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The effectiveness of screening history, physical exam, and ECG to detect
potentially lethal cardiac disorders in athletes:
A systematic review/meta-analysis
Kimberly G. Harmon, M.D.,
a, b,
⁎Monica Zigman, M.P.H.,
a
Jonathan A. Drezner, M.D.
a
a
Department of Family Medicine, University of Washington, Seattle, WA, USA
b
Department of Orthopaedics and Sports Medicine, University of Washington, Seattle, WA, USA
Abstract Background: The optimal cardiovascular preparticipation screen is debated. The purpose of this
study was to perform a systematic review/meta-analysis of evidence comparing screening strategies.
Methods: PRIMSA guidelines were followed. Electronic databases were searched from January
1996 to November 2014 for articles examining the efficacy of screening with history and physical
exam (PE) based on the American Heart Association (AHA) or similar recommendations and
electrocardiogram (ECG). Pooled data was analyzed for sensitivity, specificity, false positive rates
and positive and negative likelihood ratios. Secondary outcomes included rate of potentially lethal
cardiovascular conditions detected with screening and the etiology of pathology discovered.
Results: Fifteen articles reporting on 47,137 athletes were reviewed. After meta-analysis the sensitivity
and specificity of ECG was 94%/93%, history 20%/94%, and PE 9%/97%. The overall false positive rate
of ECG (6%) was less than that of history (8%), or physical exam (10%). Positive likelihood ratios were
ECG 14.8, history 3.22 and PE 2.93 and negative likelihood ratios were ECG 0.055, history 0.85, and PE
0.93. Therewere a total of160 potentially lethal cardiovascular conditions detected for a rate of 0.3% or 1
in 294. The most common pathology was Wolff-Parkinson-White (67, 42%), Long QT Syndrome
(18, 11%), hypertrophic cardiomyopathy (18, 11%), dilated cardiomyopathy (11, 7%), coronary artery
disease or myocardial ischemia (9, 6%) and arrhythmogenic right ventricular cardiomyopathy (4, 3%).
Conclusions: The most effective strategy for screening for cardiovascular disease in athletes is ECG.It is
5 times more sensitive than history, 10 times more sensitive than physical exam, has higher positive
likelihood ratio, lower negative likelihood ratio and a lower false positive rate. 12-lead ECG interpreted
using modern criteria should be considered best practice in screening for cardiovascular disease in
athletes while the use of history and physical alone as a screening tool should be reevaluated.
© 2015 Elsevier Inc. All rights reserved.
Keywords: Preparticipation exam; Athlete; Cardiovascular screening; ECG; Sudden cardiac death
Introduction
The preparticipation examination (PPE) or periodic health
examination (PHE) is the practice of regularly screening
athletes prior to participation in sport. PPEs have been
common place in the United States for over 50 years, in
some countries such as Italy for decades, and in other
countries like England PPEs are not required. Although there
are many objectives to the PPE, it is widely agreed that the
primary purpose of the PPE is to screen for potentially
life-threatening disorders [1–5]. Cardiovascular pathology
leading to sudden cardiac death (SCD) is the most common
medical cause of death in athletes [6–8]. Therefore, a large
portion of effort during the PPE is directed toward screening
for cardiovascular disease. Screening has traditionally
consisted of a history and physical examination although
the utility of this approach has been questioned [9,10]. More
recently there has been interest in adding a resting 12-lead
electrocardiogram (ECG) to the PPE to improve detection of
conditions associated with SCD. ECG screening is supported
by Italian data showing a 90% decrease in the rate of SCD
with the inclusion of ECG as part of athlete screening [6],
although other studies have questioned this result [11]. The
debate regarding various screening strategies engenders
passionate support on both sides. This paper examines the
data related to preparticipation cardiovascular screening in
Available online at www.sciencedirect.com
ScienceDirect
Journal of Electrocardiology 48 (2015) 329–338
www.jecgonline.com
⁎Corresponding author at: Departments of Family Medicine and
Orthopaedics and Sports Medicine, University of Washington, 3800 Montlake
Blvd, Seattle, WA 98195, USA.
E-mail address: kharmon@uw.edu
http://dx.doi.org/10.1016/j.jelectrocard.2015.02.001
0022-0736/© 2015 Elsevier Inc. All rights reserved.
athletes through a systematic review of existing studies. The
sensitivity, specificity, and positive predictive value of
history, physical exam and ECG in the individual studies
are calculated and a meta-analysis of pooled data performed
in an effort to better understand the value and limitations of these
tests in order to guide rational evidence-based approaches for
cardiovascular screening in athletes.
Methods
The Preferred Reporting Items for Systematic Reviews
and Meta-Analyses (PRIMSA) guidelines were followed con-
ducting and reporting this review.
