ECG parameters to Detect Cardiac Involvement in Fabry Disease Original Articles

ECG parameters to Detect Cardiac Involvement in Fabry Disease Original Articles | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article ECG parameters to Detect Cardiac Involvement in Fabry Disease Original Articles Yu Wang, Jie Kong, Jun Wang, Ru Zhao, Heng Wang, Jing-Fen Zhu, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7384760/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background Cardiac involvement of the disease is a leading cause of death and disability in Fabry disease characterized by pathological accumulation of globotriaosylceramide (Gb3) and lyso-globotriaosylceramide (lyso-Gb3) in multiple organs. In this study, we sought to investigate the electrocardiographic (ECG) changes in different clinical stages and evaluate the value of these parameters in assessing cardiac involvement. Methods 62 patients with Fabry disease and 45 healthy controls were recruited in this study. ECG assessment, echocardiographic assessment and cardiac magnetic resonance (CMR) were recorded at rest in the same day. We defined 4 clinical stages of Fabry disease cardiomyopathy according to echocardiographic assessment and CMR: Pre-detectable stage, Non-hypertrophic stage, Hypertrophic and pre-fibrotic stage as well as Hypertrophic and fibrotic stage. Results Our results showed that Tp-e/QT was significantly decreased and Sokolow-Lyon index was markedly increased following the development of disease. QRS width and Tp-e/QT was associated with the severity of cardiac involvement in Fabry disease. Conclusions Our results demonstrated that QRS width and Tp-e/QT were associated with the severity of cardiac involvement in patients with Fabry disease and contributed to define the optimal intervention timepoint and assess the severity of cardiac involvement and response to disease-specific therapies. Electrocardiograph Cardiomyopathy Echocardiograph Fabry Disease Figures Figure 1 Figure 2 Figure 3 Background Fabry disease is a X-linked lysosomal storage disorder characterized by pathogenic variants in the galactosidase-α (GLA) gene, deficiency α-galactosidase A activity and abnormal accumulation of globotriaosylceramide (Gb3) and globotriaosylsphingosine (lyso-Gb3). 1 Progressive accumulation of Gb3 and lyso-Gb3 in the cardiac, vascular, renal, neural, ocular, aural or skin tissues leads to activated immune system and increased fibrosis in these organs, culminating in multisystem dysfunction. Nowadays, cardiac involvement is the leading cause of death and disability worldwide. Recent studies showed that except for accumulation of Gb3 and lyso-Gb3 in nearly all cardiac cells, increased myocardial inflammation, microvascular dysfunction as well as myocardial fibrosis contributed to the development of Fabry disease. 2 – 3 Despite a wide spectrum of promising therapies currently available, the therapeutic efficacy of these treatments is insufficient to reverse cardiac damage. 4 – 7 During the last decades, enzyme replacement therapy and chaperone therapy have been approved for Fabry disease-specific treatment and substrate reduction therapy as well as gene therapies are under clinical translation. 7 With recent advance achieved in Fabry disease-specific therapies, studies on defining the progression of Fabry disease and evaluating treatment response are of paramount important in this field. Currently, echocardiographic assessment and cardiovascular magnetic resonance (CMR) are the key tools to assess cardiac involvement of Fabry disease. The typical echocardiographic changes include concentric left ventricular hypertrophy, reduced global longitudinal strain, disproportionate hypertrophy of papillary muscles and thickened right ventricular walls without functional impairment. 7 – 8 CMR has been widely applied in differential diagnosis and staging of cardiac involvement in Fabry disease. Low native T1 and late gadolinium enhancement (LGE) are two common features of CMR in Fabry disease. 7 , 9 Prior studies showed that a wide spectrum of electrocardiographic (ECG) changes were detected in cardiac Fabry disease patients including short PR interval, reduced P wave duration, increased QRS duration, high QRS voltages, fractionated QRS, altered atrial depolarization and ventricular repolarization, ST-T segment depression and T-wave inversion in the inferolateral and precordial leads. 7 , 9 – 11 Most of these studies focused on early recognition of pre-clinical Fabry disease. 10 – 11 A lack of study described ECG changes in different stages of Fabry disease and the correlation of these changes with echocardiographic parameters and CMR parameters. It is of great interest to investigate whether there are any typical features of ECG changes in the development of Fabry disease and whether these changes are associated with severity of Fabry disease. In the current study, we sought to investigate the ECG changes in different stages of Fabry disease and the value of these parameters in evaluating the progression of Fabry disease. Methods Study patients 62 patients with Fabry disease and 45 healthy controls were included in current study. All Fabry disease patients were confirmed by genetic detection of GLA mutation with or without reduced α-galactosidase A activity. The inclusion criteria were as follows: 1. Genetic analysis confirmed Fabry disease patients; 2. Fabry disease patients received ECG examination, echocardiographic assessment with or without CMR assessment. The exclusion criteria were as follows: 1. Patients under the age of 18; 2. Patients received Fabry disease-specific therapies; 3. Patients with coronary artery disease or chronic