and

sensorr specific settings (sensor blending in dual sensor systems) were adjusted to

obtainn the predicted optimal sensor setting.

HR R

180 0 - * -- 6-HWT

P P

CAEP-HC C

- * -- 6-HWT-HC

i—i—i—i—n—i— rr r r t i i i—i—r~i—i—i—r—i—i—i—n—!—I—i—i—i—i—i—i— r

11 4 7 10 13 16 19 22 25 28 31 34 Minutes s

Figuree 2. Changes in heart rate ImeanV HR-heart rate; 6-HWT= 6 minute hall walk test: CAEP = chronotropicc assessment exercise protocol. HC = healthy controls.

SO O

Chapterr 4

Exercisee test protocols

PosturePosture change and suitcase lifting

Alll patients were examined in the same conditions (before noon, uniform room

temperaturee and footgear (patients own shoes)). After instrumentation, patients

restedd supine on an examination table with one pillow for 5 minutes. They then

elevatedd to the sitting position and immediately to the standing position for 2

minutes.. The patients raised a standard suitcase (9 kg weight and measuring 47 cm

xx 37 cm x 15 cm) from the floor onto the examination couch (a height of 100 cm)

usingg their preferred arm (left, right, both).

ChronotropicChronotropic assessment of exercise protocol

Alll patients underwent a symptom limited treadmill test using the CAEP protocol

accordingaccording to Wilkoff .

Onee MET equals 35 ml oxygen uptake/kg body weight/min. representing the

approximatee metabolic cost to stand quietly. In his protocol oxygen consumption

andd carbon dioxide production was not performed, and thus metabolic workload

(METSS ) was not directly measured during exercise. Rather, metabolic levels during

eachh stage of exercise were estimated using treadmill grade and speed.

SixSix minute hall walk test

Afterr 5 minutes of rest patients were brought to the parcour. A parcour of 100 m

wass created by attaching stickers each meter in an oval form showing the walk

distance.. Patients were instructed to walk or run for 6 minutes at the parcour after

hearingg the start sign. After the symptom limited 6-HWT, the patients were brought

backk to the test room for a recovery period of 10 minutes.

StaircaseStaircase descent and ascent

First,, the patients descended 5 flights of stairs as rapidly as possible (82 steps, with

totall horizontal distance of 41.5 m and vertical distance of 15 m). After 2 minutes of

rest,, the patients then ascended the same flights as fast as they could.

81 1

Qualityy of lif e

Too compensate for the limited pacemaker patient specific OOL-q, we used 3 OOL-q.

Thee Rand-36 consisting 9 domains (physical functioning, social functioning, role

functioningg physical problems, role functioning emotional problems, mental health,

energy,, domains bodily pain, general health perception and change in general

health)) was used as a generic core module. The Rand-36 was evaluated using the

scoree system from 0 to 100 % in each domain (0% =low OOL to 100% = high QOL). H

Thee second questionnaire assessed was the Hacettepe QOL-q. which is a pacemaker

patientt specific questionnaire with 8 domains (general well-being, physical activity

andd symptoms, sleeping dysfunction, appetite, sexual functioning, cognitive

functioning,, social participation and work performance). The scores of each domain

aree between 3-50 points. (3 = low QOL and 50 = high OOL).

Fromm the final questionnaire, the Karolinska OOL-q only A domains (chest pain,

palpitations,, dizziness, dyspnoea) were used as complementary to the other two

questionnaires.. The 4 domains of the Karolinska QOL-q were evaluated using Visual

Analogg Scales and required patients to place a mark along a line of 10 cm in length

fromm a minimum of 0 (no complaints) to a maximum of 10 (maximal grade of

complaints).. The results were expressed as a percentage of the distance from the

discretee minimum point to the position of the mark divided by the length of the

line.155 In the Rand-36 and the Hacettepe QOL-q a high score means a high OOL and

inn the Karolinksa QOL-q a high score means a low QOL.

Measurements s

Beatt to beat HR was recorded during the physical tests with the Polar advantage

systemm using electrodes mounted in a belt (Polar Electro OY, Kempele, Finland).

