There has been an evolution of athlete specific Electrocardiogram (EKG) criteria over the years, resulting in improved specificity and lower false positive rates, starting with the European Society of Cardiology 2005 guidelines and most recently with the current 2017 International Recommendations. The consistency of EKG interpretation with the 2017 International Criteria have been compared between various groups, including local and specialized center physicians. Whether novice EKG interpreters (undergraduate/graduate students) can be taught to accurately interpret athletes’ EKGs with the 2017 International Criteria has not been extensively studied. This study seeks to assess the accuracy and variability of novice EKG interpreters, compared to cardiologist interpretations and expert readers.
Three novice EKG interpreters (undergraduate exercise science students) were trained in interpreting EKGs of athletes with the 2017 International Criteria during one semester under the instruction of an expert reader. During an annual high school, sports screening day 1350 EKGs were collected and assigned a corresponding number. The on-site cardiologists evaluated the EKGs in real-time and classified as “normal” or “abnormal” according to the International Criteria. Following the sports physical day, three novice EKG interpreters (students), a cardiologist and a Clinical Exercise Physiology Professor (expert reader) were asked separately to classify the same EKGs as “normal or “abnormal” according to the International Criteria. All readers were blinded to the initial classifications made by the cardiologist during the sports physical event. Information regarding the athlete's age, gender, race/ethnicity, and sport was provided on the EKGs. We assessed the agreement between the cardiologist, expert reader and students in interpreting EKGs using Fleiss' kappa analysis.
1350 athlete EKGs (males = 879; females = 471, age (mean + SD) 15.09 + 1.3y) including 37 (2.7%) abnormal cases were reviewed. The inter-rater agreement between novice readers, expert reader, and physicians in classifying an EKG as abnormal was good (k = 0.7, p < .001).
This study demonstrated that novice EKG readers could correctly classify EKGs based on the International Criteria as “normal and abnormal” to identify athletes at high risk of acute cardiovascular events