ischemic heart disease; 4. Patients with a history of cardiac surgery or cardiac arrhythmia ablation; 5. Patients with pacemaker implantation. The healthy controls that without any medical history of cardiovascular disease and free of medical treatment were also received ECG examination and echocardiographic assessment at the same day. The basic characteristics recorded included gender, age, systolic and diastolic blood pressure, body surface area (BSA), GLA variant, activity of α-galactosidase A and serum level of lyso-Gb3. ECG analysis Twelve-lead ECG examination was performed at rest with recording at a sweep of 25mm/s and an amplitude of 1mV/10mm (GE Healthcare, MAC 2000 Electrocardiograph) and analyzed manually with the aid of calipers for all parameters by two experts (Y.W. and J.K.) blinded to clinical status, echocardiographic assessment and CMR assessment. Heart rate (HR), P wave and AV conduction Heart rate was recorded by calculating 60 divided by the average of R-R interval. Duration of P wave, PR interval and Pe-Q interval were recorded in lead II. Duration of P wave was measured from the beginning of P wave to the end of P wave and PR interval was measured from the beginning of P wave to the beginning of QRS wave. To better describing AV conduction, Pe-Q interval was measured from the end of P wave to the beginning of QRS wave. QRS complex Form Duration of QRS wave was recorded in lead II and measured from the beginning of QRS complex to the end of QRS complex. The presence of delta wave at the beginning of QRS complex, left bundle block (LBBB), right bundle branch block (RBBB) and fractionated QRS were recorded. Sokolow-Lyon index was employed to detect left ventricular hypertrophy. In brief, Sokolow-Lyon index was calculated by S wave voltage in V1 plus R wave voltage in V5 or V6 (which larger). The left ventricular hypertrophy (LVH) positive criteria were 3.5mV for female and 4.0mV for male. T wave and ST segment The presence of negative or biphasic T wave in lead II or lead V5, ST segment depression in lead II or lead V5 or U wave in lead V1-V6 were recorded. The time interval from the peak of T wave to the end of T wave (Tp-e) was recorded in lead II or lead V5 (which T wave was larger). The peak was measured from the nadir of the T wave in case of negative or biphasic T wave. Duration of QT interval was recorded and corrected by heart rate. The ratio of Tp-e and QT interval was also calculated and recorded. Echocardiographic analysis Standardized transthoracic echocardiographic assessment was performed using a GE Vivid E95 echocardiographic system (GE Vingmed Ultrasound AS, Horten, Norway) with a 3.5-MHz phased-array transducer and off-line analysis was conducted using the EchoPAC system (GE Healthcare) by two experts (J.-L. F. and H.W.) independently, blinded to clinical status, ECG assessment and CMR. All measurement were conducted in accordance with American Society of Echocardiography and the European Association of Cardiovascular Imaging guidelines. 12 Inter-ventricular septal dimension at end-diastole (IVSd), posterior wall thickness (PWT), left ventricular ejection fraction (LVEF), left ventricular end-diastolic dimension (LVEDD) and left ventricular end-systolic dimension (LVESD) were recorded in the parasternal long-axis and short-axis views. Left ventricular mass was calculated based on the following formula: LV mass = 0.8*1.04*[(IVSd + LVEDD + PWT) 3 - LVEDD 3 ] + 0.6 and LV mass index (LVMI) was represented as LV mass divided by BSA (BSA = 0.0057*Height + 0.0121*Weight + 0.0882 for male or BSA = 0.0073*Height + 0.0127*Weight – 0.2106 for female). The LVEF was measured using the biplane method. Additionally, two-dimensional speckle tracking echocardiography (2D-STE) was performed offline with EchoPAC software (GE Healthcare) to evaluate the global longitudinal strain (GLS) of the LV. GLS was derived using a 17-segment model, averaging strain values from the apical four-chamber, two-chamber, and three-chamber views, with an emphasis on peak systolic strain values. CMR assessment All participants underwent standard CMR on a 3.0T scanner (MAGNETOM Skyra, Siemens Healthcare, Erlangen, Germany) using an anterior 18-channel phased-array surface coil. The LGE images were visually analyzed for the presence or absence of enhancement by two experts (J. W. and J.-F. Z.) independently, blinded to clinical status, ECG assessment and echocardiographic analysis. Native T1 mapping (3 short-axis images, including basal, mid-ventricular, and apical) were acquired using the shortened modified look-locker inversion recovery sequence (shMOLLI) in 11 cardiac cycles with varying inversion times. Then the images were transferred to a dedicated research software package (CVI42 v5.11.3, Circle Cardiovascular Imaging, Alberta, Canada) to create parametric T1 maps and corresponding values. All the analysis was conducted following the recommendations of the Society for Cardiovascular Magnetic Resonance. 