University of Groningen

The young athlete's heartBessem, Bram

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CHAPTER 4

GENDER DIFFERENCES IN THE

ELECTROCARDIOGRAM SCREENING OF

ATHLETES

Bram Bessem, Matthijs C. de Bruijn and Wybe Nieuwland

J Sci Med Sport. 2017 Feb;20(2):213-217

78 C H A P T E R 4

ABSTRACT

Objectives: Gender-related differences are frequently used in medicine. Electrocardiograms are also

subject to such differences. This study evaluated gender differences in ECG parameters of young

athletes, discussing the possible implications of these differences for ECG criteria used in the

cardiovascular screening of young athletes.

Design: Observational cross-sectional study.

Methods: In 2013 and 2014 all the ECGs from the cardiovascular screenings performed at University

Sports Medical Centre in Groningen of the student athletes who wanted to participate in a college

sports program were collected. The ECG characteristics were scored using computer-based

measurements and the Seattle ECG criteria.

Results: The study population included 1436 athletes, of which 72% were male. Male athletes were

older (19.3yrs vs. 18.6yrs), participated in sports more frequently (4.0/wk vs. 3.8/wk) and spent more

hours per week practising sports (6.4hrs/wk vs. 5.8hrs/wk) than female athletes. Male athletes had

significantly higher PR intervals (149ms vs. 141ms), lead voltages and QRS duration (98ms vs. 88ms).

Female athletes had significantly higher resting heart rates (69/min vs. 64/min) and QTc intervals

(407ms vs. 400ms). Male athletes also had significantly higher amounts of sinus bradycardia (38.3%

vs. 23.0%), incomplete RBBB (15.0% vs. 3.7%), early repolarisation (4.5% vs. 1.0%) and isolated QRS

voltage criteria for LVH (26.3% vs. 4.6%). All P-values were ≤0.001.

Conclusions: ECGs of young athletes demonstrate gender-related differences. These differences

could be considered in their cardiovascular screening. For the Seattle ECG criteria we advise

additional research into the clinical implications of using gender-based cut-off values for the QRS

duration in the intraventricular conduction delay criterion.

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INTRODUCTION

Males and females are very different, to the degree that different gender-related standards are

frequently used for medical reference ranges. For example, when assessing whether anaemia is

present we use different gender-based normal range values to analyse blood haemoglobin and

haematocrit. Electrocardiograms (ECG) are also subject to gender-related differences. For example,

we use different gender-based cut-off values for the corrected QT (QTc) interval. These gender-

related differences were studied in large populations of non-athletic healthy individuals. Both Mason

(n=80,000) and Ramirez (n=30,000) observed significant differences in heart rate, QRS-axis, QRS

duration, QTc interval and PR interval between men and women.1,2 These differences have only been

evaluated in athletes by Wasfy et al. in a cohort of 330 competitive rowers (56% male).3 They too

found a significant gender-based difference in QRS duration, QTc interval, QRS axis and QRS voltages

in selected leads. These differences might be very relevant because screening of heart disease in

young athletes is importantly based on ECGs.

For this reason, we evaluated pre-participation screening ECGs for gender-related

differences in a population of young student athletes. Differences were evaluated on their possible

implications for screening.

METHODS

In the Dutch city of Groningen, student athletes who want to join a college sports program are

required to obtain medical clearance beforehand. A college sports program is a four-year college

educational program to become a professional in sports education and/or health management (for

example: fitness coach, physical exercise teacher or manager of sports/health events). Such college

educational programs incorporate an average of 10 hours/week of different sporting activities. Since

2013 almost all of these pre-participation medical screenings are performed at University Sports

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Medical Centre in Groningen (USMC). The goal of the pre-participation screening is to filter out those

student athletes who are at a high risk of injury or of not being able to successfully finish the program

due to a physical problem.

