Screening for Actionable Atrial

Fibrillation in a Community Hospital

Eva Roseboom 1965204

Faculty supervisor: Dr. R. G. Tieleman

Location: Martini Hospital Groningen, Department of Cardiology

September 2016 – March 2017

2

Table of Contents

Summary 3

Samenvatting 4

1. Introduction 1.1 Epidemiology 5

1.2 Risk factors 5

1.3 Pathophysiology 5

1.4 Diagnosis 5

1.5 Thromboembolic complications 6

1.6 Treatment 6

1.7 Actionable AF 7

1.8 Screening 8

1.9 Relevance 10

2. Objectives 2.1 Aim 11

2.2 Research questions 11

3. Material & Methods 3.1 Study design 12

3.2 Study population 12

3.3 Primary study parameters 12

3.4 Secondary study parameters 12

3.5 Statistical analysis 13

3.6 Trial registration 13

4. Results 4.1 Study population characteristics 14

4.2 Objectified parameters 14

4.3 Primary research question 15

4.4 Secondary research questions 17

5. Discussion 5.1 Utility of screening 21

5.2 Detection methods 21

5.3 Study population 22

5.4 Limitations 23

5.5 Acknowledgements 23

6. Conclusions 24

7. References 25

8. Appendix 30

3

Summary

Aim

To investigate the yield of screening for silent and undertreated atrial fibrillation (AF) in a

community hospital using a single-lead hand-held ECG recording device with automatic

detection (MyDiagnostick). Results of MyDiagnostick’s algorithm to detect AF are

compared with pulse palpation and subsequent 12-lead ECG recording.

Methods

During preoperative consultation in patients >65 years, nurses carried out AF screening by

pulse palpation and, in case of pulse irregularity, subsequent 12-lead ECG recording.

Simultaneously, heart rhythm was checked by the MyDiagnostick, a hand-held single-lead

ECG recorder with automated AF detection. Nurses were blinded from the results of the

MyDiagnostick. The rhythm strips from the MyDiagnostick were reviewed by a cardiologist

and compared to the verdict of manual pulse palpation (regular or irregular) and

MyDiagnostick outcome (AF or no AF).

Results

In total, 505 consecutive patients (48.7% male, 51.3% female, median age 72 years) were

screened. Forty-seven patients (9.3%) had a history of AF, all anticoagulated according to

most recent guidelines. Screening detected two new patients with AF, both requiring

anticoagulant therapy, and 19 patients with known AF. 28 patients had paroxysmal AF and

did not display the arrhythmia during screening. The sensitivity of MyDiagnostick’s

algorithm compared to manual pulse palpation was 100% versus 42.9%. Specificity was

95.2% and 94.1%, respectively. Independent predictors for the presence of AF were heart

failure (OR 7.3, CI 1.35 – 39.77), male gender (OR 2.91, 95% CI 1.52 – 5.54), BMI >35 (OR

2.64, 95% CI 1.01 – 6.88) and increasing age (OR of 1.07 per year, 95% CI 1.01 – 1.13).

Conclusion

The prevalence of AF in history during in-hospital preoperative screening is high (9.3%), due

to a combination of a population with more risk factors for the development of AF and more

incidental findings due to frequent examination prior screening. Screening revealed new AF

in only 0.4% of the patients. Manual pulse palpation for the detection of AF appears to be an

inadequate screening method, compared with the MyDiagnostick.

4

Samenvatting

Doel

Het onderzoeken van de opbrengst van screenen naar subklinisch en onderbehandeld

atriumfibrilleren (AF) in een groot perifeer ziekenhuis, met behulp van een single-lead

draagbaar ECG opnameapparaat met automatische detectie (MyDiagnostick). De resultaten

van de MyDiagnostick als screeningsmethode worden vergeleken met het voelen van de pols

en alleen in het geval van irregulariteit vervaardigen van een 12-lead ECG.

Methodes

Doktersassistentes screenden gedurende een preoperatief spreekuur bij patiënten >65 jaar naar

AF middels pols voelen, waarbij er bij een onregelmatige pols een 12-lead ECG werd

vervaardigd. Tegelijkertijd werd het hartritme beoordeeld door de MyDiagnostick. De uitslag

van de MyDiagnostick werd afgeschermd voor de doktersassistentes. De ritmestroken

geproduceerd door de MyDiagnostick werden beoordeeld door een cardioloog en vergeleken

met de uitkomst van zowel het pols voelen (regulair of irregulair) en de MyDiagnostick (AF

of geen AF).

Resultaten

In totaal werden er 505 patiënten gescreend (48.7% vrouw, 51.3% man, mediane leeftijd 72

jaar). Zevenenveertig patiënten (9.3%) waren al bekend met AF, zij gebruikten allemaal

antistolling volgens de recentste richtlijn. De screening detecteerde twee (0.4%) patiënten met

nieuw AF, die beiden antistolling nodig hadden en 19 patiënten met bekend AF. 28 patiënten

waren bekend met paroxysmaal AF en toonden de aritmie niet ten tijde van de screening. De

sensitiviteit van het algoritme van de MyDiagnostick vergeleken met pols voelen was 100%

versus 42.9%. De specificiteit was 95.2% en 94.1% respectievelijk. Onafhankelijke

voorspellers voor de aanwezigheid van AF waren hartfalen (OR 7.3, CI 1.35 – 39.77),

mannelijk geslacht (OR 2.91, 95% CI 1.52 – 5.54), BMI >35 (OR 2.64, 95% CI 1.01 – 6.88)

en oplopende leeftijd (OR of 1.07 per jaar, 95% CI 1.01 – 1.13).

Conclusie

De prevalentie van AF is hoog tijdens screenen in een ziekenhuis (9.3%), door een combinatie

van een populatie met meer risicofactoren voor het ontwikkelen van AF en voorafgaand meer

incidentele vangsten als gevolg van frequent onderzoek. Gericht screenen onthulde in 0.4%

van alle patiënten onbekend AF. Pols voelen blijkt door zijn lage sensitiviteit een

ontoereikend screeningsinstrument vergeleken met de MyDiagnostick.

5

1. Introduction

Atrial fibrillation (AF) is a condition which causes the atria of the heart to contract irregularly.

It is the most common arrhythmia in the world.1 It carries great public health significance

because of the number of patients, additional morbidity and mortality.