Search strategy
Relevant articles were identified by searching the
following electronic databases: Medline, CINAHL, Embase,
SportDiscus, The Cochrane Library, and PEDro. Database
entries were searched from January 1996 to November of
2014. Initial AHA recommendations for cardiovascular
screening in athletes were published in 1996 [12]. Search
terms used included ECG, athlete, screening, preparticipation,
history, and physical. Keywords were searched individually
and grouped. The reference lists of the relevant articles and
ePublication lists of key journals were manually reviewed for
additional pertinent studies.
Selection criteria
Inclusion criteria for this analysis required: (1) the study
reported on the outcomes of cardiovascular screening in
athletes using history, physical exam, and ECG; (2) the
history questions and physical exam were based on the AHA
recommendations or similar guidelines; and (3) ECGs were
interpreted using modern standards defined as criteria
attempting to account for the physiologic changes of training
in the athletic heart. Non-English language reports, confe-
rence abstracts, and review or clinical commentary articles
were excluded. Only manuscripts by the same authors using
different case populations were included. The titles and abstracts
of the articles were reviewed to determine eligibility for
inclusion in the analysis. Where eligibility was unclear the full
text article was retrieved and reviewed.
Assessment of study quality
A seven-item quality assessment checklist was developed
to assess for risk of bias. The seven items assessed were:
(1) participant selection criteria described, (2) representative
sample, (3) data collected prospectively and had at least one
positive finding, (4) modern ECG criteria used for screening,
(5) cardiovascular screening history and physical exam
similar to recommended AHA guidelines, (6) outcomes were
reported by individual tests (history, physical exam, and
ECG), and (7) abnormal screening tests were evaluated by
appropriate diagnostic testing. For each item articles were
assessed as having fulfilled or not fulfilled the criterion.
Articles with a score of 7 were considered of highest quality.
Articles with potential bias were not excluded.
Data extraction and synthesis
A data-extraction form was developed specifically for this
review with data obtained from each study. Data was
extracted by one author (KH) and checked for accuracy by
the other authors. Acquired data included the total number of
participants in the study as well as their sex, the number
of true positives, true negatives, false positives and false
negatives based on the total number of disorders identified in
the study. If these data were not available in the article or
could not be calculated from the data provided, the
corresponding author was contacted and asked for additional
information. In some cases one element (i.e. physical
exam) could not be extracted but data from other elements
(i.e. history and ECG) could and then these elements were
included. In addition, the type of ECG criteria used and the
total number of potentially serious cardiovascular abnor-
malities discovered as well as the specific types of pathology
were extracted. After the primary data was obtained, the
sensitivity, specificity, false positive, and positive predic-
tive value (PPV) of each screening test was calculated
based on the total disorders identified by history, physical
exam, and ECG. A false negative rate was not be
calculated because in the majority of studies only those
identified as abnormal with initial screening received
additional definitive work-up. Thus, there were likely
additional cardiovascular abnormalities not detected by
any of the screening methods.
Calculations and analysis were performed in either STATA
11.0 (College Station, TX) or Excel (Redmond, WA).
Heterogeneity among studies was evaluated using
coupled forest plots. Summary points for sensitivity and
specificity were estimated using a bivariate random effects
meta-analysis model. The use of a random effects meta-
analysis model takes the heterogeneity into account and
provides a conservative estimate of pooled sensitivity
and specificity [13,14]. Secondary outcomes included
the overall rates and types of cardiovascular pathology
identified. Cardiovascular pathology rates were calculated
using simple ratios.
Results
The literature search initially yielded 787 articles. 756
articles were immediately excluded. There were 31 articles
that potentially met the inclusion criteria and these were
downloaded for further review. Of those 31, 16 articles were
excluded because the study screened only with ECG and did
not screen with a cardiovascular history or physical exam
[15–22] the athletes were screened with ECG, history and
physical exam but the statistics needed were not in the
article, could not be calculated from the information in the
article, and the corresponding author either did not have the
data or did not reply to inquires [23–25]; the cohort was
pre-identified with cardiovascular disease [17,26]; there was
not at least one positive finding in the cohort [27,28];orthe
manuscript was a letter to the editor [29]. Fifteen studies
were included for full review (Fig. 1).
330 K.G. Harmon et al. / Journal of Electrocardiology 48 (2015) 329–338
Quality assessment
Overall, the quality assessment for the 15 articles ranged
from 5 to 7. Three studies did not separate outcomes
for history and physical exam and reported them together
[30–32]. 10 of the 15 studies did not have a representative
sample and looked at only a subset of the overall group of
young athletes. Three looked primarily at high school
athletes [33–35], 2 had only male or predominantly male
participants [36–38], 2 examined only college athletes
[39,40], and one study had a wider age range (5–39 years)
than others [41]. However, taken in aggregate the group
represented a broad and diverse population of athletes and
was representative of screening in a wide array of settings.