The pre-participation screening focuses on two pillars. The first pillar is cardiovascular risk

assessment, performed according to the Lausanne protocol which includes an ECG.4 The second pillar

focuses on the physical status of the student athlete to detect presence or high risk of becoming

injured and/or developing an illness, through intake and examination by a sports physician. The

population of student athletes participating in the program consists of a heterogeneous group of

mainly healthy competitive athletes of Western European ethnicity. In 2013 and 2014 all the data

from the candidates’ pre-participation screening conducted at USMC were collected. An independent

review board statement was provided.

At the visit to USMC a standard 12-lead resting ECG was collected and scored by a sports

physician (Wech Allyn CardioPerfect software V.1.6.4). All ECGs were re-scored by the principal

investigator using the Seattle criteria provided by Drezner et al. (2013).5,6 ECG changes were

categorised as group 1 (training-related) or group 2 (training-unrelated) according to the criteria

described by Drezner et al.6 All ECG characteristics were scored using computer-based

measurements, which were checked visually by the principal investigator. When the measurement

did not fit the visual check, the parameter was calculated manually. The height of R and S peaks in

V1, V2, V5/V6 and extremity leads (lead with the highest peak in mm) was scored manually (in mm).

Other variables collected included age, height, weight, BMI, gender, sports participation (hr/week),

sports frequency (times/week) and sports type.

At USMC the Seattle ECG criteria are used to determine if an athlete’s ECG is normal or

abnormal, and whether the athlete needs to be referred for additional testing.6 When abnormalities

are found, the athletes are referred to a sports cardiologist. Depending on the abnormality and the

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opinion of the cardiologist, additional tests are performed which include echocardiogram, exercise

testing, SA-ECG, 24hr-ECG and MRI.

All student athletes who were referred for additional cardiovascular testing were followed

up. The conclusion of the cardiologist as to whether a cardiovascular pathology was present, was

collected. Athletes were excluded when the ECG quality was too low or when the ECG was missing.

Only the first medical screening was used of those student athletes who had had a screening in both

years.

The statistical analysis was performed using IBM SPSS Statistics V.22.0. To analyse gender

differences in the ECG characteristics, depending on the variable we used the independent T-test and

the chi-square test. Continues variables are presented as mean ± SD.

RESULTS

A total of 1466 screenings were collected in the years 2013 and 2014. Twenty-two of them were

doubles and 8 had an insufficient or absent ECG, and were therefore excluded. The total study

population consisted of 1436 screenings.

The study population included 72% male athletes, who were significantly older, taller and

heavier than the female athletes. The male athletes participated in sports slightly more frequently

and spent on average 36 more minutes per week practicing sports than their female counterparts.

This difference was not significant. The male athletes participated mostly in soccer, the female

athletes mostly in running (see Table 1).

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Table 1. Population demographics

Male Female P-value Numbers Percentage Numbers Percentage

Sex (M / F) 1027 72% 409 28%

Mean (SD) Range Mean (SD) Range Indp. T-

test Age 19.3 (2.4) 15.3 – 30.9 18.6 (2.1) 15.5 – 25.7 P=0.000

Height (cm) 1.82 (0.07) 1.60 – 2.07 1.70 (0.06) 1.50 – 1.85 P=0.000

Weight (kg) 73.5 (9.8) 47.0 – 118.0 63.2 (8.2) 45.0 – 89.0 P=0.000

BMI 22.1 (2.5) 15.3 – 33.8 21.8 (2.4) 15.9 – 31.0 NS*

Sport frequency

(times/week)

4.0 (1.5) 0 – 7 3.8 (1.7) 0 – 7 P=0.006

Sport time average

(hours/week)