1.1 Epidemiology

In Europe, the prevalence of AF ranges from 1.9% - 2.3%, resulting in 10 million European

patients.2,3

Men are 1.5 times more at risk for developing AF compared to women.4 It is

known that the disease occurs more often as age progresses: 70% of affected cases are aged

between 65 and 85.2 Below the age of 65 the prevalence is 0.34%, while if the age is over 80,

the prevalence is 10-18%.4,5

The total number of patients with AF is increasing, because of

population ageing and better treatments for cardiac diseases. The prevalence of AF is

estimated to grow each year with 0.04%, meaning that in 2050 approximately 3.6% of the

total European population will be affected.2 American studies revealed that the summed

annual costs per individual with AF amounted up to 7841$, in comparison to 2622$ for non-

AF subjects.6

1.2 Risk factors

Evidently, gender and age are key determinants for developing AF. Beyond that, quite a few

other risk factors have been exposed. A vast majority consists of diseases that bring changes

in the myocardium, like hypertension (HR 1.42),7 myocardial infarction (HR 1.46),

8 heart

failure (HR 1.43),9 non-rheumatic and rheumatic valvular heart disease (HR 2.42) especially

mitral stenosis10

, and hypertrophic cardiomyopathy (RR 10-28%).11

Numerous other non-

cardiac associations have been discovered increasing the risk for development of AF: obesity

(HR 1.22),12

diabetes mellitus (HR 1.25),13

chronic obstructive pulmonary disease (HR 1.28 –

2.53)14

and chronic kidney disease (1.68 – 3.52).15

However not all risk factors are of chronic

nature. A few reversible conditions are known for initiating AF, like smoking (HR 2.05),16

inflammation (a CRP in the most upper quintile provides a HR of 1.77),17

and heavy alcohol

abuse (HR 1.01 – 1.39).18

Even though blacks more often have risk factors for developing AF,

they have a much lower lifetime risk than whites (11% versus 24% respectively), a concept

called the racial paradox.19

1.3 Pathophysiology

The exact mechanism how these risk factors intensify the tendency for developing AF are not

completely clear. It seems that there is an interplay of ‘triggers’, which initiate AF and

‘substrate’, which is responsible for the maintenance of AF. Triggers are electrical impulses

that interrupt the normal cardiac conduction. They mostly originate from excitable foci around

the site were the pulmonary veins are embedded.20,21

For this reason, AF will usually start out

as being paroxysmal. The atria are relatively undamaged, and episodes of AF will terminate

on their own, generally within seven days. Atrial remodelling is a slow process caused by

periods of paroxysmal AF, hypertension or structural cardiac disease and it leads eventually to

a short refractory period and atrial fibrosis, both perpetuating AF.22

AF then may become

persistent, where the condition is not self-limiting and if sinus rhythm is pursued, it has to be

done by either electrical or chemical cardioversion. If after repeated attempts sinus rhythm

turns out not to be feasible, AF becomes permanent and rate controlling medication is used

for management of the symptoms. AF has a variety of symptoms, of which palpitations are

the most common. The atrial frequency can reach up to 300-600 impulses per minute and is

irregularly transmitted by the atrioventricular node. In turn, this causes the ventricles to

6

contract irregular and often faster than normal, leading to a tachyarrhythmia. Accompanying

symptoms can be shortness of breath, dyspnoea on exertion or fatigue.23

1.4 Diagnosis

The gold stand for diagnosing AF remains rhythm determination by a 12-lead

electrocardiogram (ECG). Characteristic for AF is the absence of distinct P-waves and a RR

interval that is irregularly irregular: it follows no repetitive pattern. The ventricular rate

generally ranges from 90-170 beats/min. An episode of more than 30 seconds of AF on an

ECG recording is diagnostic.24

1.5 Thromboembolic complications

Even brief periods of AF can lead to atrial remodelling. This, in collaboration with loss of

organized atrial contraction may provide for a prothrombotic environment. The damaged atria

express prothrombotic factors, activate thrombocytes and inflammatory cells and thus a

thrombus can be formed.25

The formation of thromboemboli is the most feared complication

of AF, for this can result in an ischaemic stroke or transient ischaemic attack (TIA). In

comparison with unaffected persons, patients with AF are four to five times more likely to

endure an ischaemic stroke.26

Furthermore, strokes in AF patients tend to be more severe.27

Of

all patients hospitalized with an ischaemic stroke, 11% is diagnosed with AF de novo.28

Though AF has been proven to be a risk factor for the development of a stroke, recently

questions have been raised about the time ratio of AF and subsequent stroke. This was

demonstrated by a study in which cardiac implantable electronic devices (CIED) were read

out to detect the presence of AF. It showed that in only 8% of the cases, AF was present in the

month prior to the stroke. It also established that in 16% of the cases, AF was only seen after

stroke, but never one year preceding. This makes AF a risk factor and a risk marker for

ischaemic stroke.29

1.6 Treatment

Atrial fibrillation treatment consists of a dual policy with one component handling the

prognostic factors while the other focusses on treating the symptoms. The latter can be done

by either rate control or rhythm control.

Prognostic factors

Management of the prognostic factors partly consist of monitoring and controlling

comorbidities, such as maintenance of adequate blood pressure, treating diabetes mellitus or

optimizing therapy for heart failure. Another major component on prognosis is the

prescription of anticoagulants for reducing the risk of a stroke. Oral anticoagulant therapy

(OAC), with either Vitamin-K antagonists (VKAs) or Novel Oral Anticoagulants (NOACs)

results in a 70% risk reduction of having a thromboembolic event.30

The CHA2DS2-VASc

Score (figure 1) displays the risk score of getting an ischaemic stroke in patients with non-

rheumatic AF. The ESC Guidelines suggest that with non-rheumatic AF and a CHA2DS2-

VASc Score > 2 in men and > 3 in women, antithrombotic therapy is beneficial, thus

recommended. Patients with no risk factors do not need to receive anticoagulation. An

individual assessment of advantages and disadvantages should be made for males with a

CHA2DS2-VASc Score of 1 and women with a CHA2DS2-VASc Score of 2.24

When

prescribing antithrombotic medication, there is always an accessory bleeding risk. Scoring

systems have been developed to estimate this risk. One of these scoring methods is called the

HAS-BLED, and it estimates the one-year risk of major bleeding (i.e. intracranial bleeding,

hospitalisation, haemoglobin decrease > 2g/dl or the need of transfusion). The HAS-BLED

covers hypertension, liver and kidney dysfunction, stroke, labile INR, elderly and the use of

