Do athletic ECG changes predict athletic performance in Gurkha recruits?

Michael Paton; A K H Wong; D Cooper; D Pun; J Melhuish; I T Parsons

doi:10.1136/military-2023-002576

Do athletic ECG changes predict athletic performance in Gurkha recruits?

BMJ Mil Health. 2024 Apr 30:e002576. doi: 10.1136/military-2023-002576. Online ahead of print.

Authors

Michael Paton¹, A K H Wong², D Cooper³, D Pun⁴, J Melhuish², I T Parsons^{5

6}

Affiliations

¹ Headquarters Army Medical Services, Camberley, UK michael.paton13@gmail.com.
² Headquarters Army Medical Services, Camberley, UK.
³ University of Cambridge, Cambridge, UK.
⁴ British Gurkhas Nepal, Pokhara, Nepal.
⁵ Carnegie School of Sport, Leeds Beckett University, Leeds, UK.
⁶ Research and Clinical Innovation, Royal Centre for Defence Medicine, Birmingham, UK.

PMID: 38688679
DOI: 10.1136/military-2023-002576

Abstract

Introduction: ECG changes are associated with regular long-term intensive exercise due to electrical manifestations of increased vagal tone, increased ventricular wall thickness and enlarged chamber size. The aim of this study was to further understand the relationship of athletic ECG changes and athletic performance in an athletic population.

Methods: A retrospective cohort study was performed in 195 Nepali civilian males undergoing selection to the Gurkhas. V̇O_2max (maximal oxygen consumption) was estimated from a 1.5-mile run time using Cooper's formula and correlated with athletic ECG adaptations. Variables were explored with univariable and multivariable linear regression.

Results: The median number of athletic changes on ECG was 2 (IQR 1-2). There was no significant correlation (p=0.46) between the number of ECG adaptations and the degree of cardiovascular fitness by estimated V̇O_2max (estV̇O_2max). We found a negligible but significant correlation between the presence of inferior T wave inversion (TWI) and estV̇O_2max (R²=0.03, p=0.02). The multivariable-fitted regression model was: estV̇O_2max~Intercept+presence of RVH (right ventricular hypertrophy) voltage criteria+absence of sinus arrhythmia+T wave axis+inferior TWI. The overall regression was statistically significant: R²=0.10, F(df=4, df=189)=[5.4], p=0.0004). All variables in the multivariable model significantly predicted estV̇O_2max (p<0.04).

Conclusion: ECG changes of athleticism negligibly predict and differentiate athletic performance in our athletic population. The most predictive ECG markers being voltage criteria for left ventricular hypertrophy and RVH. Markers of increased vagal tone were not predictive. TWI, being a marker for disease, was also a marker for athletic performance in this cohort. The number of athletic ECG adaptations did not predict increased athletic performance.

Keywords: Pacing & electrophysiology; Physiology; SPORTS MEDICINE.