6.4 (3.2) 0 – 24.5 5.8 (3.5) 0 – 26.5 P=0.004

Sport participation (top 5) Sport Numbers Percentage Sport Numbers Percentage

Soccer 643 34.5% Running 106 13.6%

Fitness 189 10.1% Soccer 101 13.0%

Running 173 9.3% Fitness 90 11.6%

Strength training 152 8.2% Gymnastics 53 6.8%

Fighting sports 115 6.2% Volleyball 40 5.1%

* NS=not significant

The ECG characteristics of female athletes showed significant differences compared to the

male athletes. Female athletes had a significantly higher resting heart rate and QTc interval. Male

athletes had a significantly higher PR interval and QRS duration. The histogram for the QRS duration

is shown in Figure 1. Male athletes had a mean QRS duration of 98.08ms with a standard deviation of

10.243ms. The female athletes had a mean QRS duration of 87.9ms with a standard deviation of

8.796ms. There was no significant difference in the QRS axis between males and females. The R and S

peaks in leads V1, V2 (only S peak), V5/V6 and the extremity leads were significantly higher in male

than in female athletes (see Table 2).

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Table 2. ECG characteristics and Training-related ECG changes (group 1) ECG characteristics Male (n=1027) Female (n=409) P-value

Mean (SD) Range Mean (SD) Range Indp. T-test

Heart Rate Beats/min 64 (12) 38 - 133 69 (13) 43 - 111 0.000

QRS axis Degree 73 (34) 178 - -171 71 (27) 159 - -129 P= 0.393

PR interval Ms 149 (20) 98 - 238 141 (20) 100 - 280 0.000

QRS duration Ms 98 (10) 75 - 137 88 (9) 67 - 137 0.000

QTc interval Ms 400 (17) 355 - 469 407 (19) 362 - 479 0.000

R in V1 Mm 3.2 (2.0) 0.5 – 14.5 2.1 (1.4) 0.5 – 8.0 0.000

S in V5/V6* Mm 2.5 (2.0) 0.0 – 17.0 1.8 (1.5) 0.0 – 11.0 0.000

R in V5/V6* Mm 18.7 (5.5) 4.5 – 44.5 14.1 (4.2) 6.0 – 39.5 0.000

R or S in standard

lead

Mm 15.0 (4.7) 4.0 – 31.0 13.2 (4.0) 5.0 – 24.5 0.000

Training-related ECG changes

(group 1)

Number % Number % Chi-square

Sinus bradycardia < 60/min 393 38.3% 94 23.0% 0.000

<51/min 119 11.6% 20 4.9% 0.000

Sinus arrhythmia

**

Present 299 29.1% 114 27.9% -

Rhythm Atrial /

Junctional

20 1.9% 8 2.0% -

AV-block 1st Degree 15 1.5% 7 1.7% -

2nd Degree

(Mobitz I)

0 0.0% 0 0.0% -

Incomplete RBBB RsR’ V1 & QRS

100-120ms 195 15.0% 15 3.7% 0.000

Isolated QRS

voltage criteria for

LVH

Sokolow(6)

index ≥ 35mm

270 26.3% 19 4.6% 0.000

Early

repolarisation

46 4.5% 4 1.0% 0.001

Total group 1

changes

≥ 1 change 769 74.9% 209 51.1% 0.000

≥ 2 change 362 25.2% 48 11.7% 0.000

* Highest voltage was used ** sinus arrhythmia is defined as a P-P interval >120ms in two consecutive beats with a normal P-

wave morphology and unchanged PR interval

Training-related (group 1) ECG changes were significantly more common in male athletes.

They had significantly more sinus bradycardia, incomplete RBBB, early repolarisation and isolated

QRS voltage criteria for LVH. There were no significant differences in sinus arrhythmias,

atrial/junctional rhythms and first- and second-degree AV blocks (see Table 2).

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Training-unrelated changes (group 2) were more common in male athletes (male 48 (4.7%)

vs. female 13 (3.2%)). This difference was not significant. Most abnormalities were found in the

abnormal Q-wave criterion (male 18 (1.8%) vs. female 2 (0.5%)), the left axis criterion (male 11 (1.1%)

vs. female 3 (0.7%)) and the T-wave inversion criterion (male 8 (0.8%) vs. female 6 (1.5%)). The total

number of abnormal ECGs using the Seattle criteria was 61 (4.2%).