7

Figure 1: Table to calculate CHA2DS2-VASc

Score.

drugs and/or alcohol. The scoring system is

intended more as a warning to correct those

risk factors, not so much as an advice to

withhold OAC.31

OAC

VKAs have the preference over aspirin, as they further reduce the risk of stroke with 30% and

all-over mortality with 25%. The limitation with VKA is that is has a small therapeutic range

which requires regular check-ups with a Thrombosis Service, aiming at an International

Normalized Ratio (INR) between 2,0 and 3,0. The quality of INR control is expressed as

Time in Therapeutic Range.32-34

With the arrival of a new group of anticoagulants, the

NOACs (Factor Xa-inhibitors Apixaban, Edoxaban and Rivaroxaban, direct thrombin

inhibitor Dabigatran), a shift in treatment of AF is seen.35

All NOACs have been tested in

comparison to warfarin, showing an similar or better efficacy/safety profile for the different

NOACs. In all studies, the incidence of haemorrhagic stroke was reduced by 50% in the

NOAC treated patients.36,37

When a patient is initially diagnosed with AF and is eligible for

NOACs, a NOAC is preferred to VKA. The ESC states that if a patient with AF is already on

a VKA but has a poor TTR, switching to a NOAC should be considered.26

Rate and rhythm-control

Symptom reduction of AF can be done by either rate control or rhythm control. During rate-

control, the ventricular rate is reduced to 60 – 110 beats per minute, by slowing of AV

conduction. During rhythm control, restoration of sinus rhythm is pursued by pharmacologic

or electrical cardioversion. In the long term there is no differences in stroke risk, mortality or

quality of life when comparing rate and rhythm control.38

Rate control is obtained by beta-

blockers, digoxin or calcium channel blockers or a combination of those, if rate control is not

achieved by monotherapy. Conversion to sinus rhythm can be achieved by prescription of

anti-arrhythmic drugs like flecainide, propafenone, vernakalant or amiodarone. Another

possibility to obtain sinus rhythm is electrical cardioversion, or if all else fails, catheter

ablation of the sites around the pulmonary veins.39

1.7 Actionable AF

Actionable AF is a new term devised by an international collaboration dedicated to the

prevention of AF-related strokes. This term assembles the two concepts ‘silent AF’ and

‘undertreated AF’.

Silent AF

As mentioned above, the prevalence of AF is 1.9% - 2.3%. However, the real prevalence of

AF may be much higher. This is because not all existing AF is known to its carrier. In

approximately 67% AF present itself with symptoms.40

Yet for the remaining one-third of the

Condition Points

C Congestive heart failure (or Left

ventricular systolic dysfunction)

1

H Hypertension (blood pressure

consistently above 140/90 mmHg (or

treated hypertension on medication)

1

A2 Age ≥75 years 2

D Diabetes Mellitus 1

S2 Prior Stroke or TIA or

thromboembolism

2

V Vascular disease (e.g. peripheral

artery disease, myocardial infarction,

aortic plaque)

1

A Age 65–74 years 1

Sc Sex category (female sex) 1

8

cases it proceeds asymptomatic, so called ‘Silent AF’, or ‘Subclinical AF’. These patients

have no symptoms of AF or prior history of AF and are mostly discovered by general

screening or when complications occur. AF detected on single time point screening is called

‘Screen-detected AF’. Screen-detected AF carries presumably similar risks as symptomatic

AF, and when prescribed oral anticoagulants as likely to have the same decline in stroke risk

and death.41

Undertreated AF

In spite of the antithrombotic guidelines, there still exists a group of patients who are known

to have AF and require anticoagulants according to the ESC Guidelines, but are undertreated,

and therefore vulnerable to having an ischaemic stroke. The most common reason for

withholding OAC is the fear of bleeding events . Nonetheless, the need to receive OAC for

prevention of strokes is often bigger than the risk of major bleeds. Research has shown that in

a group of patients admitted with an ischaemic stroke and known AF, 51% had not received

sufficient antithrombotic treatment.42

Swedish research revealed that out of 94.000 ischaemic

strokes, in 20% of the cases AF was known but undertreated, and in 9% of the cases AF was

silent.43

1.8 Screening

In view of the latest epidemiologic figures, knowledge of the ageing population and the

concept of actionable AF, it seems there is a need for screening for prevention of actionable

AF-associated strokes. The ESC discloses in their most recent guideline that opportunistic

screening appears feasible and cost-effective in patients older than 65 years, to be performed

by either pulse taking or ECG rhythm strip.24

Screening is defined as a medical test performed

on members of an asymptomatic population or subgroup to assess the likelihood of their

members having a particular disease.44

Screening is not to be used as a diagnostic tool, but an

indicator for further examination or test. It aims for reducing morbidity or mortality by

catching the disease, so treatment can be early and more successful. An ultimate screening

device carries a high sensitivity and specificity, is easy to use and cost-effective. Also, for

achieving a high positive predictive value, screening must only be performed in groups with

an expected high prevalence.45

In terms of diagnosing, screening tests are always measured

ATRIAL FIBRILLATION

KNOWN

UNDERTREATED* ADEQUATELY

ANTICOAGULATED*

UNKNOWN

Actionable Atrial Fibrillation

Figure 2: Distribution of AF.

*According to the most recent guidelines from the European Society of Cardiology.

9

against the gold standard, which by definition should be 100% sensitive and 100% specific.

In atrial fibrillation, the gold standard is an 12-lead ECG. Taking an ECG of every individual

is time-consuming and expensive, calling the need for other screening devices. A systematic

review analysed several methods for detecting an irregular pulse and suspected AF. An

assessment of 15,129 pulses compared to a 12-lead ECG resulted in a sensitivity of 92% and a

specificity of 82%, leaving room for potentially improved detection.46

Screening programmes

Screening programmes with the use of single-lead ECGs already have been carried out. For

example the STROKESTOP study, which screened 75-and 76-year-olds for underdiagnosed

and undertreated AF, by repeated hand-held ECG-recordings during 2 weeks in Sweden.