Duringg the CAEP exercise test patients were also continuously monitored by 12-lead

electrocardiographicc recordings. HR at rest, time to peak HR, maximal achieved HR.

HRR at 10 minutes recovery period, exercise duration and METS were measured, The

OOL-qq was assessed after 1 and 2 months of inclusion.

82 2

Chapterr 4

Statisticall analysis

Powerr analysis was performed on the primary endpoint of the study, exercise

capacityy in METS. Assuming that the common standard deviation is 35 and a mean

differencee in achieved METS is 3 (the difference between mean DSS l and OSS, JJL2

inn METS ), we calculated the power of 80 % using a two group t-test with a 0.05 two-

sidedd significance level. A sample size of 23 patients in each group DSS vs. OSS had

aa power of 80% to detect a difference in means of 3. Parametric data was analysed

usingg the Student's t-test while nonparametric data was analysed using the Mann-

Whitneyy U test. All data are expressed as mean SD. A P value <0,05 is considered

statisticallyy significant.

Results s

Fifty-fourr patients (26 men, 28 female) with a mean age of 65 16 years (range 27

too 89 years) were enrolled in the study. In each group (OSS and DSS) 27 patients

weree included. Demographics and baseline characteristics between both groups

weree not significantly different (see table 1).

Fivee patients (1 in OSS and 4 patients in DSS) withdrew from the study. The patient

inn group OSS stopped because of diagnosis of a pulmonary tumour. In group DSS,

threee patients stopped after programming to DSS because of symptoms of heart

failure.. The forth patient withdrew for psychosocial reasons.

Pacemakerr and sensor type

Thee majority of patients (58% in OSS group vs. 39% in DSS group) had pacemakers

equippedd with dual sensor systems of Vitatron (QT and activity. Vitatron. Arnhem

Thee Netherlands). Activity sensors were the most frequent used sensors in the

singlee sensor systems, The OSS group had 31% of activity sensors of Medtronic

(Medtronic.. Minneapolis USA), while the DSS group had 35% Medtronic and 9%

Guidantt (Guidant. Minnesota USA) activity sensors. Accelerometers of Guidant

(Guidant,, Minnesota USA) were used 17% in the DSS group and 11% in OSS.

83 3

Tciblee 2. Pacemaker optimization settings

Mode e Baseline e

WIRR i%! WII i%* DDDRR i%i ODDD i%l AAIRR i%̂ AAII i%l

4 4

26 6 9 9 4 4 7 7

fticemakerfticemaker settings changed Baseline

Afterr optimization

59 9 0 0 35 5 0 0 6 6 0 0

Afterr optimization Frequency of change (%)

LRMbprrO O URLL ibpm) THH ilow, medium/low. medium,, medium/high, high' S l o pee

Sensor r

60 0 1211 4.4f medium m

I I

default t QT=ACT T

611 2.7

14544 14.31 low,, medium/low

moree agressive OKACT.. ACT

12 2 92 2 11 1

15 5 31 1

Tablee 2. LRL = lower rate limit ; URL = upper rate limit : TH^threshold: QT= OT sensor: ACT = activityy sensor: \*) dependent of the manufacturer: response factor, response time or acceleration time:: blending OT=ACT-> 50:50. QT<ACT-> 25:75: t URL after optimization is significantly different,, p <0.001.

Sensorr optimization

Ratee response was programmed on in all patients. The LRL was changed in 12% of

thee patients but increased not significant. The URL was programmed higher in 92%

off patients, from 121 4.4 to 145.4 14.3 bpm, (p<0.001). The threshold was

changedd in 11% of the patients: from medium to medium/ low in 4% vs. medium to

loww in 7 % and the slope settings were changed in 15 % of the patients. The re-

sponsee factor vs. response time vs. acceleration of the slope was programmed in a

moree aggressive setting: from factor 8 to 14 in 7 % vs. 30 to 10 seconds in 4 % vs.

standardd to fast in 4 %. In 33% of patients, the slope settings could not be adjusted

duee to the autoslope setting inVitatro n pacemakers (Arnhem, the Netherlands),

despitee the need for a more aggressive slope setting. Sensor blending was changed in

311 %. In 12% the default sensor blending setting (QT = ACT) of the Vitatro n pacemak-

erss (Arnhem, the Netherlands) were programmed to activity only and in 19 % to

OT<ACT ,, see table 2.

