Abstract
To assess the value of electrocardiogram (ECG) RV5/V6 criteria for diagnosing left ventricular hypertrophy (LVH) in marathons. A total of 112 marathon runners who met the requirements for “Class A1” events certified by the Chinese Athletics Association in Changzhou City were selected, and their general clinical information was collected. ECG examinations were performed using a Fukuda FX7402 Cardimax Comprehensive Electrocardiograph Automatic Analyser, whereas routine cardiac ultrasound examinations were performed using a Philips EPIQ 7C echocardiography system. Real‐time 3‐dimensional echocardiography (RT‐3DE) was performed to acquire 3‐dimensional images of the left ventricle and to calculate the left ventricular mass index (LVMI). According to the LVMI criteria of the American Society of Echocardiography for the diagnosis of LVH, the participants were divided into an LVMI normal group (n = 96) and an LVH group (n = 16). The correlation between the ECG RV5/V6 criteria and LVH in marathon runners was analysed using multiple linear regression stratified by sex and compared with the Cornell (SV3 + RaVL), modified Cornell (SD + RaVL), Sokolow–Lyon (SV1 + RV5/V6), Peguero–Lo Presti (SD + SV4), SV1, SV3, SV4, and SD criteria. In marathon runners, the ECG parameters SV3 + RaVL, SD + RaVL, SV1 + RV5/V6, SD + SV4, SV3, SD, and RV5/V6 were able to identify LVH (all p < .05). When stratified by sex, linear regression analysis revealed that a significantly higher number of ECG RV5/V6 criteria were evident in the LVH group than in the LVMI normal group (p < .05), both with no adjustment and after initial adjustment (including age and body mass index), as well as after full adjustment (including age, body mass index, interventricular septal thickness, left ventricular end‐diastolic diameter, left ventricular posterior wall thickness, and history of hypertension). Additionally, curve fitting showed that the ECG RV5/V6 values increased with increasing LVMI in marathon runners, exhibiting a nearly linear positive correlation. In conclusions, the ECG RV5/V6 criteria were correlated with LVH in marathon runners.
Keywords: electrocardiogram, left ventricular hypertrophy, marathon runners, RV5/V6 criteria
1. INTRODUCTION
In recent years, with the rising popularity of marathon races, there has been a growing number of marathon enthusiasts participating in the sport. However, the incidence of sudden death among marathon athletes ranges from 0.54 to 2.1 per 100 000, 1 , 2 and many of these deaths are related to sudden cardiac death (SCD). A large amount of skeletal muscle movement and a dramatic increase in pulmonary ventilation and cardiac output during a marathon can cause significant changes in the body's metabolic state. These changes gradually alter cardiac haemodynamics and electrophysiology, which may cause arrhythmias or even sudden death. The primary cause of death in athletes ≥35 years old is coronary heart disease, while the main cause of death in marathon runners <35 years old is myocardial hypertrophy caused by cardiomyopathy. 3 In 2012, Trivax and coworkers 4 proposed the concept of “Phidippides cardiomyopathy”, suggesting that cardiac changes caused by intense and continuous heart exercise, such as marathons, may also be a cardiomyopathy that explains the SCD of some individuals with high‐intensity exercise training, even without evidence of coronary heart disease, valvular disease, or congenital heart disease (such as HCM). This may be due to physiological adaptation and remodelling of the heart caused by long‐term, high‐intensity endurance training, also known as the “athlete's heart”. 5 Exercise‐related left ventricular remodelling is affected by factors such as age, sex, body surface area, exercise intensity, and ethnicity.
Left ventricular hypertrophy (LVH) is the most common condition in which the heart experiences an increased long‐term cardiac load. Transthoracic echocardiography can detect LVH, which may also be observed using electrocardiography (ECG). Electrocardiography (ECG) is the most economical and convenient method of diagnosing LVH. The most commonly used ECG criteria for the clinical diagnosis of LVH are the Cornell (SV3 + RaVL) and Sokolow–Lyon (SV1 + RV5/V6) criteria. 6 Additionally, the modified Cornell criteria (SD + RaVL) 7 and Peguero–Lo Presti criteria (SD + SV4), 8 which have been proposed in recent years, also have good diagnostic value. Although these criteria are commonly used to diagnose hypertension‐related LVH, their applicability to marathon‐related LVH has not yet been examined. Therefore, this study aimed to optimise ECG screening criteria for marathon runners using real‐time 3‐dimensional echocardiography (RT‐3DE) to determine left ventricular mass and to find the ECG standard for identifying LVH in marathon runners.