13 In current study, 55 patients received CMR assessment. Among these patients, LGE images analysis were not performed in eleven patients due to their reluctance or contrast contraindication. Clinical Staging To analyze the ECG changes in different clinical stage, we defined 4 stages of Fabry disease cardiomyopathy according to echocardiographic assessment and CMR results. Pre-detectable stage: Fabry disease patients with normal native T1 value, normal LVMI and negative LGE; Non-hypertrophic stage: Fabry disease patients with low native T1 value, normal LVMI and negative LGE; hypertrophic and pre-fibrotic stage: Fabry disease patients with hypertrophic ventricle and negative LGE; Hypertrophic and Fibrotic stage: Fabry disease patients with positive LGE. We defined hypertrophic ventricle according to LVMI (male: LVMI > 115; female: LVMI > 95). Statistical analysis All data were analyzed by SPSS Statistics (version 27.0, IBM Corporation, Armonk, NY, USA). The results are presented as the mean ± standard error of the mean (SEM) (continuous variables and normally distribution), the median and interquartile ranges (continuous variables and abnormally distribution) or frequencies of patients with percentages (discrete variables). Kolmogorov-Smirnov test and visual Q-Q plots assessment were adopted for normal distribution test. Reproducibility analysis of ECG data was adopted using intraclass correlation coefficients. Our results showed interobserver variability of ECG parameters was good ( Supplemental Table 1 ). Parametric continuous variables were evaluated using independent Students’ t-test or Mann-Whitney U test as appropriate. Categorical variables were evaluated using Pearson’s chi-square test or Fisher’s exact test. Bivariate correlation analysis was performed using the Pearson correlation coefficient or Spearman’s rank correlation coefficient. For multiple groups analysis, one-way ANOVA with Tukey post hoc test or Kruskal-Wallis test with Bonferroni post hoc test were adopted as appreciate. A two-sided p < 0.05 was regarded as a significant difference. Linear regression analysis was adopted to assess the correlation between ECG parameters and GLS or LVMI. Demographics (age and gender) and all the ECG parameters were included in the univariate analysis and significant factors in univariable analysis were selected for the following multivariate model and inputted using an “stepwise” method. Receiver-operator characteristics (ROC) was adopted to test the performance of parameters in the final multivariate linear regression model to assess the degree of cardiac involvement. Logistic regression analysis was adopted to assess the correlation between ECG parameters and Low T1 or LGE positive in CMR. Demographics (age and gender) and all the ECG parameters were included in the univariate analysis and significant factors in univariable analysis were selected for the following multivariate model and inputted using an “stepwise” method. Results Patient characteristics In this study, sixty-two Fabry disease patients and forty-five healthy controls were recruited (Table 1 ). The percentage of female (35% vs. 27%, p > 0.05), age (40.5 years vs. 43 years, p > 0.05), systolic blood pressure (121mmHg vs. 118mmHg, p > 0.05) and diastolic blood pressure (78mmHg vs. 72mmHg, p > 0.05) were similar between Fabry disease and Control groups. For ECG analysis, compared with control group, decreased PR interval, Pe-Q interval and Tp-e/QT as well as increased QRS width, percentage of Delta wave, Sokolow-Lyon index, percentage of fractionated QRS and percentage of U wave were observed in Fabry disease group (all p < 0.05). There was no significant difference on heart rate, P wave width, percentage of atrial fibrillation, percentage of LBBB or RBBB and duration of QTc between control and Fabry disease groups. For echocardiographic analysis, compared with control group, increased ventricular wall thickness and LVMI were detected in Fabry disease group (all p < 0.05) and lower GLS was also observed in Fabry disease group (p < 0.05). LVEF, LVEDD and LVESD were similar between these two groups. Moreover, 56.36% patients were observed low native T1 value and 38.64% patients showed positive LGE in Fabry disease group. Table 1 The characteristics of patients. Variable Control (n = 45) Fabry Disease (n = 62) p Female, n (%) 27 (60.00%) 35 (56.45%) 0.714 Age (years) 43 (36.5, 50.5) 40.5 (33.75, 51.25) 0.270 SBP (mmHg) 118 (108, 128.5) 121 (113.5, 134.5) 0.391 DBP (mmHg) 72 (68, 82) 78 (71, 86) 0.153 Electrocardiographic Data HR (bpm) 67 (63, 80.5) 68 (60.5, 78) (n = 59) 0.143 P wave width (msec) 102.47 ± 1.37 99.31 ± 1.74 (n = 59) 0.155 PR interval (msec) 156.16 ± 2.77 139.49 ± 3.12 (n = 59) < 0.001 Pe-Q interval (msec) 53.69 ± 2.76 40.19 ± 2.04 (n = 59) < 0.001 Atrial fibrillation (%) 0 (0.00%) 3 (0.05%) 0.262 QRS width (without LBBB or RBBB) (msec) 90 (88, 93) (n = 43) 92 (86, 106) (n = 58) 0.020 Delta wave (%) 0 (0.00%) 6 (10.17%) 0.035 LBBB (%) 0 (0.00%) 1 (0.02%) 1.000 RBBB (%) 2 (0.04%) 3 (0.05%) 1.000 QTc (msec) 424.33 ± 3.99 428.69 ± 4.11 (n = 59) 0.458 Tp-e/QT 0.24 ± 0.01 0.19 ± 0.00 < 0.001 Sokolow-Lyon index (mV) 2.0 (1.51. 2.50) 3.38 (2.65, 4.93) < 0.001 fQRS (%) 8 (17.78%) 26 (41.94%) 0.008 U wave (%) 0 (0.00%) 18 (29.03%) < 0.001 Echocardiographic Data LVEF (%) 64.29 ± 0.67 64.27 ± 0.62 0.987 IVS (mm) 9 (8, 9) 13 (10, 15.5) < 0.001 PWT (mm) 8 (8, 9) 11 (9, 14) < 0.001 LVEDD (mm) 46 (43, 48) 45 (43, 49) 0.957 LVESD (mm) 30 (28, 32) 30 (28, 32) 0.987 LVMI 70.57 (63.36, 76.20) 109.16 (84.43, 160.80) < 0.001 GLS (%) -22.09 ± 0.34 -16.75 ± 0.65 < 0.001 CMR Data Low T1 (%) - 31/55 (56.36%) - LGE (%) - 17/44 (38.64%) - Gene mutations and activity of enzyme All Fabry disease patients under gene mutation analysis, activation of α-galactosidase A test and detection of the level of lyso-Gb3. Patients with pathogenic variant under gene analysis and patients with uncertain variant together with reduced α-galactosidase A activation as well as elevated lyso-Gb3 level were diagnosed as Fabry disease. The mutations and types of variants in Fabry disease patients were listed in Supplemental Fig. 2 . To determine whether the activation of α-galactosidase A and the serum lyso-Gb3 level were associated the severity of cardiac involvement in Fabry disease, the correlation analysis between α-galactosidase A or globotriaosylsphingosine