84 4

Chapterr 4

Tablee 3. Summary of HR during rest, exercise and recovery

Restingg rate ibpm.1-Timee to peak HR ymui' Programmedd maximum Achievedd maximum HR 100 mill recovery ibpm.1

METS S

Exercisee duration mini. M.tximall HR during SI. Posturee change

HRR \bpm l

^bpm.1 1

DSS S

Baseline e

vn-27^ ^ Default t

677 14

100 5 1211 4

1099 21 744 10 66 4 111 5

711 12 722 11

22 months

li ii = 231 Default t

633 29 100 7

I21 4" 11 OS 20 #

666 6 4.99 4"

100 5 688 10

688 + 6

Baseline e

inn = 27̂ Default t

711 14

n 5 121 4

1144 15 777 10

7 4

5 5 711 13 700 10

inn = Q̂ CAEP P

700 13 111 +. 0

1477 + I4f I I SS 9 699 15

66 + 4 111 5

7 6 + 17 7

766 5

OSS S

22 months

inn = 81 6-HWT T

666 + 7 100 4

1422 12 S 128++ 34

65 7 7.88 4*

122 5 9 9

67 6

m-Ql l &-HWTT + SC

666 9 1 1 +5 5

1477 18+ * 1233 29 #

62 8

7.99 4* 133 * 4 68 8 67 7

P-value e

ns s ns s

t<0 .001 1 -*1== 0.036

ns s

0.045* * ns s ns s nn s

Tablee 3. HR= heart rate; bpm = beats per minute: min = minutes; DSS = default sensor setting. OSSS = optimalized sensor setting: CAEP= chronotropic assessment exercise protocol; 6-HWT = 6 minute halll walk test; SC= staircase ascent and descent; SL = suitcase lifting; #-11= the achieved maximal heart ratee is significantly higher in the total group of OSS compared to DSS, p = 0.036; * = the achieved METS wass significantly improved in the subgroups 6-HWT and 6-HWT +SC compared to These three exercise testss iCAEP. 6-HWT and ó-HWT +SO were used for optimization. DSS. p = 0.045.

HR R

140 0

1300 -

120 0

110 0

100 0

90 0

80 0

70 0

60 0 50 0

40 0

-*-DSS-B B -- 2 months

Rest t Exercise e Recovery y ~ii i r r T r ~!! T

33 6 9 12 15 18 21 24 27 30 33 36 Minutes s

Figuree 3. Changes in heart rate tinea nV HR = heart rate. DSS-B = default sensor setting at baseline.

S5 S5

HR R 160 0

140 0

120 0

100 0

SO O

60 0

40 0

-è^^ OSS-B 22 months

Rest t Exercise e Recovery y

- x -- -x--x-

11 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 Minutes s

Figuree 4. Changes in heart rate (mean). HR-heart rate: OSS-B- optimalized sensor setting at baseline.. *P = 0.036.

Exercisee test protocols

PosturePosture change, suitcase lifting

Thee achieved maximal HR during posture change and suitcase liftin g were compara-

blee in OSS and DSS at baseline and after 2 months (see table3). One patient could

nott lif t the suitcase.

chronotropicchronotropic assessment exercise protocol

Thee achieved maximal HR and METS after sensor optimization were significantly

higherr compared to DSS (124 28 vs. 108 20. p = 0.036: 7.3 4 vs. 4.9 4 METS,

p=0.045). .