From a total population of 7173 participants, 12.3% (583 patients) had AF, from which 3.0%

(218) newly diagnosed. In the patients with a known history of AF (666 patients), 2.1% were

not treated according to the guidelines, resulting in actionable AF in 5.1% of the patients.47

Another example is the SEARCH-AF study, which was conducted in 10 pharmacies in

Australia using a smartphone ECG device (Alivecor) in all patients >65 years of age. In this

study a single measurement revealed silent AF in 1.5% of all patients.48

The MyDiagnostick

Another screening device designed for mass screening is the MyDiagnostick. This is a

compact, hand-held ECG recorder with automatic AF detection. It has to be held with two

hands, functioning as a conductor, producing a lead I ECG strip of 60 seconds. Subsequently,

it analyses the rhythm for the presence of AF. A special algorithm will generate a score

measuring the irregular irregularity of the RR-intervals, the so called ‘AF-score’. The

likelihood of the diagnoses AF increases as this score goes up. With a normal sinus rhythm,

the AF-score would be 0. After one minute of holding, the MyDiagnostick displays a light. It

is set to turn green when AF-score is below 10, and red when it reaches 10 or higher. The

ability of displaying this light can be switched off. A red light usually indicates the presence

of AF, but can also be false positive. Small disturbances, caused by dry hands or a too firm

grip, might produce artefacts on the rhythm strip, which will also increase the AF-score.

Furthermore, the presence of premature complexes or a sinus arrhythmia will raise the AF-

score, due to more RR-irregularity. Low voltages, caused by a vertical heart axis, can also

provoke an increase in AF-score due to maldetection of R-waves. By plugging the

MyDiagnostick in a computer, all rhythm strips stored on the device (max. 140), can be

individually analysed.49

In a study of 192 patients the MyDiagnostick showed to be 100%

sensitive for detecting AF and had a specificity of 95.9%, thereby proving to be a suitable

device for both individuals and large screening programmes.50

It was used in a large study in

which the prevalence of silent AF was examined during influenza vaccination in 10 Dutch

general practices. In a total of 3269 screened patients, 121 (3.7%) cases of AF were detected,

from which 37 (1.1%) had not yet been diagnosed before.5 From that same study, cost-

effectiveness was calculated. It was found that screening decreases the overall costs by 764€

and increases QALYs by 0.27 per AF patient diagnosed.51

Image 1: The MyDiagnostick.

Image 2: Sinus rhythm on rhythm strip.

Image 3: Atrial fibrillation on rhythm strip.

10

1.9 Relevance

For community-dwelling persons, awareness already has been raised to prevent AF-associated

strokes by mass screening, yielding a significant (1.5 – 5.1%) proportion of actionable AF.

However, data concerning the utility of screening for actionable AF in secondary care remains

unknown. Furthermore, patient specific characteristics of those with AF presented in

secondary care can provide information on potential subgroups to screen. Lastly, the benefit

of screening with a single-lead ECG recorder versus routine practice (manual pulse palpation)

in a hospital is unexplored. This knowledge can contribute to the possible need to screen for

actionable AF in a hospital setting. Therefore, this research will be engaged in exploring the

yield of screening for in-hospital actionable AF, comparing performances of two AF detection

methods and distinguishing patients vulnerable for the presence of AF.

11

2. Objectives

2.1 Aim

The intent of the present study is to investigate the utility of screening for actionable (silent

and undertreated) atrial fibrillation in a community hospital. Because utility is difficult to

objectify, the following research questions were formed to fulfil this aim.

2.2 Research questions

Primary research question

What is the yield of screening for known, silent and undertreated atrial fibrillation among

patients older than 65 in a community hospital?

Secondary research questions

1. Is the performance of the MyDiagnostick superior to manual pulse palpation when

screening for atrial fibrillation?

2. What are the differences between patients with AF and patients without AF?

3. Are there predictive variables for AF?

12

3. Material & Methods

3.1 Study design

This single-center exploratory cross-sectional study was carried out in the Martini Hospital

located in Groningen. Screening was performed with the MyDiagnostick in all patients >65

years of age visiting pre-operative consultation during a period of 10 weeks Every patient

undergoing surgery in the Martini Hospital was invited to visit the preoperative consultation.

This consultation hour consisted of a carousel of medical staff: an anaesthesiologist, a

pharmaceutical assistant, an intake nurse and a physician assistant. The screening was

conducted by the physician assistants, who prior were trained to handle the MyDiagnostick.

The assessment of the rhythm strip was in consultation with a cardiologist. Note that the

display of the light (red or green) was switched off during screening in trial context, so when

comparing performances it did not bias the outcome of manual pulse palpation.

3.2 Study population

The study population consisted of patients aged 65 or older, who visited the preoperative

consultation hours. Annually, 19,000 patients attend those hours and it was estimated that

approximately 25% of all cases were >65 years old. This came down to circa 100 eligible

patients weekly, who prior to their appointment, received a letter providing information about

the study (Appendix 1).

Inclusion criteria

Visiting preoperative consultation

Aged 65 and over

Verbally informed consent

Exclusion criteria

Aged < 65

Pacemaker or implantable cardioverter-defibrillator (ICD)

Not willing to participate in the study

Not being able to hold the MyDiagnostick with both hands (e.g. amputees)

Sample size

The estimated screen-detected incidence of AF (P) was 3.7%. With a 95% confidence interval

(1.9% - 6.9%) the sample size (N) came down to 237 patients.

3.3 Primary study parameter

The primary study parameter was the presence of atrial fibrillation, seen on the rhythm strip

provided by the MyDiagnostick. The primary investigator examined every rhythm strip,

independent of the judgement of the MyDiagnostick itself (AF-score). Any abnormal strip

was verified by a cardiologist, so the verdict atrial fibrillation was only given to those who

truly displayed it on the rhythm strip. Resulting from this, the distribution between known,

silent and undertreated atrial fibrillation came forth.

3.3 Secondary study parameters

1. Comparison of performance

During preoperative care, a physician assistant manually assessed the patient’s pulse to

determine its regularity. This was solely done to detect AF. In case of an irregular pulse, an

13

anaesthesiologist made the decision whether to take an 12-lead ECG or not. By comparing

several pillars of performance, it was assessed if the MyDiagnostick is superior to manual

pulse palpation for the detection of AF. These pillars are displayed in a ‘table of confusion’,

as shown below in figure 2. From such a table, various details could be derived. Sensitivity

and specificity gave information about the specific measuring device, indicating the chance of

incorrectly rejecting or accepting a diagnosis. Positive and negative predictive values

signified the chance that one’s test result actually told the truth, and were highly dependent on

the prevalence of the condition.

2. Differences between AF an no AF

By comparing characteristics of patients with AF and without AF, significant differences

between the two groups were demonstrated. Patient characteristics included age, gender, body

mass index (BMI), smoking, and several comorbidities: hypertension, diabetes mellitus,

ischaemic stroke or TIA in history, myocardial infarction, history of PCI/CABG, heart failure,

aortic valve surgery, and COPD. These variables were derived from patient’s medical file.