2. MATERIALS AND METHODS
2.1. Participants
This study enrolled 112 marathon runners (69 men and 43 women, aged 28−65 years) who met the requirements for “Class A1” events certified by the Chinese Athletics Association in Changzhou City. The exclusion criteria were as follows: complete left or right bundle branch block or ventricular paced rhythms; history of coronary stenting or coronary artery bypass grafting; cardiac insufficiency (left ventricular ejection fraction [LVEF] < 50%) 9 ; secondary hypertension; arrhythmia; heart valve disease; cardiomyopathy; and pulmonary, hepatic, renal, immunological, psychiatric, or haematological disorders. This study was approved by the Ethics Committee of the First People's Hospital of Changzhou, China, and all participants signed an informed consent form.
2.2. General clinical data
The data collected included age, height, weight, blood pressure, body surface area (BSA), body mass index (BMI), smoking history, alcohol consumption history, hypertension history, diabetes history, family history of sudden death, running age of marathon, average monthly running distance, number of full marathon races, best time in a marathon race, number of half‐marathon races, and best time in a half‐marathon race. Marames’ running age was categorised into four levels: <1, 1−3, 3−6, and >6 years. Average monthly running distances were divided into five levels: <60 km, 60−100 km, 100−200 km, 200−300 km, and >300 km.
2.3. Electrocardiogram (ECG) examination
ECGs were recorded using a Fukuda FX7402 Cardimax Comprehensive Electrocardiograph Automatic Analyser and coded according to the Minnesota coding standard. The paper speed was set to 25 mm/s, and the calibration was 10 mm/mV. The participants had a quiescent rest for 10 min before the examination to alleviate tension. The electrodes were placed in standard positions, and 12‐lead synchronous ECGs were recorded in the supine position. Each ECG was required to have a smooth, interference‐free baseline with clear graphics. Two physicians independently measured the indicators of the 12‐lead synchronous ECGs using an ECG equipment monitor. All ECG measurements and calculations followed the 2009 International Recommendations for the Standardisation and Interpretation of Electrocardiography and Clinical Application Guidelines. 6 The PR segment was used as the baseline to measure the deepest S or QS waves in all the precordial and limb leads. For the voltage differences within the same lead, only the highest composite voltage was selected. The SD represents the deepest S or QS amplitude in the precordial and limb leads. RV5/V6 refers to the higher voltage from leads RV5 and RV6. Four to six cardiac cycles were recorded for each lead, and the average value was calculated from three consecutive stable baseline cycles. The ECG values for SV1, SV3, SV4, RaVL, RV5/V6, SD, and QRS were recorded for all participants.
2.4. Echocardiography examination
Echocardiography was performed on the same day as the ECG. A Philips EPIQ 7C (Philips Healthcare Royal Philips Electronics, Amsterdam, Netherlands) colour Doppler echocardiographer with an X5‐1 probe was used to perform the complete transthoracic 2D and 3D examinations at frequencies of 1−5 MHz. Participants were instructed to breathe calmly and lie in the left lateral position, and a limb‐lead ECG was connected simultaneously. The parasternal long‐axis section was used to record measurements of interventricular septum thickness (IVST), left ventricular end‐diastolic diameter (LVEDD), and left ventricular posterior wall thickness (LVPWT). After the acquisition of 2‐dimensional images in the standard apical four‐chamber view, the participants were instructed to hold their breath at the end of exhalation, and the full‐volume imaging mode was activated to collect RT‐3DE images of the four cardiac cycles. Offline image analysis was conducted using the 3DQ function of Philips Netherlands QLab 10.5 quantitative analysis software. The mitral annulus level in the apical four‐chamber and two‐chamber views was selected at the end of left ventricular diastole, and manual outlining was performed to delineate the endocardial and epicardial surfaces. The software automatically calculated the left ventricular mass (LVM) and LVEF data. All data were independently interpreted by two or more attending physicians, and the average value was calculated. Left ventricular mass index (LVMI) was calculated as LVMI = LVM/BSA. According to the new standards of the American Society of Echocardiography (ASE), the diagnostic criteria for LVH are LVMI > 115 g/m2 for men and > 95 g/m2 for women. 10
2.5. Statistical methods
SPSS software (version 25.0) and R software (version 3.4.3, http://www.R‐project.org/) were used for data analysis. Normally distributed measurement data were expressed as mean ± standard deviation (x ± s); non‐normally distributed data were expressed as P50 (P25, P75). An unpaired Student's t‐test or Mann–Whitney non‐parametric test was used for group comparisons of continuous variables. Count data are expressed as percentages (%), and Pearson's chi‐squared test or Fisher's exact test was used for categorical variables.