Demographic data
A total of 47,137 athletes were screened. There were
29,658 (66%) males and 15,014 females (34%) exclu-
ding one manuscript that did not report on gender
breakdown [31]. The group was ethnically and racially
diverse (Table 1). The athletes screened were from
Algeria, France, Germany, Greece, the Netherlands, Qatar,
Spain, the United Kingdom, and the United States. The
athletes ranged in age from 5 to 39 years and were primarily
competitive athletes although some studies included active
adolescents as well (Table 1).
Sensitivity, specificity, false positive rate and positive
predictive value
The sensitivity, specificity, false positive rate and positive
predictive values demonstrated in various studies are shown
in Table 2. The combined false positive rates for history,
physical exam, and ECG were 8%, 10%, and 6%,
respectively. There was a wide range of false positive rates
for ECG reflecting the different criteria used for interpreta-
tion (1%–19%). Likewise, there was a wide range of false
positive rates for history ranging from 1% to 31%.
Meta-analysis of the fifteen studies (Table 3), showed
ECG was the most accurate screening test with a pooled
sensitivity of 94% (79%–98%), specificity of 93% (90%–
96%), and a positive likelihood ratio of 14.8 (9.43–23.16)
indicating that a positive ECG test largely increases the
likelihood of disease. The pooled sensitivity decreased for
history 20% (7%–44%) and physical exam 9% (3%–24%),
and the specificity remained similar for history 94% (89%–
96%) and physical exam 97% (95%–98%) compared to
ECG. History 3.22 (1.3–8.01) and physical exam 2.93
(1.26–6.83) had similar positive likelihood ratios indicating
that a positive result for either test suggests a small increase
in the likelihood of disease. Figs. 2–4show coupled forest
plots of sensitivity and specificity for each test, with articles
ranked in order of decreasing sensitivity.
787 articles - initial search
31 articles downloaded for
review
18 excluded
8- screened only with ECG (no H&P)
3- pertinent data not included in manuscript
2- not screening studies, cohort had disease
2- no cases of CV disease found
1- letter to the editor
15 included in review
756 title/abstracts reviewed-
excluded based on relevance
Fig. 1. Article selection.
Table 1
Demographics of individual studies.
Author Year N Males Females Population Country
Fuller 1997 5615 3375 2240 High school athletes U.S.
Wilson 2008 2720 National and international junior athletes and active school children U.K.
Bessem 2009 428 322 106 Athletes (22) Netherlands
He via 2009 1220 1171 49 Athletes (23) Spain
Baggish 2010 510 311 199 College athletes U.S.
Magalski 2011 964 463 501 College athletes U.S.
Wilson 2011 1220 1220 0 National level athletes Qatar
Assanelli 2012 6634 5307 1327 Athletes (25.2) Greece, Germany, France, Algeria
Snoek 2013 306 398 163 Students 16–35 median 18 Netherlands
Fudge 2014 1339 656 683 Active adolescents U.S.
Price 2014 2017 1432 585 High school athletes U.S.
Menagoflio 2014 1070 805 265 Regional, national, international Switzerland
Alattar 2014 230 230 0 Organized sport Dubai
Deligiannis 2014 22,205 13,546 8659 Competitive athletes Greece
Anderson 2014 659 422 237 Adolescent athletes (15.4) U.S.
Total 47,137 29,658 15,014
66% 34%
331K.G. Harmon et al. / Journal of Electrocardiology 48 (2015) 329–338
Table 2
Sensitivity, specificity, false positive rate, and positive predictive value of individual studies.
Sensitivity (95% CI) Specificity (95% CI) False positive (95% CI) Positive predictive value (95% CI)