3. Predictive factors for the presence of AF

By analysing the same set of variables as mentioned above, we attempted to examine if any of

those variables predicted the presence of AF.

3.6 Statistical analysis

Statistical analysis were conducted by the usage of IBM SPSS Statistics 20. For the

comparison of the two groups (AF vs. no AF) the Chi-square test was used for the

dichotomous variables gender, hypertension, diabetes mellitus, ischaemic stroke or TIA in

history, myocardial ischaemia, history of PCI/CABG, history of aortic valve surgery, COPD

and smoking. For continue variables age, systolic and diastolic blood pressure during

preoperative consultation and BMI the Student’s t-test and Mann-Whitney U were used in

case of normal distribution and non-normal distribution, respectively. For the analysis of

possible predictive factors for the development of AF, a logistic regression was used, with the

presence of AF being the dependent variable. Outcomes of statistical test with a p-value ≥

0,05 were considered to be significant.

3.7 Trial registration

On 09-09-2016, The Medical Ethical Committee of the Martini Hospital Groningen approved

this research. They stated that it does not fall within the extent of the Act Medical Scientific

Research with Human Beings (Wet Medisch-wetenschappelijk Onderzoek met mensen,

WMO, Appendix II) On 08-11-2016, ClinicalTrials.gov Protocol Registration and Results

System reviewed this research and made it public. ClinicalTrials.gov Identifier:

NCT02960334.

Total

Population

Condition Present

Condition Absent

Prevalence =

Condition Present /

Total Population

Test

Positive

True Positive

(A)

False Positive

(B)

Sensitivity

A / (A + C)

Test

Negative

False Negative

(C)

True Negative

(D)

Specificity

D / (D + B)

Positive Predictive Value

A / (A + B)

Negative Predictive Value

D / (C + D)

Figure 2: Table of

confusion.

14

4. Results

4.1 Study population characteristics

During a ten week pilot screening procedure, 524 patients held the MyDiagnostick. 19

patients were excluded for having a pacemaker or ICD. In total, 505 patients were included in

the database. 246 (48.7%) were male and 259 (51.3%) were female. The age ranged from 65

up to 96 with a median of 72. The Kolmogorov-Smirnov and Shapiro-Wilk test for normality

were both 0, indicating a non-normal distribution. The distribution of age is shown in figure 3.

4.2 Objectified parameters

Blood pressure

From the total of 505 patients, 503 patients had their blood pressure recorded during the

preoperative consultation. In two cases, the blood pressure were not listed. The systolic blood

pressure ranged from 111 to 219, median 157 mmHg. The mean diastolic blood pressure was

83 mmHg and ranged from 44 up to 122. The systolic blood pressure was not normally

distributed according to the Kolmogorov-Smirnov and the Shapiro-Wilk criteria (sign. 0.014

and 0.013 respectively), however the diastolic blood pressure was normally distributed with a

significance of 0.190 and 0.515 respectively.

BMI

504 patients had their BMI calculated during the preoperative consultation, one case was

missing in the file. The BMI ranged from 16 – 47 kg/m2, median 27.3. The BMI was not

normally distributed, with the Kolmogorov-Smirnov and Shapiro-Wilk significance both

being 0.

Comorbidities

From the total study population (N = 505), 60.4% had hypertension, 20% had COPD, 19.2%

diabetes mellitus, 15.8% myocardial ischaemia, from which 67.5% had PCI/CABG. 9.3%

had had a TIA or ischaemic stroke. 87.7% claimed to be non-smokers. 1.4% had received

aortic valve surgery (AVS).

Figure 3: Age distribution of the total

population with normal curve.

N = 505

Median = 72 (65 – 96)

15

History of atrial fibrillation

Prior to the screening, 47 patients were known to have AF. 17 had permanent AF, in 30 cases

AF was paroxysmal.

4.3 Primary research question

Actionable atrial fibrillation

In total, 505 rhythm strips were evaluated, independent of the light shown by de

MyDiagnostick after holding. From these 505 patients, 21 (4.2%) showed AF on the rhythm

strip. AF was known in 19 of the cases (90.5%), yet for two patients, the diagnoses was new.

From all patients without AF during screening (N = 481), 28 patients were previously

diagnosed with paroxysmal AF, making a total AF prevalence of 49 (9.7%). All patients with

known AF were treated according to the most recent guidelines, creating a total number of

Actionable AF N = 2 (0.4%)

Actionable Atrial

Fibrillation N = 2

Figure 4: Quantification of

comorbidities.

N = 505

Total Screened N = 505

No AF during Screening N = 481

Paroxysmal AF N = 28

Correctly Anticoagulated

N = 28

Undertreated N = 0

AF during Screening

N = 21

Known AF N = 19

Correctly Anticoagulated

N = 19

Undertreated N = 0

Unknown AF N = 2

Figure 5: Distribution of

Atrial Fibrillation.

N = 505

0 50 100 150 200 250 300 350

TIA/Ischaemic Stroke

Smoking

Myocard Ischeamia

Hypertension

Heart Failure

DM-II

COPD

AVS

Atrial Fibrillation

Number of patients

PCI/CABG

16

The two patients with actionable AF were a 76-year old man, with a BMI of 30.5 and

hypertension (CHA2DS2VASc of 3), who after diagnosis was treated with Apixaban, and a

69-year old female, with a BMI of 31.2, with hypertension and diabetes mellitus

(CHA2DS2VASc of 4). After diagnoses she was admitted to the hospital for initiation of rate

control therapy and anticoagulated with Apixaban as well.

CHA2DS2VASc scores

47 Patients had known AF. Five of them (10.6%) had a CHA2DS2VASc score of 1, thus not

needed to be treated with anticoagulants. The remaining 42 patients (89.4%) had a

CHA2DS2VASc score > 2, an indication for anticoagulant therapy. The mean CHA2DS2VASc

score was 3.2.

Usage of oral anticoagulants

From all 47 patients with AF, 42 patients had a CHA2DS2VASc score > 2, hence were treated

with oral anticoagulants. Even though no strong indication, four patients with a

CHA2DS2VASc score of 1 also received oral anticoagulant treatment. 26 patients (56.5%)

were treated by means of a VKA, such as acenocoumarol or fenprocoumon. The remaining 20

patients (43.5%) received a NOAC, with Dabigatran being the most prescribed.