With the screening and additional testing we were able to diagnose one case of hypertrophic

cardiomyopathy (HCM) and two cases of ventricular pre-excitation (WPW). The HCM case was a male

student athlete of African ethnicity who had deep negative T-waves in the inferolateral leads on his

ECG. The two WPW cases were one male and one female student athlete of Western European

ethnicity. They both had a short PQ interval, widening of QRS duration and presence of a delta wave

on their ECG.

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Figure 1. Norm value distribution for QRS duration by gender. Percentage as total per variable.

DISCUSSION

An ECG is subject to gender-related differences.1,2 Also the ECG of an athlete is different from that of

a non-athletic counterpart because of the development of what is known as an ‘athlete’s heart’. An

athlete’s heart is a physiological adaption to intensive and repetitive exercise, leading to structural,

functional and electrophysiological changes in the heart of an athlete. An athlete’s heart represents

the endpoint in the development during which electrophysiological changes will gradually occur.

Adaptations fitting the athlete’s heart have been well described by Prior and La Gerche (2012).7

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Gender-related ECG differences in athletes have only been described by Wasfy et al..3 They

described gender differences in a small cohort of 330 competitive rowers as a reference for other

ECG screenings in rowers, but did not discuss possible implications for screening.

In an effort to prevent sudden cardiac death in young athletes, Corrado et al. introduced the

Lausanne ECG criteria in 2005.4 The goal of these criteria is to separate normal athlete ECGs from

abnormal and potentially pathological athlete ECGs. Since their introduction in 2005, updated

versions of the Lausanne ECG criteria have been proposed to improve sensitivity and specificity. A

version was introduced in 2010 by the European Society of Cardiology (ESC) and another in 2013 by

Drezner et al. (the Seattle criteria).5,6 Except for the different gender-based criteria for longQT, these

ECG criteria use the same normal range values for male and for female athletes.

With this study we evaluated whether there are gender-based differences in the ECGs of

young athletes, and if so whether this could have implication for cardiac screening for young

athletes. In this study we demonstrated gender differences in ECGs of young athletes and we

speculate on their possible impact on screening.

In contrast to Mason et al. and Wasfy et al., we did not find gender-based differences in QRS

axis.1,3 Whether or not this gender difference in QRS axis is significant, the clinical implications will be

limited based on the absolute difference found in the present study (M 73 vs. F 71 degrees) and the

studies of Mason et al. (M 38 vs. F 36 degrees) and Wasfy et al. (M 74 vs. F 67 degrees).

All other variables (HF, QRS duration, PR interval and QTc interval) are significantly different.

The R and S peaks in all measured leads are also significantly higher in male than in female athletes.

These differences in characteristics were also observed in large non-athletic populations by Mason et

al. (2007) and by Ramirez et al. (2011).1,2 Wasfy et al. also described these differences in their cohort

of highly competitive rowers.3

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In the present study male athletes also show significantly more training-related ECG changes

than their female counterparts. The total number of student athletes with one or more training-

related ECG changes (e.g. 70,3%) is comparable to other athletic cohorts.8-10

Wasfy et al. (2015) also observed a significant difference in training-related ECG changes

between male and female competitive rowers.3 They found that male athletes had higher amounts

of early repolarisation and more isolated QRS voltage criteria for LVH. Compared to the present

study, they did not find a significant difference in the presence of sinus bradycardia or of an

incomplete RBBB pattern.

Despite these gender influences on ECGs, we still mainly use the same normal-range values

for both genders. We use different gender-related norm values only for the QTc interval. The reason

for not using gender-related norm values in ECG interpretation could be that cardiovascular

diagnoses are usually made by a combination of complaints, (e.g. chest pain), history, physical

evaluation and additional testing (e.g. blood tests, echocardiogram). Diagnoses are rarely made

purely on the ECG alone; therefore gender-related differences on the ECG have a low clinical impact.

