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MEASUREMENT METHOD IS IMPORTANT FOR INTERPRETATION OF ATHLETES' ECG
  1. HM Berge1,
  2. K Steine2,
  3. TE Andersen1,
  4. EE Solberg3,
  5. K Gjesdal4
  1. 1Oslo Sports Trauma Research Center, Oslo, Norway
  2. 2Akershus University Hospital, Lørenskog, Norway
  3. 3Diakonhjemmet Hospital, Oslo, Norway
  4. 4Oslo University Hospital, Ullevaal, Oslo, Norway

Abstract

Background Electrocardiography (ECG) is recommended as part of IOC's preparticipation health examination in athletes. The new Seattle criteria for interpreting ECG in athletes are developed with reference values for abnormality, but yet, no guidelines exist on how to perform the measurements.

Objective To test the correlations between visual and computer-based measurements, and examine how method choice influences prevalence of abnormal ECG findings.

Design Cross-sectional study on the Seattle criteria comparing visual and computer-based reading of ECGs.

Setting Preparticipation cardiac screening examination of male professional football players in Norway during a preseason training camp in 2008.

Participants Athletes aged 18–38 years.

Assessment of risk factors All ECG findings suggestive of cardiomyopathy or primary electrical disease were categorized according to the Seattle criteria. Visually, the measurements were conducted with calipers on-screen on the average PQRST complex in each lead, calculated by the trimmed mean. Computer-based measurements were derived from the medium beat. For both, heart rhythm and conduction were scored visually by cardiologist.

Main outcome measurements Prevalence of abnormal ECG findings, and differences between visual and computer-based measurements. Categorical variables were compared by kappa statistics (K).

Results ECG of good quality were available from 579 (97%) of 595 players. The ECG was categorized as abnormal in 64 (11%) players after visual assessment, versus in 122 (21%) after computer-based measurements, mainly due to more abnormal Q wave durations (35), T wave inversions (24) and ST depressions (12) detected by the computer. Abnormal ECG findings suggestive of; cardiomyopathy were present in 62 versus 122 players (Κ=0.544), and primary electrical disease in 8 versus 6 players (Κ=0.855).

Conclusions The correlations between visual and computer-based measurements are moderate. Clinically, this difference will influence the prevalence of abnormal ECG findings in athletes. Thus, method choice should always be reported in preparticipation health examination studies. Reference values may need adjustments dependent on measurement methods.

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