Author Year History PE ECG History PE ECG History PE ECG History PE ECG ECG criteria
Fuller 1997 0%
(0%–
45.9%)
17%
(0.42%–
64.1%)
83%
(35.9%–
99.6%)
97.9%
(97.5%–
98.3%)
96.9%
(96.4%–
97.3%)
97.5%
(97%–
97.9%)
2%
(1.7%–
2.5%)
3%
(2.7%–
3.6%)
2.5%
(2.1%–
2.9%)
0%
(0%–
3.16%)
0.57%
(0.01%–
3.14%)
3.4%
(1.12%–
7.81%)
No specific criteria
Wilson 2008 0%
(0%–
33.6%)
–100%
(66.4%–
100%)
97.5%
(96.9%–
98.1%)
–98.9%
(98.4%–
99.2%)
2.4%
(1.9%–
3.1%)
–1.1%
(0.7%–
1.6%)
0%
(0%–
5.36%)
–22.5%
(10.8%–
38.5%)
No specific criteria
Bessem 2009 25%
(0.63%–
80.6%)
0%
(0%–
60.2%)
75%
(19.4%–
99.4%)
94.8%
(92.2%–
96.7%)
97.4%
(95.4%–
98.7%)
92.5%
(89.5%–
94.8%)
5.2%
(3.3%–
7.8%)
2.6%
(1.3%–
4.6%)
7.5%
(5.2%–
10.5%)
4.3%
(0.11%–
21.9%)
0%
(0%–
28.5%)
8.6%
(1.8%–
23.1%)
Lausaunne criteria
Hevia 2009 0%
(0%–
45.9%)
0%
(0%–
45.9%)
100%
(54.1%–
100%)
99.1%
(98.4%–
99.5%)
99.6%
(99.2%–
99.9%)
93.9%
(92.5%–
95.3%)
0.9%
(0.4%–
1.6%)
0.3%
(.08%–
0.8%)
5.9%
(4.7%–
7.4%)
0%
(0%–
28.5%)
0%
(0%–
60.2%)
7.6%
(2.84%–
15.8%)
2005 ESC
Baggish 2010 0%
(0%–
70.8%)
33%
(0.84%–
90.6%)
66%
(9.43%–
99.2%)
95.8%
(93.7%–
97.4%)
97.8%
(96.2%–
98.9%)
84%
(80.5%–
87.1%)
4.1%
(2.6%–
6.3%)
2.2%
(1.1%–
3.8%)
15.9%
(12.9%–
19.4%)
0%
(0%–
16.1%)
8.33%
(0.21%–
38.5%)
2.4%
(0.29%–
8.43%)
2005 ESC
Magalski 2011 44%
(13.7%–
78.8%)
11%
(0.28%–
48.2%)
100%
(66.4%–
100%)
75.2%
(72.4%–
78%)
94.5%
(92.8%–
95.8%)
90.9%
(89%–
92.7%)
24.7%
(22.0%–
27.6%)
5%
(4.2%–
7.2%)
9%
(7.3%–
11.0%)
1.67%
(0.46%–
4.21%)
1.2%
(0.05%–
9.89%)
9.5%
(4.42%–
17.2%)
No specific criteria
Wilson 2011 42%
(9.9%–
81.6%)
–100%
(59%–
100%)
82%
(80.2%–
84.5%)
–91%
(88.8%–
92.2%)
17.6%
(15.5%–
19.8%)
–9.4%
(7.8%–
11.2%)
1.4%
(0.29%–
4.01%)
–5.8%
(2.36%–
11.6%)
No specific criteria
Assanelli 2012 74%
(61.6%–
85.6%)
–100%
(93.5%–
100%)
98%
(97.8%–
98.5%)
–97%
(96.5%–
97.3%)
2%
(1.5%–
2.2%)
–3%
(2.7%–
3.5%)
26%
(19.5%–
33.6%)
–21%
(16.4%–
26.7%)
2010 ESC
332 K.G. Harmon et al. / Journal of Electrocardiology 48 (2015) 329–338
Snoek 2013 0%
(0%–
70.8%)
0%
(0%–
70.8%)
33%
(0.84%–
90.6%)
83%
(79.1%–
87.7%)
97%
(95.3%–
99.1%)
78%
(73.1%–
82.7%)
16.2%
(12.3%–
20.9%)
2.3%
(0.9%–
4.7%)
21.9%
(17.3%–
26.9%)
0%
(0%–
7.25%)
0%
(0%–
41%)
1.5%
(0.04%–
8.04%)
2010 ESC
Alattar 2014 50%
(11.8%–
88.2%)
0%
(0%–
45.9%)
100%
(54.1%–
100%)
90%
(85.5%–
93.7%)
97%
(93.7%–
98.7%)
81%
(75.5%–
86.1%)
9.8%
(6.3%–
14.5%)
3%
(1.3%–
6.3%)
19%
(13.9%–
24.5%)
12%
(2.55%–
31.2%)
0%
(0%–
41%)
12.5%
(4.73%–
25.2%)
ESC/Lausaunne
Deligiannis 2014 61%
(42.1%–
77.1%)
48%
(30.8%–
66.5%)
70%
(51.3%–
84.4%)
91%
(90.5%–
91.3%)
85%
(84.6%–
85.6%)
92%
(91.4%–
92.1%)
9%
(8.7%–
9.5%)
14.9%
(14.4%–
15.4%)
8%
(7.9%–
8.6%)
1%
(0.6%–
1.51%)
0.5%
(0.28%–
0.78%)
1.2%
(0.79%–
1.87%)
2010 ESC
Menagoflio 2014 0%
(0%–
60.2%)
0%
(0%–
60.2%)
100%
(39.8%–
100%)
98.7%
(97.8%–
99.3%)
98.6%
(97.7%–
99.2)
96.4%
(95.1%–
97.5%)
1.3%
(0.7%–
2.2%)
1.4%
(0.7%–
2.3%)
3.6%
(2.5%–
4.9%)
0%
(0%–
23.2%)
0%
(0%–
21.8%)
9.5%
(2.66%–
22.6%)
2010 ESC
Fudge 2014 40%
(5.27%–
85.3%)
0%
(0%–
52.2%)
100%
(47.8%–
100%)
68.5%
(66%–
71.1%)
90.3%
(89%–
92.2%)
94.9%
(93.7%–
96.1%)
31.4%
(28.9%–
34.0%)
9.3%
(7.8%–
11.0%)
5%
(3.9%–
6.3%)
0.47%
(0.06%–
1.71%)
0%
(0%–
2.93%)
6.9%
(2.29%–
15.5%)
Pre-Seattle
Price 2014 20%
(0.50%–
71.6%)
20%
(0.51%–
71.6%)
100%
(47.8%–
100%)
87.9%
(86.4%–
89.3%)
96.3%
(95.4%–
97.1%)
97.2%
(96.3%–
97.8%)
12%
(10.7%–
13.6%)
3.6%
(2.9%–
4.6%)
2.8%
(21.5%–
36.6%)
0.4%
(0.01%–
2.26%)
1%
(0.03%–
7.21%)
8.1%
(2.67%–
17.8%)
2010 ESC
Anderson 2014 20%
(0.50%–
71.6%)
20%
(0.51%–
71.6%)
80%
(28.4%–
99.5%)
92%
(90%–
94.3%)
96%
(94.6%–
97.6%)
89%
(86.3%–
91.3%)
8%
(5.7%–
10%)
3.6%
(2.4%–
5.4%)
11%
(8.7%–
13.7%)
2%
(0.05%–
10.4%)
4%
(0.1%–
20.4%)