In contrast to this, in the cardiovascular screening of young athletes according to the

Lausanne protocol, an abnormal ECG alone is merit for further testing. When we use ECG as a

screening tool and base our decision for referral and further testing on gender-influenced numbers

alone, we could consider using different gender-based cut-off values. This is the case for example

with the QTc interval. To determine whether there is a possibility of Long QT syndrome, we use the

QTc value as guidance to whether or not we should consider further evaluation. Since norm value

distribution between males and females differs, we use different gender-based cut-off values.11

In the current Seattle criteria we use the single value of the QRS duration in the criterion for

intraventricular conduction delay to discriminate between normal and abnormal and to determine

whether further testing is advised.

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As is shown in Figure 1, the QRS duration has a gender-based difference in norm value

distribution. This was also found by Wasfy et al. (Figure 1 of that article). As the absolute difference

between male and female in distribution is relatively large in proportion (e.g. mean value difference

of 10ms), this difference seems not only significant but also clinically relevant. Since we use QRS

duration in the intraventricular conduction delay criterion in the same manner as we use QTc, we

could consider using different gender-based cut-off values for the QRS duration in this criterion.

To determine what the clinical impact would be and where the optimal cut-off values could

be, we would have to look at the norm value distribution for the pathology we are screening for with

this criterion. Given that the present study only focuses on non-pathological (‘normal’) ECGs, we are

not able to determine the possible clinical impact or to advise a cut-off value based on this study

alone. This is something to be determined by further research. The other ECG characteristics that are

showing gender-based differences (e.g. PR interval, heart rate and lead voltages) are not used solely

as cut-off value in the current Seattle ECG criteria. The implications of using gender-based cut-off

values for these ECG characteristics will therefore be limited.

This study has a few limitations. First, it was conducted on a very homogeneous population,

with over 95% Western European ethnic/genetic background. Race and genetic background have a

major influence on ECG findings for athletes in groups 1 and 2; hence our conclusions cannot be

extrapolated to athletes of a different race or ethnicity.12-16

Secondly, when performing a cardiovascular screening only a small part will be referred for

further testing. This could mean that we might have missed some cardiovascular pathology. The total

numbers we referred (80) and the detected major pathology (3) we found are comparable to other

studies.8,14,17-23 We therefore think that the chances of having missed significant cardiovascular

pathologies are limited.

Thirdly, this study only looked at healthy/non-pathological athletic ECGs, so no ‘norm values’

in QRS duration distribution patterns are known for athletes with cardiovascular pathology. It could

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be that there are no gender differences when the heart becomes pathological, but this does not

seem likely.

Fourthly, since this study only looked at healthy/non-pathological athletic ECGs, we have no

data on what the impact could be on detecting more cardiac pathology in females. This is something

to be investigated in further research.

Fifthly, the studied population consisted of mainly competitive athletes but not of top-level

elite athletes. Since the elite athletes usually exercise more frequently, the results for this population

could be different or even more pronounced.

Finally, the gender differences in ECG among athletes could be explained at least partially by

differences in sports participation, as men exercise more and practise different sport types. On the

other hand, the difference in sports time per week is only just over 30 minutes. Besides, the ECG

differences we found are similar to those found for the non-athletic population. If the gender

differences came from different exposure to exercise, one would expect to see no difference in the

unexposed non-athletic population. The effect of sports participation on the development of athletic

ECGs remains a topic for further research.

CONCLUSION

ECGs of young athletes demonstrate gender-related differences in PR interval, heart rate, QRS

duration and lead voltages. These gender differences should be considered when using these

characteristics in the screening of young athletes, because application of the same normal values

might cause more false-positive and false-negative screening results. When looking at the current

Seattle ECG criteria, we would advise additional research into the clinical impact of using gender-

based cut-off values for the QRS duration in the intraventricular conduction delay criterion.

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