with GLS, LVMI, Low T1 or LGE were performed. Our results showed that the activation of enzyme and accumulation of lyso-Gb3 were only corelated with low native T1 value ( Supplemental Table 3 ). Activation of enzyme and accumulation of lyso-Gb3 have been well documented to be associated with the severity of the Fabry disease. Nonetheless, increased myocardial inflammation and fibrosis as well as microvascular dysfunction were all the key factors to assess the cardiac involvement in Fabry disease. Therefore, we performed this study to better describe the progression of Fabry disease in the heart. ECG findings in different clinical stages The echocardiographic, MRI and ECG characteristics in different clinical stages were shown in Fig. 1 . To determine the ECG changes in different clinical stages, we summarized the ECG parameters based on different clinical stages in Table 2 and Fig. 2 . Our results showed that no significant difference on P wave width, Pe-Q interval or QRS width was observed between different clinical stages (Fig. 2 A-C). The duration of QTc markedly reduced in Non-hypertrophic stage compared with Hypertrophic and pre-fibrotic stage as well as Hypertrophic and fibrotic stage. There was no significant difference on the duration of QTc between Control group, Pre-detectable, Hypertrophic and pre-fibrotic as well as Hypertrophic and fibrotic stages (Fig. 2 D). Compared with control group, Tp-e/QT significant decreased in Hypertrophic and pre-fibrotic as well as Hypertrophic and fibrotic stages. There was no significant difference between Control group, Pre-detectable and Non-hypertrophic stages (Fig. 2 E). Compared with Control group, Sokolow-Lyon index significantly increased in Non-hypertrophic, Hypertrophic and pre-fibrotic as well as Hypertrophic and fibrotic stages (all p < 0.05, Fig. 2 F). In addition, Sokolow-Lyon index in Hypertrophic and pre-fibrotic stage was higher than Pre-detectable stage (p < 0.05, Fig. 2 F). Table 2 The ECG findings of patients. Variable Control (n = 45) Pre-detectable stage (n = 6) Non-hypertrophic stage (n = 15) Hypertrophic and pre-fibrotic stage (n = 6) Hypertrophic and Fibrotic stage (n = 17) P wave width (msec) 102.47 ± 1.37 103.17 ± 6.74 99.87 ± 2.93 93.50 ± 4.34 98.63 ± 3.64 PR interval (msec) 156.16 ± 2.77 149.67 ± 11.71 141.20 ± 4.88 128.00 ± 10.25 138.31 ± 7.08 Pe-Q interval (msec) 53.69 ± 2.76 46.50 ± 6.99 41.33 ± 3.70 34.50 ± 6.09 39.69 ± 4.40 QRS width (msec) 92 (88, 97) 91 (84, 96) 90 (82, 102) 100 (93, 113) 104 (86, 120) Delta wave (%) 0 (0.00%) 0 (0.00%) 1 (6.67%) 2 (33.33%) 2 (11.76%) LBBB (%) 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) 1 (5.88%) RBBB (%) 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) 1 (5.88%) QTc (msec) 424.33 ± 3.99 431.67 ± 6.90 402.80 ± 7.38 447.50 ± 9.75 436.13 ± 8.31 Tp-e/QT 0.24 ± 0.01 0.23 ± 0.02 0.21 ± 0.01 0.17 ± 0.02 0.18 ± 0.00 Sokolow-Lyon index (mV) 2.00 (1.51. 2.50) 2.37 (1.85, 2.80) 3.29 (2.59, 4.11) 5.94 (4.88, 7.13) 2.91 (2.75, 5.51) II ST depression (%) 0 (0.00%) 1 (16.67%) 3 (20.00%) 4 (66.67%) 9 (52.94%) II negative or biphasic T (%) 0 (0.00%) 1 (16.67%) 1 (6.67%) 5 (83.33%) 10 (58.82%) V5 ST depression (%) 0 (0.00%) 1 (16.67%) 2 (13.33%) 5 (83.33%) 6 (35.29%) V5 negative or biphasic T (%) 0 (0.00%) 1 (16.67%) 2 (13.33%) 5 (83.33%) 11 (64.71%) fQRS (%) 8 (17.78%) 1 (16.67%) 6 (40.00%) 1 (16.67%) 8 (47.06%) U wave (%) 0 (0.00%) 0 (0.00%) 1 (6.67%) 5 (83.33%) 5 (29.41%) Determinants of cardiac involvement Echocardiographic parameters including GLS and LVMI as well as CMR parameters including low native T1 value and LGE are widely used to evaluate cardiac involvement and disease progression. To determine which ECG change was associated with cardiac involvement and disease progression of Fabry disease, bivariate correlation analysis, univariate and multivariate analysis were performed between ECG parameters and GLS, LVMI, low native T1 value or LGE. Our results showed that gender, age, Tp-e/QT, QRS width, ST segment depression or negative or biphasic T wave in lead II or lead V5, Sokolow-Lyon index and U wave were significantly associated with GLS in the correlation coefficient analysis and univariate model (Table 3 ). Nonetheless, in multivariate model, gender, age, Tp-e/QT, QRS width and Sokolow-Lyon index were significantly related to GLS (Table 3 ). The final multivariate model was showed in Fig. 3 A and Supplemental Table 4 . Moreover, our results demonstrated that gender, age, Tp-e/QT, QRS width, ST segment depression or negative or biphasic T wave in lead II or lead V5, Sokolow-Lyon index and U wave were also significantly associated with LVMI in the correlation coefficient analysis and univariate model (Table 4 ). Nevertheless, in multivariate analysis, gender, Tp-e/QT, QRS width were associated with LVMI (Table 4 ). The final multivariate model was showed in Fig. 3 B and Supplemental Table 4 . To assess the robustness of these changes, the significant factors in multivariate models were computed in ROC curve analysis. A ROC curve of Tp-e/QT had the best discriminative ability in both ROC curve analysis of GLS and ROC curve analysis of LVMI with area under the curve (AUC) 0.83 and 0.82 respectively (Fig. 3 C-D) Table 3 Predictors for GLS. Variable Correlation Coefficient analysis Univariate analysis Multivariate analysis R P B P B P Gander (Female) -0.294 0.021 -2.923 0.025 -2.609 0.003 age 0.479 < 0.001 0.220 < 0.001 0.107 0.014 P wave width -0.049 0.712 -0.018 0.712 Pe-Q interval -0.155 0.242 -0.048 0.242 Tp-e/QT -0.574 < 0.001 -85.408 < 0.001 -35.818 0.011 QRS width 0.582 < 0.001 0.186 < 0.001 0.109 < 0.001 II ST depression 0.479 < 0.001 4.701 < 0.001 II negative or biphasic