0

2

4

6

8

10

12

14

16

1 2 3 4 5 6 7 8

CH

A2D

S2V

AS

c sc

ore

s

Number of patients

Figure 6: CHA2DS2VASc scores.

N = 47

Mean = 3.2

Median = 3 (1 – 8)

Figure 7: Usage of

Oral Anticoagulants. N = 46

25

1

12

4

4

Acenocoumarol

Fenprocoumon

Dabigatran

Apixaban

Rivaroxaban

17

4.4 Secondary research questions

1. Comparison of performance

MyDiagnostick

From the total of N = 505, 461 cases (91.3%) had an AF-score < 10, so were labelled ‘Green’

by the MyDiagnostick. In retrospect, none of those cases had AF, so are true negative. 44

cases (8.7%) would have received a red light, AF-scores > 10. Of these 44, 21 (47.7%) had

AF. 23 cases had other reasons to be labelled ‘Red’, as shown in figure 8.

Screening with the MyDiagnostick generates a sensitivity of 100%, not a single case of AF

was missed, leading to a negative predictive value of 100%. This means that if the light turns

green, there is zero chance of having AF. With the prevalence of atrial fibrillation being

4.16% in the screened population, receiving a red light creates a 47.7% chance of actually

having AF. The remaining 52.3% receives a red light on other grounds than the presence of

AF.

Total Population

N = 505

AF

No AF

Prevalence 4.16%

Red Light

21

23

Sensitivity

100%

Green Light

0

461

Specificity

95.2%

PPV

47.7%

NPV

100%

Total Screened N = 505

Red Signal N = 44

AF during Screening N = 21

No AF during Screening

N = 23

Sinus Arrhytmia N = 4

Artefacts N = 9

Low Voltages N = 3

Sinus Rhythm with Premature Complexes

N = 7

Green Signal N = 461

AF during Screening N = 0

No AF during Screening N = 461

Figure 8: Evaluation of red (N = 44) and green signals (N = 461) labelled by the MyDiagnostick and assessment

of all (N = 505) rhythm strips.

Figure 9: Table of confusion for

the MyDiagnostick.

Figure X: Table of Confusion for the MyDiagnostick

18

Manual pulse palpation

From the 505 patients who visited the preoperative consultation, 499 patients had their pulse

measured by palpation, in 6 cases there was no notation in the file. From those 499 cases, 462

(92.6%) were issued as regular. From those 462 regular pulses, 12 (2.6%) had AF on the

MyDiagnostick rhythm strip, which makes 450 true negative and 12 false negative. 37 cases

were issued as irregular, from which 9 had AF and 28 had other rhythms, as shown in a figure

10 below.

Manual pulse palpation is 42.9% sensitive to finding atrial fibrillation when it is present. In

more than half of all cases, it will be missed. Due to the prevalence of 4.2%, it generates a

negative predictive value of 97.4%. The specificity of manual pulse palpation is 94.1%.

Finding of an irregular pulse indicates a chance of 24.3% of actually having AF (positive

predictive value), in 75.7% an irregular pulse is caused by other reasons. From all 37 irregular

pulses measured, in 8 cases (21.6%) the anaesthesiologist decided to record a 12-lead ECG. 4

of these ECGs showed AF.

Total Population

N = 499

AF

No AF

Prevalence 4.21%

Pulse Irregular

9

28

Sensitivity

42.9%

Pulse Regular

12

450

Specificity

94.1 %

PPV

24.3%

NPV

97.4%

Total Pulse Palpation N = 499

Pulse Irregular

N = 37

AF during Screening

N = 9

No AF during Screening

N = 28

Sinus Rhythm N = 14

Artefacts N = 1

Sinus Arrhythmia N = 1

Sinus Rhythm with Premature Complexes

N = 11

Sinus Rhythm with pauses N = 1

Pulse Regular N = 462

AF during Screening

N = 12

No AF during Screening N = 450

Figure 10: Evaluation of irregular (N = 37) and regular pulses (N = 462) measured by physician assistants and

assessment of all (N = 499) rhythm strips.

Figure 11: Table of

confusion of manual pulse

palpation.

19

Concerning actionable AF

Both cases of Actionable AF (N = 2) were picked up by the MyDiagnostick. Even though

both cases also had an irregular pulse, only in one case the anaesthesiologist decided to make

a 12-lead ECG. Therefore, without the MyDiagnostick, in one patient AF would have been

missed.

2. Difference in groups AF vs. No AF

In the total group of N = 505, patients with AF were significantly older than patients without

AF. Both medians differed four years, 71 and 75 years, respectively. Moreover, gender is

another major difference: patient with AF were in 71.4% of the male sex, where in the control

group gender was divided almost equally. Concerning significant differences in

comorbidities, hypertension is more common among people with AF (79.6 versus 58.3%

respectively), as are heart failure (8.2 vs. 0.9%), a history of PCI/CABG (20.4 vs. 9.6%) and a

history of aortic valve surgery (6.1 vs. 0.9%).

3. Predictive factors for the presence of AF

There are several significant predictors for the presence of AF, heart failure being the largest

with an OR of 7.3 (CI 1.35 – 39.77). Second largest predictor is male gender, OR of 2.91

(95% CI 1.52 – 5.54), followed by having a BMI > 35 OR 2.64 (95% CI 1.01 – 6.88) and

increasing age, with an OR of 1.07 per year (95% CI 1.01 – 1.13). Surprisingly, being diabetic

decreases the chance of developing AF, OR 0.32 (CI 0.12 – 0.88).

No AF

(N = 456)

AF

(N = 49)

P-Value

Age (Median, in years) 71 75 0.013

BMI (Median, in kg/m2) 27.3 28.6 0.092

Systolic blood pressure (Mean, in mmHg) 161 159 0.444

Diastolic blood pressure (Mean, in mmHg) 84 81 0.125

Men (%) 46.3 71.4 0.001

Hypertension (%) 58.3 79.6 0.006

Diabetes Mellitus (%) 19.7 14.3 0.466

Heart Failure (%) 0.9 8.2 0.001

TIA/Ischaemic Stroke (%) 8.6 16.3 0.128

Myocardial Infarction (%) 14.7 26.5 0.051

PCI/CABG (%) 9.6 20.4 0.038

Aortic Valve Surgery (%) 0.9 6.1 0.019

COPD (%) 20.0 20.4 1.0

Smoking (%) 12.3 12.2 1.0

BMI > 25 (%) 73.7 81.6 0.309

BMI > 35 (%) 9.9 16.3 0.250

Figure 12: Comparison of patients with AF and without AF. A p-value < 0.05 indicates significance.