This was a cross‐sectional study. The observation group used a new ECG index (RV5/V6), and the control group are existing ECG standards. A comprehensive literature review was conducted to determine the appropriate values for the parameters used in this study. Based on the findings of the literature review, bilateral α was set to 0.05, and the degree of power was set to 80% to calculate the sample size using a sample size calculation formula. Additionally, considering the relatively small sample size, a strategy involving two outcome variables was employed to enhance the study's statistical power. The left ventricular mass index was treated as both a numerical and dichotomous variable to maximize efficiency. Multivariate linear regression models were used to examine the correlations between multiple ECG indicators and LVH in marathon runners. Three models were used to estimate the association: model 1 (unadjusted); model 2 (adjusted for age and BMI); and model 3 (adjusted for age, BMI, IVST, LVEDD, LVPWT, and history of hypertension). In addition, generalised additive models (GAMs) were used to test whether there was a linear or nonlinear relationship between ECG RV5/V6 and LVMI (numerical and categorical variables). Statistical significance was determined using a two‐sided test, with a significance level set at p < .05.
3. RESULTS
3.1. General clinical characteristics and data from electrocardiograms and echocardiographic data
According to the LVMI criteria, all marathon runners were divided into an LVMI normal group (n = 96) and an LVH group (n = 16). Following stratification by sex, male and female marathon runners were divided into the LVMI normal group (n = 59 for men, n = 37 for women) and the LVH group (n = 10 for men, n = 6 for women). There were no statistically significant differences in sex, age, BSA, BMI, systolic blood pressure, diastolic blood pressure, smoking history, alcohol consumption history, hypertension history, diabetes history, family history of sudden death, LVEF, SV1, SV4, RaVL, QRS, running age of marathon, average monthly running distance, number of full marathons, best time in full marathons, number of half‐marathons, and best time in half‐marathons between the normal LVMI and LVH groups (all p > .05). However, statistically significant differences were observed between the two groups in various parameters, including IVST, LVEDD, LVPWT, LVMI, SV3, SD, RV5/V6, SV1 + RV5/V6, SV3 + RaVL, SD + RaVL, and SD + SV4 (all p < .05). Among them, the echocardiographic indices IVST, LVEDD, LVPWT, and LVMI in the LVH group were higher than those in the normal LVMI group (all p < .05). In addition, the ECG indices SV3, SD, RV5/V6, SV1 + RV5/V6, SV3 + RaVL, SD + RaVL, and SD + SV4 in the LVH group were higher than those in the LVMI normal group (all p < .05), as shown in Table 1.
TABLE 1.
Comparison of basic clinical data, electrocardiogram, and echocardiographic data in different left ventricular thickness groups (n = 112).
| LVMI normal group | LVH group | ||
|---|---|---|---|
| Characteristics | (n = 96) | (n = 16) | p‐value |
| Male sex (n, [%]) | 59(61.46) | 10(62.50) | .937 |
| Age (year) | 45.74 ± 7.21 | 49.31 ± 8.12 | .204 |
| BSA (m2) | 1.71 ± 0.17 | 1.68 ± 0.14 | .517 |
| BMI (kg/m2) | 22.83 ± 2.47 | 23.38 ± 1.51 | .178 |
| SBP (mm Hg) | 131.89 ± 15.87 | 138.09 ± 16.78 | .148 |
| DBP (mm Hg) | 80.39 ± 10.19 | 85.38 ± 12.65 | .132 |
| Smoking history (n, [%]) | 15(15.63) | 3(18.75) | .531 |
| Alcohol consumption history (n, [%]) | 24(25.00) | 4(25.00) | .471 |
| Hypertension history (n, [%]) | 10(10.42) | 3(18.75) | .429 |
| Diabetes history (n, [%]) | 1(1.04) | 1(6.25) | .266 |
| Family history of sudden death (n, [%]) | 2(2.08) | 0(0.00) | .560 |
| IVST (mm) | 0.88 ± 0.08 | 1.06 ± 0.12 | <.001 |
| LVEDD (mm) | 48.67 ± 3.70 | 51.56 ± 2.50 | .003 |
| LVPWT (mm) | 8.70 ± 0.68 | 10.25 ± 1.06 | <.001 |
| LVEF (%) | 64.71 ± 2.16 | 63.69 ± 3.55 | .343 |
| LVMI (male) (g/m2) | 89.08 ± 12.74 | 127.75 ± 8.42 | <.001 |
| LVMI (female) (g/m2) | 80.00 ± 9.82 | 107.88 ± 11.68 | <.001 |
| SV1 (mV) | 0.83 ± 0.40 | 1.06 ± 0.51 | .072 |
| SV3 (mV) | 0.93 ± 0.59 | 1.37 ± 0.70 | .012 |
| SV4 (mV) | 0.60 ± 0.51 | 0.85 ± 0.59 | .064 |
| SD (mV) | 1.41 ± 0.59 | 1.72 ± 0.61 | .030 |
| RaVL (mV) | 0.22 ± 0.20 | 0.27 ± 0.21 | .488 |
| RV5/V6 (mV) | 1.72 ± 0.66 | 2.26 ± 0.69 | .004 |
| QRS (ms) | 105.37 ± 14.58 | 108.00 ± 8.82 | .242 |
| SD + SV4 (mV) | 2.01 ± 1.01 | 2.57 ± 1.11 | .028 |
| SV1 + RV5/V6 (mV) | 2.55 ± 0.86 | 3.32 ± 1.10 | .003 |
| SV3 + RaVL (mV) | 1.15 ± 0.62 | 1.64 ± 0.72 | .009 |