5.3%
(1.45%–
12.9%)
No specific criteria
48% (40%–55.8%) 23.6% (15.2%–33.8%) 90%
(84.3%–
94.2%)
92.3%
(92.1%–
92.5%)
89.6%
(89.2%–
89.9%)
93.8%
(93.6%–
94%)
7.7%
(7.5%–
7.9%)
10.4%
(10.1%–
10.8%)
6.2%
(6.0%–
6.4%)
2.1%
(1.65%–
2.6%)
0.5%
(0.34%–
0.84%)
4.7%
(4.0%–
5.5%)
333K.G. Harmon et al. / Journal of Electrocardiology 48 (2015) 329–338
Cardiovascular pathology
There were 160 potentially lethal cardiovascular condi-
tions identified in 47,137 athletes for a rate of 0.3% or 1 in
every 294 athletes. Wolff-Parkinson-White (WPW) was
the most frequently identified pathology (67, 42%), followed
by Long QT Syndrome (LQTS) (18, 11%), hypertrophic
cardiomyopathy (HCM) (18, 11%), dilated cardiomyopathy
(11, 7%), coronary artery disease (CAD)/myocardial ische-
mia (MI) (9, 6%), and arrhythmogenic right ventricular
cardiomyopathy (ARVC) (4, 3%). The rate of WPW was 1
in every 703 athletes while the rate of identified HCM and
LQTS was 1 in 2618.
Discussion
The data on cardiovascular screening in a diverse
population of over 47,000 athletes around the world is
summarized by this systematic review. Cardiovascular
screening examinations prior to participation in sport have
a long history with various countries, states, and sporting
organizations recommending or requiring differing elements.
Most notably, the European Society of Cardiology (ESC),
International Olympic Committee (IOC), Federation Inter-
nationale de Football Association (FIFA), and various U.S.
professional sporting organizations recommend a cardiovas-
cular screen inclusive of ECG [2,42], while the AHA
recommends a 14-point personal and family history and
Table 3
Meta-analysis of pooled data.
ECG History Physical
Sensitivity 94% (79%–98%) 20% (7%–44%) 9% (3%–24%)
Specificity 93% (90%–96%) 94% (89%–96%) 97% (95%–98%)
Positive likelihood ratio* 14.8 (9.43–23.16) 3.22 (1.3–8.01) 2.93 (1.26–6.83)
Negative likelihood ratio* 0.055 (0.012–0.25) 0.85 (0.68–1.07) 0.93 (0.85–1.03)
*Interpretation of likelihood ratios
Likelihood ratio Interpretation
N10 Large and often conclusive increase in the likelihood of disease
5–10 Moderate increase in the likelihood of disease
2–5 Small increase in the likelihood of disease
1–2 Minimal increase in the likelihood of disease
1 No change in the likelihood of disease
0.5–1.0 Minimal decrease in the likelihood of disease
0.2–0.5 Small decrease in the likelihood of disease
0.1–0.2 Moderate decrease in the likelihood of disease
b0.1 Large and often conclusive decrease in the likelihood of disease
SENSITIVITY (95% CI)
0.95[0.81 - 0.99]
0.33 [0.01 - 0.91]
0.67 [0.09 - 0.99]
0.70 [0.51 - 0.84]
0.75 [0.19 - 0.99]
0.80 [0.28 - 0.99]
0.83 [0.36 - 1.00]
1.00 [0.48 - 1.00]
1.00 [0.66 - 1.00]
1.00 [0.54 - 1.00]
1.00 [0.66 - 1.00]
1.00 [0.54 - 1.00]
1.00 [0.94 - 1.00]
1.00 [0.59 - 1.00]
1.00 [0.40 - 1.00]
1.00 [0.48 - 1.00]1.00 [0.48 - 1.00]
STUDY(YEAR)
COMBINED
Snoek 2013
Baggish 2010
Deligiannis 2014
Bessem 2009
Anderson 2014
Fuller 1997
Fudge 2014
Wilson 2008
Hevia 2009
Magalski 2011
Alattar 2014
Assanelli 2012
Wilson 2011
Menagoflio 2014
Price 2014
0.0 1.0
SENSITIVITY
ECG
SPECIFICITY (95% CI)
0.94[0.90 - 0.96]
0.78 [0.73 - 0.83]
0.84 [0.81 - 0.87]
0.92 [0.91 - 0.92]
0.92 [0.90 - 0.95]
0.89 [0.86 - 0.91]
0.97 [0.97 - 0.98]
0.95 [0.94 - 0.96]
0.99 [0.98 - 0.99]
0.94 [0.93 - 0.95]
0.91 [0.89 - 0.93]
0.81 [0.76 - 0.86]
0.97 [0.96 - 0.97]
0.91 [0.89 - 0.92]
0.96 [0.95 - 0.97]
0.97 [0.96 - 0.98]0.97 [0.96 - 0.98]
STUDY(YEAR)
COMBINED
Snoek 2013
Baggish 2010
Deligiannis 2014
Bessem 2009
Anderson 2014
Fuller 1997
Fudge 2014
Wilson 2008
Hevia 2009
Magalski 2011
Alattar 2014