T 0.517 < 0.001 5.108 < 0.001 fQRS 0.188 0.143 1.649 0.215 Sokolow-Lyon index 0.495 < 0.001 1.447 < 0.001 0.710 0.006 V5 ST depression 0.453 < 0.001 4.655 < 0.001 V5 negative or biphasic T 0.569 < 0.001 5.732 < 0.001 U wave 0.384 0.002 4.564 0.001 Table 4 Predictors for LVMI. Variable Correlation Coefficient analysis Univariate analysis Multivariate analysis R P B P B P Gander (Female) -0.299 0.018 -42.704 0.014 -36.644 0.002 age 0.561 < 0.001 2.694 < 0.001 P wave width -0.009 0.943 -0.564 0.407 Pe-Q interval -0.161 0.224 -0.852 0.138 Tp-e/QT -0.581 < 0.001 -977.959 < 0.001 -559.648 0.002 QRS width 0.570 < 0.001 2.769 < 0.001 2.343 < 0.001 II ST depression 0.468 < 0.001 49.402 < 0.001 II negative or biphasic T 0.519 < 0.001 56.855 < 0.001 fQRS 0.208 0.104 33.453 0.058 Sokolow-Lyon index 0.429 < 0.001 13.558 0.006 V5 ST depression 0.440 < 0.001 43.972 0.012 V5 negative or biphasic T 0.585 < 0.001 65.393 < 0.001 U wave 0.367 0.003 45.761 0.016 Next, in correlation coefficient analysis, gender and Sokolow-Lyon index were associated with low native T1 value (Table 5 ). Nonetheless, no ECG parameter was significantly related to low native T1 value (Table 5 ). Age, Tp-e/QT, negative and biphasic T wave in lead II or lead V5 were associated with LGE positive in correlation coefficient analysis (Table 6 ). Age, Tp-e/QT, QRS width, negative and biphasic T wave in lead II or lead V5 were associated with LGE positive in univariate analysis (Table 6 ). Nevertheless, none of ECG parameters was significantly related to LGE positive in multivariate analysis (Table 6 ). Table 5 Predictors for Low T1. Variable Correlation Coefficient analysis Univariate analysis Multivariate analysis R P Exp(B)(95%CI) P Exp(B)(95%CI) P Gander (Female) -0.405 0.002 0.166 (0.049–0.564) 0.004 6.017 (1.773–20.416) 0.004 age -0.086 0.535 0.985 (0.941–1.031) 0.512 P wave width 0.041 0.771 1.002 (0.961–1.044) 0.926 Pe-Q interval -0.025 0.863 0.998 (0.963–1.034) 0.900 Tp-e/QT 0.136 0.321 1307.154 (0.000-7.805*10 9 ) 0.367 QRS width -0.064 0.644 0.986 (0.954–1.018) 0.390 II ST depression -0.030 0.828 0.884 (0.298–2.621) 0.824 II negative or biphasic T -0.146 0.288 0.550 (0.185–1.631) 0.281 fQRS 0.012 0.929 1.053 (0.351–3.155) 0.927 Sokolow-Lyon index 0.281 0.038 1.321 (0.938–1.860) 0.111 V5 ST depression 0.012 0.929 1.053 (0.351–3.155) 0.927 V5 negative or biphasic T -0.121 0.377 0.611 (0.209–1.789) 0.369 U wave -0.001 0.992 0.994 (0.307–3.211) 0.991 Table 6 Predictors for LGE. Variable Correlation Coefficient analysis Univariate analysis Multivariate analysis R P Exp(B)(95%CI) P Exp(B)(95%CI) P Gander (Female) 0.091 0.559 0.682 (0.195–2.383) 0.549 age 0.495 < 0.001 1.106 (1.034–1.184) 0.003 1.106 (1.034–1.184) 0.003 P wave width 0.021 0.892 0.997 (0.950–1.045) 0.891 Pe-Q interval 0.004 0.980 0.995 (0.956–1.035) 0.796 Tp-e/QT -0.340 0.024 0.000 (0.000-0.513) 0.043 QRS width 0.247 0.106 1.041 (1.000 -1.084) 0.048 II ST depression 0.233 0.128 2.672 (0.757–9.426) 0.127 II negative or biphasic T 0.329 0.029 4.082 (1.119–14.883) 0.033 fQRS 0.176 0.252 2.111 (0.598–7.448) 0.245 Sokolow-Lyon index 0.055 0.722 1.100 (0.781–1.548) 0.585 V5 ST depression 0.059 0.703 1.295 (0.356–4.720) 0.695 V5 negative or biphasic T 0.345 0.022 4.354 (1.195–15.865) 0.026 U wave 0.081 0.602 1.458 (0.366–5.812) 0.593 Taken together, our results demonstrated that Tp-e/QT, QRS width and Sokolow-Lyon index were associated with GLS and Tp-e/QT and QRS width were associated with LVMI. Moreover, Tp-e/QT had the best ability to discriminate patients with impaired GLS or increased LVMI from normal controls. Discussions Main findings In this study, we summarized the ECG changes in different clinical stages of Fabry disease. Our results showed that compared with Control group, decreased PR interval, Pe-Q interval and Tp-e/QT as well as increased QRS width, delta wave, Sokolow-Lyon index, fractionated QRS wave and U wave were observed in Fabry disease group. Following the progression of cardiac involvement, Tp-e/QT progressively decreased whereas Sokolow-Lyon index gradually increased from Pre-detectable stage to Hypertrophic and pre-fibrotic stage and tended to reduce in Hypertrophic and fibrotic stage. In addition, our results provide the proof-of-principle evidence the Tp-e/QT, QRS width and Sokolow-Lyon index were associated with GLS and LVMI. Tp-e/QT had the best discrimination ability in clinical staging. Clinical Stage In this study, we define cardiac involvement of Fabry disease into four stages: Pre-detectable stage, Non-hypertrophic stage, Hypertrophic and pre-fibrotic stage as well as Hypertrophic and fibrotic stage. Previous study defined cardiac involvement into four stages, including non-hypertrophic, hypertrophic-pre-fibrotic, hypertrophic-fibrotic and overt dysfunction stage 14 . Nevertheless, recent studies showed that earlier detection of Fabry disease and earlier beginning of Fabry disease-specific therapies could benefit the progression of cardiac involvement of Fabry disease. Therefore, we included a pre-detectable stage in our study. As few Fabry disease patients with severe systolic dysfunction or diastolic dysfunction in our study, we did not include an overt dysfunction stage in current study. Recent studies showed that lysosomal storage was insufficient to represent the severity of cardiac involvement as cardiac inflammation and fibrosis were all contributed to cardiac involvement of Fabry disease 7 , 11 , 14 . Therefore, we did not include lysosomal storage and activity of enzyme in staging of Fabry disease. In this study, we defined cardiac involvement of Fabry disease mainly according to the results of echocardiographic assessment and CMR. Previous study