| SD + RaVL (mV) | 1.63 ± 0.62 | 1.99 ± 0.58 | .017 |
| Running age of marathon (n, [%]) | .563 | ||
| <1 year | 7 (7.29) | 0 (0.00) | |
| 1–3 year | 37 (38.54) | 6 (37.50) | |
| 3–6 year | 35 (36.45) | 8 (50.00) | |
| >6 year | 17 (17.70) | 2 (12.50) | |
| Average monthly running distance (n, [%]) | .494 | ||
| <60 km | 10 (10.42%) | 1 (6.25%) | |
| 60–100 km | 17 (17.71%) | 0 (0.00%) | |
| 100–200 km | 36 (37.50%) | 8 (50.00%) | |
| 200–300 km | 29 (30.21%) | 6 (37.50%) | |
| >300 km | 4 (4.17%) | 1 (6.250%) | |
| Number of half‐marathon races (time) | 16.26 ± 22.35 | 11.81 ± 12.10 | .914 |
| Best time in half‐marathon (min) | 110.06 ± 23.89 | 108.27 ± 10.92 | .865 |
| Number of full marathon races (time) | 4.05 ± 6.35 | 2.06 ± 3.26 | .400 |
| Best time in full marathon (min) | 236.08 ± 34.83 | 257.69 ± 46.20 | .154 |
Note: Data are presented as the mean standard deviation, or as n(%).
Abbreviations: BMI, body mass index; BSA, body surface area; DBP, diastolic blood pressure; IVST, interventricular septum thickness; LVEDD, left ventricular end diastolic diameter; LVPWT, left ventricular posterior wall thickness; SBP, systolic blood pressure.
3.2. Multivariate linear regression analysis of the distribution of ECG indicators in different left ventricular masses in marathon runners
Models 1 (unadjusted), 2 (adjusted for age and BMI), and 3 (adjusted for age, BMI, IVST, LVEDD, LVPWT, and a history of hypertension) were used to control for potential confounders. Regression analysis showed that among male marathon runners, compared to the LVMI normal group, the ECG parameters in the LVH group, including SV1, SV3, SD, RV5/V6, SV1 + RV5/V6, SV3 + RaVL, SD + SV4, and SD + RaVL, were significantly different among all three models (all p < .05) (Table 2). In female marathon runners, compared to the LVMI normal group, only RV5/V6 in the LVH group showed a statistically significant difference in all three models (p < .05) (Table 3). In summary, among all marathon runners, only the ECG indicator RV5/V6 showed a statistically significant difference in left ventricular mass among the three models (all p < .05).
TABLE 2.
Multiple regression model of electrocardiogram indexes for male marathon runners in different left ventricular thickness groups.
| SV1(mV) | SV3(mV) | SV4(mV) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| B | 95%CI | p‐value | B | 95%CI | p‐value | B | 95%CI | p‐value | |
| Model 1 (unadjusted) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | 0.425 | 0.148, 0.702 | .004 | 0.551 | 0.152, 0.951 | .009 | 0.160 | −0.022, 0.341 | .093 |
| Model 2 (adjusted for age, BMI) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | 0.412 | 0.140, 0.684 | .004 | 0.656 | 0.249, 1.062 | .002 | 0.182 | −0.011, 0.375 | .071 |
| Model 3 (adjusted for age, BMI, IVST, LVEDD, LVPWT, hypertension) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | 0.380 | 0.109, 0.651 | .008 | 0.629 | 0.212, 1.045 | .004 | 0.173 | −0.024, 0.370 | .094 |
| RV5/V6(mV) | SD(mV) | SD+SV4(mV) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| B | 95%CI | p‐value | B | 95%CI | p‐value | B | 95%CI | p‐value | |
| Model 1 (unadjusted) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | 0.642 | 0.199, 1.086 | .006 | 0.414 | 0.012, 0.816 | .047 | 0.716 | −0.002, 1.435 | .055 |
| Model 2 (adjusted for age, BMI) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | 0.598 | 0.135, 1.061 | .014 | 0.521 | 0.121, 0.920 | .013 | 0.870 | 0.138, 1.603 | .023 |
| Model 3 (adjusted for age, BMI, IVST, LVEDD, LVPWT, hypertension) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | 0.648 | 0.178, 1.118 | .009 | 0.515 | 0.102, 0.929 | .017 | 0.852 | 0.095, 1.610 | .031 |
| SV3 + RaVL(mV) | SV1 + RV5/V6(mV) | SD + RaVL(mV) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| B | 95%CI | p‐value | B | 95%CI | p‐value | B | 95%CI | p‐value | |
| Model 1 (unadjusted) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | 0.603 | 0.191, 1.014 | .005 | 1.067 | 0.496, 1.638 | <.001 | 0.466 | 0.053, 0.878 | .031 |
| Model 2 (adjusted for age, BMI) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | 0.710 | 0.287, 1.134 | .002 | 1.010 | 0.432, 1.589 | .001 | 0.575 | 0.153, 0.998 | .010 |
| Model 3 (adjusted for age, BMI, IVST, LVEDD, LVPWT, hypertension) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | 0.698 | 0.262, 1.135 | .003 | 1.028 | 0.429, 1.627 | .001 | 0.585 | 0.148, 1.022 | .011 |
Abbreviations: BMI, body mass index; IVST, interventricular septum thickness; LVEDD, left ventricular end diastolic diameter; LVPWT, left ventricular posterior wall thickness.