Assanelli 2012
Wilson 2011
Menagoflio 2014
Price 2014
0.0 1.00.5
SPECIFICITY
ECG
Fig. 2. Forest plot of sensitivity and specificity of ECG.
334 K.G. Harmon et al. / Journal of Electrocardiology 48 (2015) 329–338
cardiovascular physical exam without an ECG [4]. While
there is widespread agreement that cardiovascular screening
in athletes is “justifiable, necessary, and compelling on the
basis of ethical, legal and medical grounds”the AHA has
cited concern regarding the high false positive rate of ECG
[2,5]. However, as evidenced by this review, ECG actually
has a lower false positive rate than either history or physical
exam even when considering that 9 of the 15 studies used
older criteria such as the 2005 or 2010 ESC criteria that have
higher false positive rates than more recently defined
standards for ECG interpretation in athletes. Newer ECG
criteria such as the Seattle Criteria have decreased the false
positive rate while retaining the sensitivity to detect
pathologic conditions [43–47]. International collaboration
will further refine and improve ECG criteria.
The screening history questions that are currently
recommended are based on expert opinion. There is little
research into how well different aged populations or cultures
understand the questions or how different demographic
groups answer the questions. In addition, there is concern
that the typical history questions inquire about symptoms
which are common place, subjective and not specific to
those with cardiac disease. While chest pain or shortness
of breath can be indicative of cardiovascular pathology,
it can also be indicative of many other conditions
including gastrointestinal, musculoskeletal, psychological
or pulmonary issues. Studies looking at the number of AHA
based history questions initially answered positive prior
to physician review report positive rates of 35%–60%
[23,30,34] while other studies report positive history responses
as low as 1% [38,48].
This wide range of positive responses depends on whether
the history questions are considered positive if answered
affirmatively initially by the athlete or considered positive
only after review by a physician or in combination with a
normal ECG. When positive rates are reported after review
by a physician it is often not possible to tell how many
positive responses were disregarded because further testing
SENSITIVITY (95% CI)
0.20[0.07 - 0.44]
0.00 [0.00 - 0.34]
0.00 [0.00 - 0.60]
0.00 [0.00 - 0.46]
0.00 [0.00 - 0.71]
0.00 [0.00 - 0.46]
0.00 [0.00 - 0.71]
0.20 [0.01 - 0.72]
0.20 [0.01 - 0.72]
0.25 [0.01 - 0.81]
0.40 [0.05 - 0.85]
0.43 [0.10 - 0.82]
0.44 [0.14 - 0.79]
0.50 [0.12 - 0.88]
0.61 [0.42 - 0.77]
0.75 [0.62 - 0.86]0.75 [0.62 - 0.86]
STUDY(YEAR)
COMBINED
Wilson 2008
Menagoflio 2014
Fuller 1997
Baggish 2010
Hevia 2009
Snoek 2013
Anderson 2014
Price 2014
Bessem 2009
Fudge 2014
Wilson 2011
Magalski 2011
Alattar 2014
Deligiannis 2014
Assanelli 2012
0.0 1.0
SENSITIVITY
History
SPECIFICITY (95% CI)
0.94[0.89 - 0.96]
0.98 [0.97 - 0.98]
0.99 [0.98 - 0.99]
0.98 [0.98 - 0.98]
0.96 [0.94 - 0.97]
0.99 [0.98 - 1.00]
0.84 [0.79 - 0.88]
0.92 [0.90 - 0.94]
0.88 [0.86 - 0.89]
0.95 [0.92 - 0.97]
0.69 [0.66 - 0.71]
0.82 [0.80 - 0.85]
0.75 [0.72 - 0.78]
0.90 [0.86 - 0.94]
0.91 [0.91 - 0.91]
0.98 [0.98 - 0.98]0.98 [0.98 - 0.98]
STUDY(YEAR)
COMBINED
Wilson 2008
Menagoflio 2014
Fuller 1997
Baggish 2010
Hevia 2009
Snoek 2013
Anderson 2014
Price 2014
Bessem 2009
Fudge 2014
Wilson 2011
Magalski 2011
Alattar 2014
Deligiannis 2014
Assanelli 2012
0.0 1.0
SPECIFICITY
History
Fig. 3. Forest plot of sensitivity and specificity of history.