showed that RBBB, Sokolow-Lyon index and repolarization abnormalities were associated with ventricular hypertrophy 15 . Nonetheless, our result showed that repolarization abnormalities and QRS width were associated with ventricular hypertrophy. Ventricular fibrosis in patients with Fabry disease might lead to a decrease in Sokolow-Lyon index. Previous study demonstrated that Sokolow-Lyon index, ratio between P-wave and PR-segment duration, QRS width and QRS duration were predictors of low T1 value 16 . In our study, there was no ECG parameter associate with low T1 value. The T1 values of some Fabry disease patients with increased LVMI, decreased GLS and LGE positive were normal. Increased myocardial inflammation and fibrosis might influence the T1 value. Therefore, in this study, we sought to investigate whether any ECG changes could be detected prior to appearance of echocardiographic and CMR changes. Fortunately, there was no significant difference on ECG parameters between Control and Pre-detected stage in current study. Prior study showed decreased P wave duration and Pe-Q interval in pre-hypertrophic Fabry disease patient with normal T1 compared with control 9 . Nonetheless, in our study, the duration of P wave was similar between Control and Pre-detectable stage. Although a decreasing tendency of Pe-Q interval was observed in Pre-detectable stage compared with control group, no statistic difference was detected. Augusto JB, et al. included Fabry disease patients with or without Fabry disease-specific therapies in their study and only two groups including pre-hypertrophy with normal native T1 and pre-hypertrophy with low T1 groups were included in their study 9 . Nevertheless, only Fabry disease patients without any Fabry disease-specific therapies was recruited in our studies and both pre-hypertrophic as well as hypertrophic and fibrotic patents was included in current study. Whether any ECG changes could be detected prior to echocardiographic and CMR detections remains unclear. Future studies can be launched to explore different ECG changes in different clinical staging. The ECG parameters related with cardiac involvement of Fabry disease Cardiac involvement of Fabry disease starts prior to the appearance of clinical symptoms. Previous studies demonstrated that LVMI, GLS, native T1 value and LGE were associated with the progression of cardiac involvement 7 . Interesting, we performed correlation coefficient analysis between the activity of α-galactosidase A and the serum level of Gb3 with GLS, LVMI, Low T1 and LGE. Only low native T1 value was associated with decreased activity of α-galactosidase A and increased serum level of Gb3. Accumulation of Gb3, microvascular dysfunction, myocardial inflammation and cardiac fibrosis are all involved in progression of cardiac involvement of Fabry disease 7 . That is why Fabry disease-specific therapies targeting on the activity of enzyme has limited effect on cardiac involvement and why only echocardiographic assessment or CMR is insufficient to define cardiac involvement of Fabry disease. Therefore, studies on ECG parameters in Fabry disease is of parameter important to define the progression of cardiac changes and evaluate cardiac response to Fabry disease-specific therapies. Prior studies demonstrated that short Pe-Q interval, high QRS voltages and pathological repolarization contributed to the diagnosis of Fabry disease 7 , 10 . Consistent with previous studies, reduced Pe-Q interval and Tp-e/QT as well as increased QRS width and Sokolow-Lyon index were detected in Fabry disease patients in our study. Moreover, increased presence of delta wave, fractionated QRS wave and U wave were also observed in Fabry disease patients. To better describe the progression of cardiac involvement in Fabry disease, we sought to investigated which ECG parameters were relevant to cardiac involvement of Fabry disease. Correlation coeffective analysis was performed between parameters mentioned above and ECG changes. Our results showed that Tp-e/QT, Sokolow-Lyon index and QRS width were associated with GLS whereas Tp-e/QT and QRS width were associated with LVMI. The area under curve (AUC) showed that Tp-e/QT was the best ECG parameters to predict impaired GLS and increased LVMI. As the CMR parameters in different cardiovascular center is different, we define low native T1 value and LGE positive according to the recommendation commercially available. Unfortunately, our results demonstrated that there was no significant difference between ECG parameters and CMR parameters. Prior studies demonstrated that progressive accumulation of Gb3 and lyso-Gb3 in AV node resulted in accelerated AV conduction and reduced Pe-Q interval 11 , 17 . As cardiac involvement progressed, increased cardiac inflammation and fibrosis decreased AV conduction, culminating in normal Pe-Q interval even AV blockage 11 . That is why short Pe-Q interval was observed in Fabry disease patients, whereas no significant relationship was detected between the severity of cardiac involvement and Pe-Q interval. Recent studies discussed the value of echocardiographic assessment and CMR in evaluation of cardiac damage of Fabry disease 18 , 19 . Our study demonstrated that Tp-e/QT and QRS width were of value in assessing cardiac damage and cardiac involvement in Fabry disease. Limitation First of all, this is a single center cross-sectional study. How ECG parameters changed during the development of Fabry disease was hypothesized rather than detected. Longitudinal studies would be helpful to confirm the ECG changes. Moreover, the small sample size in the Pre-detectable stage and Hypertrophic and pre-fibrotic stage