TABLE 3.
Multiple regression model of electrocardiogram indexes for female marathon runners in different left ventricular thickness groups.
| SV1(mV) | SV3(mV) | SV4(mV) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| B | 95%CI | p‐value | B | 95%CI | p‐value | B | 95%CI | p‐value | |
| Model 1 (unadjusted) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | −0.10 | −0.420, 0.212 | .523 | 0.253 | −0.025, 0.531 | .081 | 0.160 | −0.022, 0.341 | .093 |
| Model 2 (adjusted for age, BMI) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | −0.076 | −0.414, 0.263 | .663 | 0.274 | −0.020, 0.569 | .076 | 0.182 | −0.011, 0.375 | .071 |
| Model 3 (adjusted for age, BMI, IVST, LVEDD, LVPWT, hypertension) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | −0.069 | −0.404, 0.267 | .690 | 0.269 | −0.043, 0.580 | .099 | 0.173 | −0.024, 0.370 | .094 |
| RV5/V6(mV) | SD(mV) | SD + SV4(mV) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| B | 95%CI | p‐value | B | 95%CI | p‐value | B | 95%CI | p‐value | |
| Model 1 (unadjusted) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | 0.339 | 0.212, 0.844 | .001 | 0.133 | −0.212, 0.478 | .454 | 0.293 | −0.176, 0.762 | .228 |
| Model 2 (adjusted for age, BMI) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | 0.391 | 0.205, 0.848 | .002 | 0.202 | −0.161, 0.564 | .283 | 0.384 | −0.109, 0.876 | .135 |
| Model 3 (adjusted for age, BMI, IVST, LVEDD, LVPWT, hypertension) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | 0.450 | 0.227, 0.881 | .001 | 0.153 | −0.210, 0.516 | .415 | 0.326 | −0.184, 0.835 | .219 |
| SV3+RaVL(mV) | SV1+RV5/V6(mV) | SD+RaVL(mV) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| B | 95%CI | p‐value | B | 95%CI | p‐value | B | 95%CI | p‐value | |
| Model 1 (unadjusted) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | 0.282 | −0.029, 0.593 | .083 | 0.235 | −0.362, 0.832 | .444 | 0.162 | −0.193, 0.517 | .377 |
| Model 2 (adjusted for age, BMI) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | 0.266 | −0.059, 0.591 | .117 | 0.316 | −0.320, 0.951 | .336 | 0.193 | −0.182, 0.568 | .319 |
| Model 3 (adjusted for age, BMI, IVST, LVEDD, LVPWT, hypertension) | |||||||||
| LVMI normal group | Reference | Reference | Reference | ||||||
| LVH group | 0.283 | −0.055, 0.622 | .110 | 0.381 | −0.255, 1.018 | .248 | 0.167 | −0.219, 0.553 | .402 |
Abbreviations: BMI, body mass index; IVST, interventricular septum thickness; LVEDD, left ventricular end diastolic diameter; LVPWT, left ventricular posterior wall thickness.
3.3. Curve fitting
Following stratification by sex, the GAMs were used to examine the correlation between ECG RV5/V6 values and LVMI. After adjusting for covariates (age, BMI, IVST, LVEDD, LVPWT, and history of hypertension), ECG RV5/V6 values gradually increased with an increase in LVMI in marathon runners, showing an approximately linear positive correlation (mean degrees of freedom: 1.000, p < .001). In the groups divided according to LVMI, the ECG RV5/V6 values increased in the LVH group (p < .001) (Figure 1).
FIGURE 1.
