TY - JOUR
T1 - Relating QRS voltages to left ventricular mass and body composition in elite endurance athletes
AU - the Pro@Heart consortium
AU - De Bosscher, Ruben
AU - Moeyersons, Jonathan
AU - Dausin, Christophe
AU - Claeys, Mathias
AU - Janssens, Kristel
AU - Claus, Piet
AU - Goetschalckx, Kaatje
AU - Bogaert, Jan
AU - Van De Heyning, Caroline M.
AU - Paelinck, Bernard
AU - Sanders, Prashanthan
AU - Kalman, Jonathan
AU - Van Huffel, Sabine
AU - Varon, Carolina
AU - La Gerche, André
AU - Heidbuchel, Hein
AU - Claessen, Guido
AU - Willems, Rik
AU - Van Soest, Sofie
AU - Hespel, Peter
AU - Dymarkowski, Steven
AU - Dresselaers, Tom
AU - Miljoen, Hielko
AU - Favere, Kasper
AU - Vermeulen, Dorien
AU - Witvrouwen, Isabel
AU - Hansen, Dominique
AU - Thijs, Daisy
AU - Vanvoorden, Peter
AU - Ghekiere, Olivier
AU - Herbots, Lieven
AU - Lefebvre, Kristof
AU - Flannery, Michael Darragh
AU - Mitchell, Amy
AU - Brosnan, Maria
AU - Prior, David
AU - Elliott, Adrian
AU - Fatkin, Diane
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2023/3
Y1 - 2023/3
N2 - Purpose: Electrocardiogram (ECG) QRS voltages correlate poorly with left ventricular mass (LVM). Body composition explains some of the QRS voltage variability. The relation between QRS voltages, LVM and body composition in endurance athletes is unknown. Methods: Elite endurance athletes from the Pro@Heart trial were evaluated with 12-lead ECG for Cornell and Sokolow-Lyon voltage and product. Cardiac magnetic resonance imaging assessed LVM. Dual energy x-ray absorptiometry assessed fat mass (FM) and lean mass of the trunk and whole body (LBM). The determinants of QRS voltages and LVM were identified by multivariable linear regression. Models combining ECG, demographics, DEXA and exercise capacity to predict LVM were developed. Results: In 122 athletes (19 years, 71.3% male) LVM was a determinant of the Sokolow-Lyon voltage and product (β = 0.334 and 0.477, p < 0.001) but not of the Cornell criteria. FM of the trunk (β = − 0.186 and − 0.180, p < 0.05) negatively influenced the Cornell voltage and product but not the Sokolow-Lyon criteria. DEXA marginally improved the prediction of LVM by ECG (r = 0.773 vs 0.510, p < 0.001; RMSE = 18.9 ± 13.8 vs 25.5 ± 18.7 g, p > 0.05) with LBM as the strongest predictor (β = 0.664, p < 0.001). DEXA did not improve the prediction of LVM by ECG and demographics combined and LVM was best predicted by including VO2max (r = 0.845, RMSE = 15.9 ± 11.6 g). Conclusion: LVM correlates poorly with QRS voltages with adipose tissue as a minor determinant in elite endurance athletes. LBM is the strongest single predictor of LVM but only marginally improves LVM prediction beyond ECG variables. In endurance athletes, LVM is best predicted by combining ECG, demographics and VO2max.
AB - Purpose: Electrocardiogram (ECG) QRS voltages correlate poorly with left ventricular mass (LVM). Body composition explains some of the QRS voltage variability. The relation between QRS voltages, LVM and body composition in endurance athletes is unknown. Methods: Elite endurance athletes from the Pro@Heart trial were evaluated with 12-lead ECG for Cornell and Sokolow-Lyon voltage and product. Cardiac magnetic resonance imaging assessed LVM. Dual energy x-ray absorptiometry assessed fat mass (FM) and lean mass of the trunk and whole body (LBM). The determinants of QRS voltages and LVM were identified by multivariable linear regression. Models combining ECG, demographics, DEXA and exercise capacity to predict LVM were developed. Results: In 122 athletes (19 years, 71.3% male) LVM was a determinant of the Sokolow-Lyon voltage and product (β = 0.334 and 0.477, p < 0.001) but not of the Cornell criteria. FM of the trunk (β = − 0.186 and − 0.180, p < 0.05) negatively influenced the Cornell voltage and product but not the Sokolow-Lyon criteria. DEXA marginally improved the prediction of LVM by ECG (r = 0.773 vs 0.510, p < 0.001; RMSE = 18.9 ± 13.8 vs 25.5 ± 18.7 g, p > 0.05) with LBM as the strongest predictor (β = 0.664, p < 0.001). DEXA did not improve the prediction of LVM by ECG and demographics combined and LVM was best predicted by including VO2max (r = 0.845, RMSE = 15.9 ± 11.6 g). Conclusion: LVM correlates poorly with QRS voltages with adipose tissue as a minor determinant in elite endurance athletes. LBM is the strongest single predictor of LVM but only marginally improves LVM prediction beyond ECG variables. In endurance athletes, LVM is best predicted by combining ECG, demographics and VO2max.
KW - Athlete
KW - Cardiac magnetic resonance imaging
KW - Dual X-ray absorptiometry
KW - Electrocardiogram
KW - Left ventricular mass
UR - http://www.scopus.com/inward/record.url?scp=85143839349&partnerID=8YFLogxK
U2 - 10.1007/s00421-022-05080-5
DO - 10.1007/s00421-022-05080-5
M3 - Article
AN - SCOPUS:85143839349
SN - 1439-6319
VL - 123
SP - 547
EP - 559
JO - European Journal of Applied Physiology
JF - European Journal of Applied Physiology
IS - 3
ER -