SENSITIVITY (95% CI)
0.09[0.03 - 0.25]
0.00 [0.00 - 0.46]
0.00 [0.00 - 0.46]
0.00 [0.00 - 0.52]
0.00 [0.00 - 0.71]
0.00 [0.00 - 0.60]
0.00 [0.00 - 0.60]
0.11 [0.00 - 0.48]
0.17 [0.00 - 0.64]
0.20 [0.01 - 0.72]
0.20 [0.01 - 0.72]
0.33 [0.01 - 0.91]
0.48 [0.31 - 0.66]
. [. - .]
. [. - .]
. [. - .]. [. - .]
STUDY(YEAR)
COMBINED
Hevia 2009
Alattar 2014
Fudge 2014
Snoek 2013
Menagoflio 2014
Bessem 2009
Magalski 2011
Fuller 1997
Anderson 2014
Price 2014
Baggish 2010
Deligiannis 2014
Assanelli 2012
Wilson 2011
Wilson 2008
0.0 1.0
SENSITIVITY
Physical Exam
SPECIFICITY (95% CI)
0.97[0.95 - 0.98]
1.00 [0.99 - 1.00]
0.97 [0.94 - 0.99]
0.91 [0.89 - 0.92]
0.98 [0.95 - 0.99]
0.99 [0.98 - 0.99]
0.97 [0.95 - 0.99]
0.94 [0.93 - 0.96]
0.97 [0.96 - 0.97]
0.96 [0.95 - 0.98]
0.96 [0.95 - 0.97]
0.98 [0.96 - 0.99]
0.85 [0.85 - 0.86]
. [. - .]
. [. - .]
. [. - .]. [. - .]
STUDY(YEAR)
COMBINED
Hevia 2009
Alattar 2014
Fudge 2014
Snoek 2013
Menagoflio 2014
Bessem 2009
Magalski 2011
Fuller 1997
Anderson 2014
Price 2014
Baggish 2010
Deligiannis 2014
Assanelli 2012
Wilson 2011
Wilson 2008
0.0 1.0
SPECIFICITY
Physical Exam
Fig. 4. Forest plot of sensitivity and specificity of physical.
335K.G. Harmon et al. / Journal of Electrocardiology 48 (2015) 329–338
in those athletes was deferred. There were 2 studies that
performed echocardiograms in all athletes [39,40] and one
that did echocardiography for all athletes in the first half of
the 18 year study period [41]. In these studies the sensitivity
of ECG (80%) was still superior compared to history (50%)
and physical exam (33%). Although the screening questions
may serve as a flag for further questioning, the ability to
correctly differentiate positive versus negative responses by
both experts and primary care physicians is unknown.
SCD is the presenting symptom in cardiovascular
pathology in up to 80% of cases [49], therefore screening
for prodromal symptoms by history will miss the over-
whelming majority of cases. The 20% of athletes who do
have warning signs preceding death may have symptoms
which are non-specific and fairly ubiquitous making
screening by history alone challenging. For example,
abnormal history responses were initially reported in 68%
of responses on the Pre-participation Physical Evaluation
Monograph screening questions in a cardiovascular screen of
active adolescents [34]. After review by a physician over half
of these responses were not thought to be relevant and were
disregarded, however in this study 31% of the total
population screened still went on for further testing because
of a positive history question [34]. In other studies 11%–
15% of athletes reported a positive history of exertional chest
pain [33,40], exercise associated dizziness (12%) [30], and
exertional dyspnea (7%–15%) [33,40]. In contrast, some
studies report a very low rate of positive responses to history
questions [31,35,39,48]. The reason for the discrepancy
between positive rates is likely due to differences in athlete
population, manner in which the question is asked and understood,
and the amount of overview done by a physician.
In this meta-analysis physical exam had the lowest
sensitivity, the highest specificity, the lowest positive
likelihood ratio and highest negative likelihood ratio. PE
also had the highest false positive rate. The primary findings
prompting further review on cardiovascular screening is a
murmur or physical stigmata of Marfan’s. The most common
reason for secondary testing was a murmur on physical
exam. The accuracy of auscultation to distinguish physiologic
from pathologic murmurs compared to echocardiography for
detection of cardiac pathology has been questioned [50].