(A) Correlation between LVH and adjusted mean of RV5/V6 for male marathon runners. (B) Correlation between LVH and adjusted mean of RV5/V6 for female marathon runners. (C) Correlation between LVMI and RV5/V6 for male marathon runners. (D) Correlation between LVMI and RV5/V6 for female marathon runners.
4. DISCUSSION
Marathons are high‐intensity endurance sports in which the body undergoes significant metabolic changes, including increased heart rate, reduced coronary perfusion, coronary vasoconstriction, increased oxygen demand, and increased ventricular load. 4 These changes gradually alter cardiac haemodynamics and electrophysiology and affect cardiac homeostasis. Long‐term, high‐intensity endurance training can result in physiological adaptations and remodelling, potentially resulting in the development of the “athlete's heart” condition. This condition is characterised by ventricular enlargement, myocardial hypertrophy, increased cardiac output, and a decreased resting heart rate. 5 , 11
In a study by Pelliccia and coworkers, 12 it was found that approximately 2% of well‐trained adult male athletes had a slight increase in left ventricular wall thickness (13−15 mm), and 15% had left ventricular enlargement exceeding 60 mm. Both ventricular enlargement and myocardial thickening contribute to an increase in LVM. However, Ghorayeb and coworkers 13 found that the pressure and volume overload caused by intensive physical exercise only represents haemodynamic stimuli for the development of LVH and not necessarily neurohumoral changes in pathological hypertrophy. Notably, LVH in athletes appears to be limited to myocytes and does not result in changes to the extracellular matrix or interstitial fibrosis. On the other hand, Prior and coworkers 5 describe exercise‐stimulated left ventricular remodelling as a “physiological” response. The molecular mediators of “pathological” LVH (natriuretic peptides, vasoactive hormones, and catecholamines) differ significantly from those mediating LVH in athletes (nutritional hormones such as insulin‐like growth factor). These manifestations differ from those observed in hypertension‐related LVH.
Currently, there are no reference standards for normal left ventricular thickness and mass in marathons. However, this study aimed to define LVH based on real‐time 3‐dimensional echocardiography‐derived LVMI, using the normal standards of the ASE as a reference. Additionally, the study examined the distribution of ECG indicators in different cohorts to identify more suitable ECG indicators for LVH in marathon runners.
Pre‐race 12‐lead ECG screening may be particularly important for reducing the risk of sudden death during competitions. ECG examinations are also applicable to outdoor activities, such as marathons, and are often used to detect arrhythmias. Herm and coworkers 14 equipped 109 athletes with a portable ECG recorder during a marathon race to monitor arrhythmias during competition. Lasocka and coworkers 15 compared the ECG values before and after a race in amateur marathon runners and found that male runners exhibited higher exercise‐induced ECG changes than female runners. Physicians should explain the various ECG abnormalities in these athletes, including training‐related ECG changes that are common in marathon runners, such as sinus bradycardia, sinus arrhythmia, and LVH. 16
The 12‐lead ECG is the most economical and convenient diagnostic method for LVH in clinical settings, typically detecting LVH through changes in the electrical voltage of myocardial activity. In this study, the sequence of ventricular activation in the LVH group was the same as that in the control group. However, because the depolarising surface of the hypertrophic left ventricle was enlarged and the positions shifted to different degrees leftward, downward, and backwards, the direction and size of the QRS vector loop of the left ventricular wall depolarisation were changed. The ECG showed that the QRS vector loop was more leftward and backward, and the amplitude, voltage, and time were increased.
The current international ECG diagnostic criteria commonly used for LVH are the Cornell criteria and the Sokolow–Lyon criteria, which have been widely validated for the diagnosis of hypertension‐related LVH. 17 Additionally, a series of derived ECG criteria related to LVH have been developed, 7 , 8 most of which have been investigated in sex‐specific groups. Porthan and coworkers 18 found that the Cornell criteria tended to identify LVH in women, whereas the Sokolow–Lyon criteria tended to identify LVH in men. In this study, ECG criteria, including the SD, RV5/V6, Cornell, and Sokolow–Lyon criteria, as well as their derived criteria, were associated with LVH in male marathon runners, whereas only RV5/V6 was associated with LVH in female marathon runners. This may be due to differences in female body size and anatomy, sex hormones, and other hormones of the endocrine system, further confirming the existence of sex differences in the ECG diagnostic criteria for LVH.