Highestt increase in maximal HR, METS and exercise duration was achieved in the

subgroupss whereby the sensor was adjusted with 6-HWT (128 34 vs. 7.8 4 vs.12

86 6

Chapterr 4

5)and6-HWT +SC (123 29 vs. 7.9 4 vs. 13 4) compared to the subgroup

CAEPP (118 19 vs. 6 4 vs. 11 5Ï-

Otherr measured parameters between the groups and subgroups like resting rate,

timee to peak HR, HR at 10 minute recovery, maximal HR during suitcase liftin g and

posturee change were comparable between the two CAEP tests (see table 3, figure 3

andd figure 4).

Qualityy of lif e

Thee achieved scores from all the three QOL-q (RAND-3Ó, Hacettepe and Karolinska)

onee month after optimization compared to DSS were not significantly different.

Alsoo scores attained within the subgroups of the three QOL-q were not significantly

different. .

Discussion n

Exercise e

Ourr study shows that individual optimization of pacemaker sensors results in

improvedd exercise capacity. Also, after sensor optimization the reason for stopping

thee exercise test shifted to concomitant restrictions (e.g. physical activity level of

thee elderly pacemaker patients) rather than cardiovascular limitations. The in-

creasedd METS and HR indicate that patients have an improved exercise capacity

afterr sensor optimization

Thee highest benefit from optimization in achieved METS and maximal HR was

obtainedd with the 6-minute HWK and 6-minute HWK+ SC. In the CAEP subgroup,

theree were 33% more pacemakers with automatic slope settings, which could not be

individuallyy adjusted. Other possible factors, which could influence the exercise

capacityy between the groups. like medical history and medical therapy, were not

significantlyy different. These results underline the importance of individually

adjustmentt of pacemaker sensors and the necessity of accessible pacemaker

algorithms. .

Too date, limited studies investigated the effect of sensor adjustment and to the best

87 7

off our knowledge: our study is the first and largest randomized controlled study,

comparingg DSS with OSS in detail. Previous studies mainly compared different

sensorss and were not primarily designed to evaluate individual adjustment,5

Sulkee et al. showed that appropriate programming of sensors is crucial in rate

responsivee pacing. & In 20 patients the effects on exercise and QOL of appropriate,

overr and under programming of the sensor were assessed. In contrast to our study,

onlyy activity sensors were evaluated and the sensors were optimized according to

thee manufacturer's instructions without detailed insight in these instructions. In

anotherr study, Klonis et al. investigated whether automatic algorithms for sensor

optimizationn could reduce clinical follow up time compared to manual adjustment.

Usingg the activity level of patients (more active, the same, or less active) they

concludedd that automatic adjustment is less time consuming than manual adjust-

ment,, This study supports the current trend in increasing automaticity in pacemak-

ers,, although it is disputable if such a rough guide as three levels of activity can be

usedd as a guide for sensor optimization. In general, sensor optimization methods

aree poorly described, mostly referring to the manufacturers advice.

Inn agreement with previous reports, exercise duration was not significantly im-

provedd after sensor optimization.8 2D This can partly be explained by the category of

patientss in need of permanent pacing (elderly and relatively sedentary). In these

patients,, exercise is often limited by loss of muscle strength and mass rather than

cardiopulmonaryy capacity. This loss of muscle strength is particularly apparent

whenn exercise testing is performed on a bicycle or treadmill. The CAEP exercise test

consistt nonlinear characteristics. The first 10 minutes it requires a low metabolic

workload,, beyond which it increases abruptly. Patients with preserved functional

capacity,, capable of exercising for more than 10 minutes, may quit before reaching

maximall 02 uptake, mainly because of excessive increments in workload near the

endd of the test, thus, being limited by mechanical rather than metabolic barri-

ers.12211 In our study there is a trend to increase of exercise duration with a mean of

11 5 minutes. This increased exercise duration results in a higher achieved speed

andd steeper slope on the CAEP. And this longer exercise duration is achieved due to

thee higher achieved heart rate. The symptom limited 6 minute hall walk test resem-

bless closer daily activities and less time consuming compared to the treadmill or

bicyclee exercise tests. 22

Thee healthy controls achieved higher HR than patients despite individual optimiza-

tion,, probably because current sensors are still hypochonotropic and physicians feel