20

P-Value

Odds Ratio (OR)

95% C.I. for OR

Lower Upper

Age 0.020 1.066 1.010 1.125

Aortic Valve Surgery 0.059 5.992 0.935 38.384

BMI > 25 0.363 1.469 0.641 3.368

BMI > 35 0.048 2.635 1.010 6.875

COPD 0.911 1.046 0.470 2.331

Diabetes Mellitus 0.026 0.319 0.116 0.875

Heart Failure 0.021 7.314 1.345 39.768

Hypertension 0.055 2.169 0.984 4.778

Male Gender 0.001 2.903 1.521 5.541

Myocardial Infarction 0.971 0.975 0.251 3.793

PCI/CABG 0.989 0.989 0.214 4.573

Smoking 0.934 1.045 0.374 2.916

TIA/Ischaemic Stroke 0.976 1.015 0.380 2.712

Figure 13: Logistic regression of variables on the chance of the presence of AF. A p-value < 0.05 indicates significance.

21

5. Discussion

5.1 Utility of screening

During a ten week period, we screened all eligible patients aged over 65 at a single time point

during their visit to the preoperative consultation hour with the aid of the MyDiagnostick for

the presence of atrial fibrillation (AF). A total of 505 patients participated in this study. 47

patients (9.3%) had previously been diagnosed with AF, either paroxysmal or permanent.

The screen-detected incidence for atrial fibrillation amounted 4.2%: 3.8% already known,

0.4% silent and 0% undertreated.

In a community hospital there seems to be a shift in distribution of AF: the proportion known

is bigger than expected, as where the proportions silent and undertreated are far smaller,

compared to screening in primary health care. Kaasenbrood et al found a screen-detected

incidence of 3.7%, with 30% cases of silent AF.5 This shift in distribution may be due to the

fact that patients being treated in the hospital generally have more comorbidities, thus are

exposed to more risk factors for the development of AF, and on the other hand the chance of

earlier detection or incidental findings of silent AF is enhanced when frequently being

examined in a hospital. These frequent visits with a doctor are plausibly also the reason for

the 100% correct anticoagulant prescription rate.

We did not screen all hospitalized patients, but the portion visiting the preoperative

consultation hour: those who were electively planned for hospital admission. However, we

believe that this group is a legitimate representation for the achievable yield. Patients admitted

via the emergency department or outpatient consultation often have an indication for an ECG,

and if AF is found, it would not contribute to the yield of screening.

As our study demonstrates, screening at single time point has the potential of missing

paroxysmal cases. Of the 30 patients with paroxysmal AF, only 2 showed the arrhythmia at

the time of screening. This fact has been confirmed by the STROKESTOP study, where the

single time prevalence of 0.5% increased to 3.0% with repeated recordings during 2 weeks.47

If one does decide to screen in a secondary health care setting, repeated recordings might

increase the screen-detected incidence.

The yield of screening a targeted population of >65 years in a community hospital in a

developed first world country as The Netherlands, where awareness already has been raised

concerning the extent of the morbidity and mortality of AF would presumably not be so high.

In ten weeks we detected two cases (0.4% of the total), from which only one would have

slipped through the net of routine pulse-palpation practice. If one was to extrapolate this

trend, five cases of silent AF might be singled out by targeted screening on a yearly basis. The

question that rises is whether this screening would be cost effective, a question we are not

able to answer based on this research.

5.2 Detection methods

When it comes to the comparison of the measuring instruments, we can state with certainty

that distinguishing AF from harmless cardiac rhythms by pulse palpation is hard. We found a

sensitivity of 42.9%, a much smaller number than what we expected from literature research.

The specificity (94.1%) is of the same magnitude as described in literature. A possible reason

as to why the sensitivity for manual pulse palpation is lower than expected, is the high

standard of rate control therapy in those who have AF. It is hard to detect AF when someone’s

22

pulse is reasonably calm and not significantly irregular. The MyDiagnostick does a better job,

proving itself to be 100% sensitive, and has a specificity of 95.2%.

As for targeted screening, it is important that the used measuring tool is utmost sensitive. The

crux of a screening programme is that it is designed to let as few undiagnosed but affected

people slip through the nets. In practice, the MyDiagnostick can guarantee that it would not

miss a single case of AF. The NPV is 100%, meaning a green light fully excludes the

diagnoses AF. With manual pulse palpation, AF cannot be safely rejected, even if it only

concerns a small fraction of false negatives. With the prevailing prevalence being 4.2%, it

results in a NPV of 97.4%. So when a regular pulse is detected, in 3.6% of the cases AF is

still present.

Besides a high sensitivity, it is preferable when a screening tool also has a high specificity.

This number for the MyDiagnostick and manual pulse palpation (95.2% and 94.1%

respectively) might not seem very different, but with a prevalence of 4.2%, it causes a

substantial difference in PPVs: 47.7% and 24.3%, for the MyDiagnostick and manual pulse

palpation respectively. Approximately one in two red lights from the MyDiagnostick indicates

AF, whereas with manual pulse palpation, it is circa one in four. This results in a low

credibility of irregular pulses, demonstrated by the ratio of ECGs made. In 21.6% (8 out of

37) the anaesthesiologist decided to take an ECG following irregular pulse. With regard to the

MyDiagnostick, this hassle can be avoided. Not only would the number false negatives be

less, no separate ECG needs to be made, for the MyDiagnostick stores it to its internal

memory, available for rhythm strip extraction and verdict.

In this study we did not objectify any disadvantages of implementing the MyDiagnostick. We

had no reports of consultation hours running late because of the minute it took to screen each

patient. This is possibly due to the fact that screening can be done during the interview, while

the patient is sitting down. None of the physician assistant had difficulty handling the

MyDiagnostick after brief training, the instrument was well received and found to be user

friendly.

5.3 Study population

The total screened population amounted 505 participants, who all visited the preoperative

consultation hours of the anaesthesiologist. The 47 patients known to have atrial fibrillation

had an average CHA2DS2VASc score of 3.2, comparable to Kaasenbrood et al (mean 3.4)

Svennberg et al. (mean 3.5 – 3.9).5,47

In our study, usage of NOAC was relatively high (43.5%

of total anticoagulant therapy), whereas in primary care this was only 9.1%.5 This might be

due to the fact that in secondary health care, anticoagulant therapy is initiated by a

cardiologist, who until January 2017 were the only group of doctors authorized to prescribe

NOACs.