In this study, RT‐3DE data from marathon runners were collected, and LVH cases were screened according to the ASE's standards. RT‐3DE, which is known for its adaptability to regional differences in wall thickness, provides accurate measurements of left ventricular mass. 19 Instead of cardiac magnetic resonance (CMR), a more applicable and common echocardiography was used due to the outdoor complexity of marathons, the high cost of CMR, and its limited availability in remote areas. Participants were stratified by sex, and different models were established to adjust for confounders and validate the relationship between LVH and all ECG indicators according to the criteria for different sexes. Multiple regression analysis showed that ECG RV5/V6 was not sex dependent and was associated with LVH in marathons. Our study revealed that, unlike the ECG criteria for hypertensive LVH, the ECG criteria for marathon runners may be attributed to physiological cardiac adaptation from regular exercise and unique electrophysiological manifestations after long‐term high‐intensity exercise. Sharma and coworkers 20 found that pathological LVH, such as hypertension, is usually associated with additional ECG characteristics, such as T‐wave inversion (TWI) in the inferior and lateral leads, ST segment depression, and pathological Q‐wave. However, an isolated high QRS voltage meeting the voltage standard for LVH is considered a normal and training‐related ECG change in athletes.
Marathon runners must consider not only the impact of LVH but also morphological changes in the lungs and alterations in lung function on cardiac electrical activities. Long‐term marathons can also cause adaptive changes in the lungs, 21 , 22 including increased lung volume, which can further shift the heart slightly downward, further changing the direction and size of the QRS vector loop of the left ventricular wall depolarisation. Thus, the ECG V5/V6 position better reflects the myocardial electrical activity of the left ventricle in the context of LVH and increased lung volume, particularly in overcoming challenges in women owing to their body anatomy. Indeed, Sugita and coworkers 23 reported that RV5 amplitudes were correlated with left ventricular mass in both men and women, which is consistent with the findings of this study. This study used the GAM to further confirm that the ECG RV5/V6 value was linearly and positively correlated with LVMI in marathons.
In summary, the RV5/V6 criteria of the ECG can conveniently and dynamically reflect LVH in marathon runners, which is of great significance in preventing SCD and guiding athletes and long‐distance runners to exercise appropriately. However, there are some limitations to this study. Firstly, the sample size of the marathon runners that participated in this study was relatively small. Secondly, the low sensitivity of ECG in some rare cases of LVH, such as myocardial amyloidosis, was overlooked. In addition, follow‐up of long‐term adverse cardiac events in marathon runners has not yet been completed.
5. CONCLUSIONS
The ECG RV5/V6 criteria were correlated with LVH in marathons. Thus, this measure can be used as a simple method to detect the presence of LVH during marathons.
AUTHOR CONTRIBUTIONS
Pan Yang, Zhixiang Ge, Min Xu participated in research design, data analysis and interpretation, and writing of the manuscript; Jinmei Gao, Xia Liu participated in sample collection, and contributed to the acquisition and interpretation of data; Min Xu, Haiyan Ke participated in research design and supervised the course of the project. All authors read and approved the final manuscript.
CONFLICT OF INTEREST STATEMENT
None.
DATE AVAILABILITY STATEMENT
The data underlying this article will be shared on reasonable request to the corresponding author.
ACKNOWLEDGMENTS
This study was generously supported by Changzhou Health Commission Youth Project QN202208 and Top Talent of Changzhou “The 14th Five‐Year Plan” High‐Level Health Talents Training Project 2022260.
Yang P, Ge Z, Gao J, Liu X, Xu M, Ke H. Evaluation of the electrocardiogram RV5/V6 criteria in the diagnosis of left ventricular hypertrophy in marathon runners. J Clin Hypertens. 2023;25:638–646. 10.1111/jch.14692
Pan Yang and Zhixiang Ge are co‐first authors.
Contributor Information
Min Xu, Email: loisicelin@163.com.
Haiyan Ke, Email: khyrain2014@163.com.