limited the robustness of subgroup analysis. Secondly, Fabry disease patients without disease-specific therapies were recruited in our study. How disease-specific therapies influence the ECG changes remains unclear. Thirdly, native T2 value of CMR were not included in current study. Previous studies showed that native T2 value was associated with cardiac inflammation 20 , 21 . Further model could include native T1/T2 value, LGE, LVMI, GLS as well as ECG parameters, such as QRS width and Tp-e/QT to predict cardiac involvement and damage in patients with Fabry disease. Last but not least, our study showed that no significant difference on regular ECG assessment was observed between Pre-detectable stage and Non-hypertrophic stages. Holter examination which includes more ECG information would be benefit to detect subtle ECG changes in Pre-detectable stage and might be helpful in early diagnosis of Fabry disease. Conclusion This study summarized ECG changes in different stages of cardiac involvement of Fabry disease patients. QRS width and Tp-e/QT were associated with the severity of cardiac involvement in patients with Fabry disease. Future studies can be launched to investigate the value of these ECG parameters in defining the optimal intervention timepoint and assessing the severity of cardiac involvement and response to disease-specific therapies. Abbreviations AUC Area under curve BSA Body surface area CMR Cardiovascular magnetic resonance ECG electrocardiographic Gb3 Globotriaosylceramide GLA Galactosidase-α GLS Global longitudinal strain HR Heart rate IVSd Inter-ventricular septal dimension LBBB Left bundle branch block LGE Late gadolinium enhancement LV Left ventricle LVEDD Left ventricular end-diastolic dimension LVEF Left ventricular ejection fraction LVH Left ventricular hypertrophy LVMI Left ventricular mass index LVESD Left ventricular end-systolic dimension Lyso-Gb3 Globotriaosylsphingosine PWT Posterior wall thickness RBBB Right bundle branch block ROC Receiver-operator characteristics SEM Standard error of the mean Tp-e The peak of T wave to the end of T wave 2D-STE Two-dimensional speckle tracking echocardiography Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of the First Affiliated Hospital of Soochow University (2024 − 468). Patients were recruited in our cardiovascular center from January 2021 to June 2024 and Written informed consent was obtained from all patients. Consent for publication All the authors have agreed with manuscript well for its submission for BMC cardiovascular disorders. The manuscript has not been published and is not being considered for publication elsewhere in whole or in part in any language. Competing interests All authors have no conflict of interest. Funding This research was supported by the National Natural Science Foundation of China (82200283), the Scientific Research Project of Gusu Health Talents Program of Suzhou (GSWS2022017), the Innovation and Entrepreneurship Team in Jiangsu Province (JSSCT202353), the Multi-center Clinical Research Project for Major Diseases in Suzhou (DZXYJ202302). The funder had no roles in study design, data collection and analysis, decision to publish, or preparation of the manuscript. 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02:23:05","extension":"xml","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":162098,"visible":true,"origin":"","legend":"","description":"","filename":"305f81b0e24c400ea292f5d3898260fc1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7384760/v1/b1cd026b0db059369dce175a.xml"},{"id":93731107,"identity":"7b66f071-0dd2-4b46-9bac-777204581671","added_by":"auto","created_at":"2025-10-17 02:23:04","extension":"html","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":170914,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7384760/v1/91535a078015ae975a1e4976.html"},{"id":93731102,"identity":"529402f7-6a31-403b-9f66-949b273db0b2","added_by":"auto","created_at":"2025-10-17 02:23:04","extension":"tiff","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":722639,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClinical stages and electrocardiographic parameters in different clinical stages.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFabry disease patients were divided into 4 stages according to echocardiographic assessment and CMR. Pre-detectable stage: normal LVMI, normal T1 and LGE negative; Non-hypertrophic stage: low T1, normal LVMI and LGE negative; Hypertrophic and pre-fibrotic stage: increased LVMI and LGE negative; Hypertrophic and fibrotic stage: increased LVMI and LGE positive. Following the development of Fabry disease, reduced Pe-Q interval, negative or biphasic T waves in anterior and inferior leads, ST segment depression in anterior and inferior leads, increased QRS width, increased Sokolow-Lyon index and decreased Tp-e/QT were observed in patients with Fabry disease.\u003c/p\u003e","description":"","filename":"Figure1.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7384760/v1/38c282c79035dc7ad12f9771.tiff"},{"id":93731112,"identity":"c1db8083-a34f-493e-a5ec-b6d77b638944","added_by":"auto","created_at":"2025-10-17 02:23:05","extension":"tiff","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":194209,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eElectrocardiographic changes in the development of Fabry disease.