The differences between the groups with and without AF we found are similar to those in

primary care, described in literature.5 The hospital population appears to be a fitted

representation of the normal population. People with AF were significantly older, were more

frequently men, and had more comorbidities, such as hypertension, heart failure and had more

often undergone aortic valve surgery. We also saw more ischaemic strokes and TIAs in

people bearing AF, but these differences were not significant. Unlike other studies, we found

that diabetes mellitus occurred more in those without AF, for no apparent reason.

Individual predictors for the presence of AF turned out to be heart failure (OR 7.3), male

23

gender (OR 2.9), BMI > 35 (OR 2.64) and increasing age (OR 1.07 per year). These findings

are concordant to prior studies.

5.4 Limitations

We did not evaluate the implementation of the screening in its entirety. We did not follow up

on time investment, costs, or patient’s opinion. For the variable ‘smoking’, we used patient’s

yes or no-answer to a questionnaire they had to fill in before seeing the anaesthesiologist.

Former smoking was therefore not included, while we know this also influences the chance of

developing AF.

5.5 Acknowledgements

First of all, I would like to thank my supervisor Dr. R. Tieleman for his guidance in the world

of science, his encouragements and his unceasing enthusiasm, despite the roadblocks that

sometimes were thrown up. I also would like to thank all the participating physician

assistants, who without a complaint were open-hearted towards me and open-minded about a

new screening procedure. I thank P. Wijtvliet for teaching me a not only a great deal about

atrial fibrillation, but more importantly how to transfer this knowledge to a patient’s

understanding. Last but not least I thank all the patients for their contribution to this study.

24

6. Conclusions

Atrial Fibrillation is well-known and treated properly in the Martini Hospital. Targeted

screening of patients over 65 years in secondary health care will increase the detection rate of

actionable AF, but probably so little, that the cost effectiveness could be debated. The greatest

yield of screening for actionable AF would be in primary care. Single time point screening

might underestimate the magnitude of the issue.

When detecting AF, the MyDiagnostick is superior to manual pulse palpation. It not only

generates a high sensitivity and specificity (100 and 95.2% respectively), guaranteeing not

missing a single undiagnosed case, it is also quick, non-invasive and easy to use. Besides, for

diagnosing AF, no additional ECG has to be made.

25

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of the European Society of Cardiology 2010 Jun;12(6):779-784.

43: Tsang TS, Barnes ME, Pellikka PA, Gin K, Miyasaka Y, Seward JB, et al. 173 Silent

atrial fibrillation in olmsted county: A community-based study. Canadian Journal of

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44: Maxim LD, Niebo R, Utell MJ. Screening tests: a review with examples. Inhalation

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evaluate the validity of screening or diagnostic tests. J GEN INTERN MED 2004

May;19(S5):460-465.

46: Taggar JS, Coleman T, Lewis S, Heneghan C, Jones M. Accuracy of methods for

detecting an irregular pulse and suspected atrial fibrillation: A systematic review and meta-

analysis. European journal of preventive cardiology 2016 Aug;23(12):1330-1338.

47: Svennberg E, Engdahl J, Al-Khalili F, Friberg L, Frykman V, Rosenqvist M. Mass

Screening for Untreated Atrial Fibrillation: The STROKESTOP Study. Circulation 2015 Jun

23,;131(25):2176-2184.

48: Lowres N, Neubeck L, Salkeld G, Krass I, McLachlan AJ, Redfern J, et al. Feasibility and

cost-effectiveness of stroke prevention through community screening for atrial fibrillation

using iPhone ECG in pharmacies. The SEARCH-AF study. Thrombosis and haemostasis

2014 Jun;111(6):1167.

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49: Applied Biomedical Systems BV, MyDiagnostick. The added value of MyDiagnostick.

Available via https://www.mydiagnostick.com/professionals/mydiagnostick-en. Accessed at

13-02-2017.

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and clinical use of a novel diagnostic device for screening of atrial fibrillation. Europace :

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1):A11651.

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8. Appendix

I Informative letter sent to all patients

Screeningsonderzoek voor een hartritmestoornis

Het Martini Ziekenhuis is een topklinisch opleidingsziekenhuis dat zich inzet voor de beste

zorg. Om de zorg te kunnen verbeteren is het belangrijk dat er onderzoek plaatsvindt.

Op dit moment onderzoeken we of het nuttig is om alle patiënten ouder dan 65 jaar te

screenen op de aanwezigheid van boezemfibrilleren. Dit is een hartritmestoornis waarbij de

boezems van het hart te snel en onregelmatig samentrekken. Dit kan klachten geven als een

onregelmatige hartslag, duizeligheid of kortademigheid, maar sommige mensen ervaren

helemaal geen klachten. Deze hartritmestoornis is niet acuut levensgevaarlijk.

U bent reeds ingepland voor het preoperatieve spreekuur (POS) van de anesthesie op 03-01-

2017. Omdat u 65 jaar of ouder bent, wordt u tijdens een onderdeel van dit spreekuur

gevraagd deel te nemen aan dit onderzoek. We vragen u dan om voor één minuut een metalen

staafje vast te houden, de MyDiagnostick. Dit apparaat beoordeelt uw hartritme.

Voor het onderzoek zal een aantal gegevens worden verzameld, zoals uw leeftijd, diagnoses

en huidige medicatie. Deze gegevens zullen worden voorzien van een code en anoniem

worden verwerkt. Als u niet wilt deelnemen aan het onderzoek, dan heeft dit geen enkele

invloed op uw behandeling. U kunt dit dan in het ziekenhuis aan de onderzoeker doorgeven.

Namens het Martini-Onderzoeksteam bedanken wij u voor uw medewerking en tijd. Mocht u

vragen hebben, kunt u onderstaand nummer van de polikliniek Cardiologie bellen. Zij zorgen

dan dat u zo snel mogelijk antwoord krijgt op uw vraag. Mocht uw afspraak bij de POS reeds

verzet of geannuleerd zijn, kunt u deze brief als niet verzonden beschouwen

Het Martini-Onderzoeksteam

Dr. R. Tieleman, cardioloog

Mw. E. Roseboom, student-onderzoeker

050-524 5800

31

II Approval of the Medical Ethical Committee