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Visual or computer-based measurements: important for interpretation of athletes’ ECG
  1. H M Berge1,
  2. K Steine2,3,
  3. T E Andersen1,
  4. E E Solberg4,
  5. K Gjesdal3,5
  1. 1Oslo Sports Trauma Research Center, The Norwegian School of Sport Sciences, Oslo, Norway
  2. 2Department of Cardiology, Akershus University Hospital, Lørenskog, Norway
  3. 3Institute of Clinical Medicine, University of Oslo, Oslo, Norway
  4. 4Department of Internal Medicine, Diakonhjemmet Hospital, Oslo, Norway
  5. 5Department of Cardiology, Oslo University Hospital, Oslo, Norway
  1. Correspondence to Dr Hilde Moseby Berge, Oslo Sports Trauma Research Center, the Norwegian School of Sport Sciences, Sognsveien 220, P O Box 4014, Ullevaal Stadion, Oslo 0806, Norway, hilde.moseby.berge{at}


Background ECG is recommended for preparticipation health examination in athletes. Owing to a lack of consensus on how to read and interpret athletes’ ECGs, different criteria for abnormality are used.

Aims To compare the prevalence of abnormal ECGs and test the correlation between visual and computer-based measurements.

Methods In a preparticipation cardiac screening examination of 595 male professional soccer players aged 18–38 years, ECGs were categorised according to the European Society of Cardiology's (ESC) recommendations and the Seattle criteria, respectively. Visual measurements were conducted with callipers on-screen on the averaged PQRST complex in each lead, calculated by the trimmed mean. Computer-based measurements were derived from the medium beat. Heart rhythm and conduction were scored visually by a cardiologist. Categorical variables were compared by κ statistics (K) and continuous variables by intraclass correlation.

Results ECGs of good quality were available from 579 players. According to the ESC's recommendations and Seattle criteria, respectively, ECGs were categorised as abnormal in 171 (29.5%) vs 64 (11.1%) players after visual assessment, and in 293 (50.6%; K=0.395) vs 127 (21.9%; K=0.564) after computer-based measurements. Intraclass correlation was very good for measurements of R and S wave amplitudes and moderate to very good for intervals. K was very good for pathological Q wave amplitudes and moderate for T wave inversions.

Conclusions Abnormal ECGs were more than twice as common after computer-based than after visual measurements. Such a difference will markedly influence the number of athletes who need further examinations. Reference values may need adjustments dependent on measurement methods.

  • Athletics
  • Soccer
  • Cardiology prevention

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