88 8

Chapterr 4

reluctancee to program such high upper rates due to concomitant heart disease. The

maximall HR in the default setting is generally too low, well below the age predicted

maximall HR of the mean age of a typical pacemaker patient of 70 year, according to

thee Astrand formula (220-age). An inappropriately low programmed maximum sensor

ratee and failure to reach maximum exercise will result in sensor indicated pacing rates

duringg exercise testing below the calculated expected HR. The clinician may attempt

too compensate for this by programming more aggressive rate response parameters

whichh may result in excessive rate response behavior of the pacemaker during the

patient'ss normal ambulatory activities.0

Qualityy of lif e

Qualityy of life did not improve with individual sensor optimization. Specific sub-

groupss that derived benefit were not observed, including stratified to device indica-

tion,, age or specific complaints. Again, only the study of Sulke et al. assessed the

effectt of rate responsive pacing on QOL. Appropriate, over and under programming

off the rate response were evaluated in both dual and single chamber activity sensor

ratee adaptive pacemakers with visual analog scales and specific activity question-

naires.. Symptoms were least in the appropriate programmed pacemakers after 2

weekss of follow up. The found differences between both studies could be explained

duee to the greater programming steps in Sulke's study (rate response off, appropri-

atee programming and aggressive programming). Another explanation for the failure

too improve QOL after sensor optimization could be the relatively good baseline

functionall capacity, because patients with relative preserved functional capacity at

enrollmentt show the lowest improvement in health related values.25

Alsoo in large pacemaker trials, improvements in QOL were minimal. The PAcemaker

Selectionn in the Elderly study (PASE, n=407) showed only in the subgroup with sick

sinuss syndrome a moderate improvement in QOL in patients with dual chamber

pacingg as opposed to ventricular pacing, whereas in the Canadian Trial Of Physiolog-

icc Pacing investigating (CTOPP, n = 172II only the global well being score was better

inn the physiologic vs. WIR mode.

Inn general, there is a lack of validated pacemaker patient specified quality of life

QOL-q.244 To date, only two questionnaires were specifically developed for pacemak-

err patients (Hacettepe Qol-q2\ Aquarel QOL-q). This complicates comparing

studiess using different QOL-q's and methods for assessing QOL (transtelephonic,

89 9

selff administered at hospital by researcher /patient). Therefore, it is advisable to

interprett QOL data in pacemaker patients cautiously.15 A The recent developed

Aquarell Qol-q is an accurate QOL-q for study design as our present study, therefore

wee suggest to use this OOL-q in future studies. We could not use this QOL-q for our

studyy because it was not available.

Inn this study we showed an improvement in exercise capacity without improvement

inn QOL. The reverse is shown in cardiac resynchronization therapy studies with

onlyy minor changes in exercise capacity yet major changes in QOL. The PATH-CHF

studyy there was only a minor improvement of 60 meters after cardiac resynchroniza-

tionn therapy while QOL improved clearly.2' These disconnect between exercise

capacityy and QOL can be explained possibly due to several factors. The pacemaker

implantationn has already a large impact and therefore it is more difficult to obtain

moree additional improvement. In this study we compared in hospital tests with

evaluationn of QOL based on the activities at home. As described above the in- hospital

testss are artificial, therefore it would be theoretically and scientifically better when

wee compared the sensor function at home using holter registration with QOL.

Conclusions s

Afterr 1 month of individual optimization of rate response pacemakers, exercise

capacityy and maximum HR was improved, although QOL remained unchanged.

Accessiblee pacemaker sensor algorithms are mandatory for individual optimization,

althoughh automatic features are indisputably important in the pacemaker sensor

development. .

Developmentt of sensor algorithms which create the possibility for monitoring

sensorr behavior in detail at home is a great challenge to overcome the disadvantages

off hospital exercise tests for sensor optimization.

Acknowledgments s

Thee authors thank Wandena Ramsoekh. pacemaker technician for the technical

supportt and Michael Kortz, MD (department of Cardiology, Flevohospital. Almere.

Thee Netherlands) for helping with the inclusion of patients.

Q0 0

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Chapterr 4

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