Comparison of QTc formulas in young athletes

Background Cardiac screening, including a 12-lead electrocardiogram (ECG), is recommended for athletes to detect abnormal findings such as QT prolongation and prevent sudden cardiac death. Since the QT interval is influenced by heart rate (HR), it must be corrected to a standard HR of 60 beats per minute. Several correction formulas exist, with Bazett’s being the most commonly used. Purpose This study sought to compare different QT time correction formulas in athlete screening ECGs and identify the most accurate method for HR-independent QT correction in young athletes. Methods In this retrospective study, we analyzed resting 12-lead ECGs and questionnaires from an existing database of athletes aged 9 to 47 years in the eastern region of Switzerland, collected between 2022 and 2025. Automated and manually measured QT intervals in leads II and V5 were corrected using the Bazett (QTcB), Fridericia (QTcFri), Framingham (QTcFra), Hodges (QTcH), and Rautaharju (QTcR) formulas. QTc to HR correlation coefficients (r) as well as regression slopes (b) were used to assess each formula’s performance. A bootstrap resampling approach (R = 10’000 resamples) was used to obtain the sampling distribution of the QTc-HR correlation and slopes of each correction formula. Results A total of 228 female and male athletes were included (mean age 22 years). For the automated QT time, QTcFri showed the lowest QTc-HR correlation (r = 0.011, 95% CI [-0.118, 0.142]) and flattest regression slope (b = 0.016, 95% CI [-0.173, 0.207]). For the manually calculated QT times, QTcH showed the lowest QTc-HR correlations (lead II r = 0.177, 95% CI [0.045, 0.305], lead V5 r = 0.134, 95% CI [0.003, 0.263]) and the flattest slopes (lead II b = 0.368, 95% CI [0.097, 0.637], lead V5 b = 0.275, 95% CI [-0.004, 0.556]). Overall, QTcB showed the strongest QTc-HR correlations (automated r = 0.570, 95% CI [0.480, 0.660], lead II r = 0.571, 95% CI [0.479, 0.659], lead V5 r = 0.549, 95% CI [0.459, 0.639]) and steepest slopes (automated b = 1.027, 95% CI [0.829, 1.229], lead II b = 1.520, 95% CI [1.191, 1.851] , lead V5 b = 1.433, 95% CI [1.107, 1.767]). QTcB also had the highest quantity of pathological values for the automated and manually calculated QT times. Conclusions QTcFri performed best for the automated QT time and QTcH for the manually calculated QT times. All four formulas QTcFri, QTcFra, QTcH and QTcR provided more consistent QT time correction than Bazett’s formula. The Fridericia and Hodges formulas could be an alternative to Bazett’s formula in young athlete screening to avoid false-positive QT prolongation and unnecessary disqualification.