The most common identified condition associated with
SCD was WPW with an incidence of 1 in 703 athletes. This
is consistent with reports of a prevalence of 1 to 4.5 per 1000
individuals [51]. In some studies HCM is reported as the
leading cause of death in athletes in the United States with a
reported prevalence of 1 in 500 in adults [8]. In other studies
and in other countries it appears that HCM is a less common
cause of SCD in athletes with autopsy-negative unexplained
death or presumed arrhythmia being the most common cause
of death [52–57]. In this systematic review of over 47,000
athletes screened there were 18 cases of HCM discovered for
an incidence of 1 in 2618. ECG should detect over 90% of
cases of HCM [58,59]. It is possible that some cases of HCM
were missed and the actual prevalence of HCM is higher. Of
the 12,353 cases that were screened with history, physical
exam, ECG and echocardiogram, there was 1 case of HCM
out of the 5 detected that was found only by echocardiogram.
Because this review looked at pooled data from around the
world and some reports have suggested that a large
proportion of deaths in the US are due to HCM, the data
was re-analyzed for screening studies in the US only. There
were 11,104 US athletes screened and only 2 cases of HCM
detected for a prevalence of HCM in the US of 1 in 5552.
This data would suggest that HCM is less prevalent in athletes
at screening than expected.
Interestingly, of the 47,137 cases screened there were no
reports of coronary artery abnormalities. This is surprising
because in studies reporting the etiology of SCD in athletes
[8,52,53,60–62] or military recruits [55] SCD due to
coronary artery abnormalities (CAA) represent between
6% and 27%. ECG would not be expected to detect CAA,
however, screening with history and physical exam did not
detect any CAA despite reports that 44% of athletes who
died from CAA had prodromal symptoms such as syncope or
chest pain [63]. Nearly a quarter of the total population was
screened with echocardiogram in addition to history,
physical exam and ECG and there were still no CAA
detected. It is not clear which echocardiographic screening
protocols were utilized and whether or not they were
sufficient to identify CAAs. It is likely that the overall
incidence of cardiac pathology found in this study is actually
higher than stated because of undetected CAAs, as well
as other disorders not routinely identified by history,
physical exam, or ECG such as aortopathies and premature
coronary atherosclerosis.
Strengths and limitations
The strengths of this review are that it combines data on
the screening of 47,137 athletes with a measure of the quality
of the studies and meta-analysis of pooled data. The findings
reinforce the emerging body of literature supporting the
effectiveness of ECG in screening for potentially lethal
cardiac disease in athletes while also demonstrating the low
relative of history and physical exam.
There were several limitations to this review. The
meta-analysis did not have the level of data to investigate
the interaction of several factors on the outcome. These
factors include age group of the study populations or clinical
experience of the diagnosing staff. The small number of
studies included in this review also prevented stratification
for sub-group analysis. Therefore conclusions cannot make
on how these factors impact testing accuracy.
Another limitation to this study is the criteria used to
evaluate ECG results. The various criteria used for screening
included the Lausanne criteria, the ESC 2005 or 2010
criteria, or no specific published criteria but the authors of
the study described what they considered physiologic versus
pathologic findings [2,42,64]. A standardization of criteria
would lead to more definitive screening results and reduce
the potential for misclassification bias.
There was a moderate degree of heterogeneity among the
estimates for specificity and sensitivity. This could have
resulted from the diversity of study populations and study
locations. The random-effects meta-analysis takes this into
336 K.G. Harmon et al. / Journal of Electrocardiology 48 (2015) 329–338
account and provides conservative estimates for pooled
sensitivity and specificity estimates. However, future analysis
of studies using similar ECG criteria for interpretation will likely
decrease statistical heterogeneity. Finally, not all athletes were
screened with definitive studies (echocardiogram, cardiac magnetic
resonance imaging, genetic testing) and therefore pathology may
have been missed. Thus, sensitivity and specificity were based
on the total number of disorders identified in the study.
Conclusions
The purpose of this study was to perform a systematic
review/meta-analysis of evidence comparing screening
strategies. There were fifteen articles identified reporting
on 47,137 athletes. The sensitivity of 12-lead ECG was much
higher than both history and physical with similar sensitivity.
In addition, the false positive rate of ECG (6%) was less than
that of history (8%), or physical exam (10%). ECG had the
highest positive likelihood ratios and lowest negative
likelihood ratios. There were a total of 160 potentially lethal
cardiovascular conditions detected for a rate of 0.3% which is
consistent with other studies. The most common pathology
identified was electrical disease and hypertrophic cardiomyopathy
was a relatively infrequent finding. This meta-analysis suggests that
electrical disease is more common cause of death than
cardiomyopathies. This meta-analysis shows that ECG is the
most effective strategy for screening for cardiovascular disease
in athletes, and the use of history and physical exam alone as a
screening tool should be reevaluated.
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