De Bosscher Ruben, Moeyersons Jonathan, Dausin Christophe, Claeys Mathias, Janssens Kristel, Claus Piet, Goetschalckx Kaatje, Bogaert Jan, Van De Heyning Caroline M, Paelinck Bernard, Sanders Prashanthan, Kalman Jonathan, Van Huffel Sabine, Varon Carolina, La Gerche André, Heidbuchel Hein, Claessen Guido, Willems Rik
Department of Cardiovascular Science, KU Leuven, Leuven, Belgium.
Cardiology, University Hospitals Leuven, Leuven, Belgium.
Eur J Appl Physiol. 2023 Mar;123(3):547-559. doi: 10.1007/s00421-022-05080-5. Epub 2022 Nov 14.
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.
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.
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 VOmax (r = 0.845, RMSE = 15.9 ± 11.6 g).
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 VOmax.
心电图(ECG)的QRS电压与左心室质量(LVM)的相关性较差。身体成分可解释部分QRS电压变异性。耐力运动员的QRS电压、LVM与身体成分之间的关系尚不清楚。
对来自Pro@Heart试验的精英耐力运动员进行12导联心电图检查,测量康奈尔电压和索科洛夫-里昂电压及乘积。心脏磁共振成像评估LVM。双能X线吸收法评估躯干和全身的脂肪量(FM)和瘦体重(LBM)。通过多变量线性回归确定QRS电压和LVM的决定因素。建立结合心电图、人口统计学、双能X线吸收法和运动能力来预测LVM的模型。
在122名运动员(19岁,71.3%为男性)中,LVM是索科洛夫-里昂电压及乘积的决定因素(β = 0.334和0.477,p < 0.001),但不是康奈尔标准的决定因素。躯干FM(β = -0.186和-0.180,p < 0.05)对康奈尔电压及乘积有负面影响,但对索科洛夫-里昂标准无影响。双能X线吸收法略微改善了心电图对LVM的预测(r = 0.773对0.510,p < 0.001;均方根误差[RMSE] = 18.9±13.8对25.5±18.7 g,p > 0.05),其中LBM是最强的预测因子(β = 0.664,p < 0.001)。双能X线吸收法并未改善心电图和人口统计学因素联合对LVM的预测,将最大摄氧量(VOmax)纳入后对LVM的预测最佳(r = 0.845,RMSE = 15.9±11.6 g)。
在精英耐力运动员中,LVM与QRS电压相关性较差,脂肪组织是次要决定因素。LBM是LVM最强的单一预测因子,但仅略微改善了超出心电图变量的LVM预测。在耐力运动员中,结合心电图、人口统计学因素和VOmax对LVM的预测最佳。