REFERENCES
- 1. Schwabe K, Schwellnus M, Derman W, et al. Medical complications and deaths in 21 and 56 km road race runners: a 4‐year prospective study in 65 865 runners–SAFER study I. Br J Sports Med. 2014;48(11):912‐918. [DOI] [PubMed] [Google Scholar]
- 2. Beutler J, Schmid E, FischeR S, et al. Sudden cardiac death during a city marathon run. Anaesthesist. 2015;64(6):451‐455. [DOI] [PubMed] [Google Scholar]
- 3. Braber TL, Reitsma JB, Mosterd A, et al. Cardiac imaging to detect coronary artery disease in athletes aged 35 years and older. A scoping review. Scand J Med Sci Sports. 2018;28(3):1036‐1047. [DOI] [PubMed] [Google Scholar]
- 4. Trivax JE, Mccullough PA. Phidippides cardiomyopathy: a review and case illustration. Clin Cardiol. 2012;35(2):69‐73. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Prior DL, La Gerche A. The athlete's heart. Heart. 2012;98(12):947‐955. [DOI] [PubMed] [Google Scholar]
- 6. Hancock EW, Deal BJ, Mirvis DM, et al. AHA/ACCF/HRS recommendations for the standardization and interpretation of the electrocardiogram: part V: electrocardiogram changes associated with cardiac chamber hypertrophy: a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Cardiology Foundation; and the Heart Rhythm Society. Endorsed by the International Society for Computerized Electrocardiology. J Am Coll Cardiol. 2009;53(11):992‐1002. [DOI] [PubMed] [Google Scholar]
- 7. Xu M, Ge Z, Huang J, et al. Modified Cornell electrocardiographic criteria in the assessment of left ventricular hypertrophy geometry of patients with essential hypertension. J Clin Hypertens (Greenwich). 2020;22(7):1239‐1246. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Peguero JG, Lo Presti S, Perez J, et al. Electrocardiographic criteria for the diagnosis of left ventricular hypertrophy. J Am Coll Cardiol. 2017;69(13):1694‐1703. [DOI] [PubMed] [Google Scholar]
- 9. Yao GH, Zhang M, Yin LX, et al. Doppler Echocardiographic Measurements in Normal Chinese Adults (EMINCA): a prospective, nationwide, and multicentre study. Eur Heart J Cardiovasc Imaging. 2016;17(5):512‐522. [DOI] [PubMed] [Google Scholar]
- 10. Marwick TH, Gillebert TC, Aurigemma G, et al. Recommendations on the use of echocardiography in adult hypertension: a report from the European Association of Cardiovascular Imaging (EACVI) and the American Society of Echocardiography (ASE). J Am Soc Echocardiogr. 2015;28(7):727‐754. [DOI] [PubMed] [Google Scholar]
- 11. Heidbuchel H, Prior DL, La Gerche A. Ventricular arrhythmias associated with long‐term endurance sports: what is the evidence? Br J Sports Med. 2012;46(suppl 1):i44‐i50. [DOI] [PubMed] [Google Scholar]
- 12. Pelliccia A, Maron BJ, De Luca R, et al. Remodeling of left ventricular hypertrophy in elite athletes after long‐term deconditioning. Circulation. 2002;105(8):944‐949. [DOI] [PubMed] [Google Scholar]
- 13. Ghorayeb N, Batlouni M, Pinto IM, et al. Left ventricular hypertrophy of athletes: adaptative physiologic response of the heart. Arq Bras Cardiol. 2005;85(3):191‐197. [DOI] [PubMed] [Google Scholar]
- 14. Herm J, Töpper A, Wutzler A, et al. Frequency of exercise‐induced ST‐T‐segment deviations and cardiac arrhythmias in recreational endurance athletes during a marathon race: results of the prospective observational Berlin beat of running study. BMJ Open. 2017;7(8):e015798. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Lasocka Z, Dąbrowska‐Kugacka A, Kaleta AM, et al. Electrocardiographic changes in male and female amateur marathon runners: a comparison study. Int J Sports Med. 2021;42(10):936‐944. [DOI] [PubMed] [Google Scholar]
- 16. Wen X, Huang YM, Shen TH, et al. Prevalence of abnormal and borderline electrocardiogram changes in 13, 079 Chinese amateur marathon runners. BMC Sports Sci Med Rehabil. 2021;13(1):41. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Tomita S, Ueno H, Takata M, et al. Relationship between electrocardiographic voltage and geometric patterns of left ventricular hypertrophy in patients with essential hypertension. Hypertens Res. 1998;21(4):259‐266. [DOI] [PubMed] [Google Scholar]
- 18. Porthan K, Niiranen TJ, Varis J, et al. ECG left ventricular hypertrophy is a stronger risk factor for incident cardiovascular events in women than in men in the general population. J Hypertens. 2015;33(6):1284‐1290. [DOI] [PubMed] [Google Scholar]
- 19. Lang RM, Badano LP, Mor‐Avi V, et al. Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. Eur Heart J Cardiovasc Imaging. 2015;16(3):233‐270. [DOI] [PubMed] [Google Scholar]
- 20. Sharma S, Drezner JA, Baggish A, et al. International recommendations for electrocardiographic interpretation in athletes. J Am Coll Cardiol. 2017;69(8):1057‐1075. [DOI] [PubMed] [Google Scholar]
- 21. Salinero JJ, Soriano ML, Ruiz‐Vicente D, et al. Respiratory function is associated to marathon race time. J Sports Med Phys Fitness. 2016;56(12):1433‐1438. [PubMed] [Google Scholar]
- 22. Tiller NB. Pulmonary and respiratory muscle function in response to marathon and ultra‐marathon running: a review. Sports Med. 2019;49(7):1031‐1041. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Sugita S, Takada K, Takada H, et al. The relationship between R amplitude in lead V5 (RV5) and left ventricular mass in the groups of adolescent subjects classified by body composition. Jpn Circ J. 1998;62(12):893‐899. [DOI] [PubMed] [Google Scholar]