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was no significant difference on P wave width, Pe-Q interval and QRS width between different stages (A-C). Compared with Hypertrophic and pre-fibrotic stage as well as Hypertrophic and fibrotic stage, a decreased QTc duration was observed in Non-hypertrophic stage (D). Compared with control group, a decreased Tp-e/QT was observed in Hypertrophic and pre-fibrotic stage as well as Hypertrophic and fibrotic stage (E). Compared with control group, Sokolow-Lyon index was significantly increased in Non-hypertrophic stage, Hypertrophic and pre-fibrotic stage as well as Hypertrophic and fibrotic stage (F). Moreover, Sokolow-Lyon index was higher in Hypertrophic and pre-fibrotic stage than that in Pre-detectable stage (F).\u003c/p\u003e","description":"","filename":"Figure2.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7384760/v1/d6822b6287f94a0c28de70c1.tiff"},{"id":93731103,"identity":"6e949a64-f7bd-4174-8c64-6f4b2a922b74","added_by":"auto","created_at":"2025-10-17 02:23:04","extension":"tiff","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":177359,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTp-e/QT and QRS width were associated with the severity of cardiac involvement.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTp-e/QT, QRS width and Sokolow-Lyon index were associated with GLS. Linear regression analysis showed that GLS=26.49-2.61*Gander+0.11*age-35.82*Tp-e/QT-0.11*QRS width+0.71*Sokolow-Lyon index (A). Tp-e/QT and QRS width were associated with LVMI. Linear regression analysis showed that LVMI=27.94-36.64*Gander-559.65*Tp-e/QT+2.34*QRS width (B). ROC curve analysis showed that the area under curve (AUC) of GLS were listed below: Tp-e/QT 0.83; Sokolow-Lyon index 0.81; QRS width 0.79 (C). ROC curve analysis showed that the AUC of LVMI were listed below: Tp-e/QT 0.82; QRS width 0.78 (D).\u003c/p\u003e","description":"","filename":"Figure3.tiff","url":"https://assets-eu.researchsquare.com/files/rs-7384760/v1/28afcd7e929cd8e932fa37a8.tiff"},{"id":93733141,"identity":"fae7b5ca-4095-4b1c-98b7-2be943072742","added_by":"auto","created_at":"2025-10-17 02:39:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2828004,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7384760/v1/75475363-d17e-47c9-864f-2005ec8bbf4a.pdf"},{"id":93731094,"identity":"90213a06-c358-491b-8a55-e94253f3853a","added_by":"auto","created_at":"2025-10-17 02:23:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":232507,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementalmaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7384760/v1/904b48515b0f116b599e37ef.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"ECG parameters to Detect Cardiac Involvement in Fabry Disease Original Articles","fulltext":[{"header":"Background","content":"\u003cp\u003eFabry disease is a X-linked lysosomal storage disorder characterized by pathogenic variants in the galactosidase-α (GLA) gene, deficiency α-galactosidase A activity and abnormal accumulation of globotriaosylceramide (Gb3) and globotriaosylsphingosine (lyso-Gb3).\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Progressive accumulation of Gb3 and lyso-Gb3 in the cardiac, vascular, renal, neural, ocular, aural or skin tissues leads to activated immune system and increased fibrosis in these organs, culminating in multisystem dysfunction. Nowadays, cardiac involvement is the leading cause of death and disability worldwide. Recent studies showed that except for accumulation of Gb3 and lyso-Gb3 in nearly all cardiac cells, increased myocardial inflammation, microvascular dysfunction as well as myocardial fibrosis contributed to the development of Fabry disease.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Despite a wide spectrum of promising therapies currently available, the therapeutic efficacy of these treatments is insufficient to reverse cardiac damage.\u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e During the last decades, enzyme replacement therapy and chaperone therapy have been approved for Fabry disease-specific treatment and substrate reduction therapy as well as gene therapies are under clinical translation. \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e With recent advance achieved in Fabry disease-specific therapies, studies on defining the progression of Fabry disease and evaluating treatment response are of paramount important in this field. Currently, echocardiographic assessment and cardiovascular magnetic resonance (CMR) are the key tools to assess cardiac involvement of Fabry disease. The typical echocardiographic changes include concentric left ventricular hypertrophy, reduced global longitudinal strain, disproportionate hypertrophy of papillary muscles and thickened right ventricular walls without functional impairment.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e CMR has been widely applied in differential diagnosis and staging of cardiac involvement in Fabry disease. Low native T1 and late gadolinium enhancement (LGE) are two common features of CMR in Fabry disease.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Prior studies showed that a wide spectrum of electrocardiographic (ECG) changes were detected in cardiac Fabry disease patients including short PR interval, reduced P wave duration, increased QRS duration, high QRS voltages, fractionated QRS, altered atrial depolarization and ventricular repolarization, ST-T segment depression and T-wave inversion in the inferolateral and precordial leads.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Most of these studies focused on early recognition of pre-clinical Fabry disease.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e A lack of study described ECG changes in different stages of Fabry disease and the correlation of these changes with echocardiographic parameters and CMR parameters. It is of great interest to investigate whether there are any typical features of ECG changes in the development of Fabry disease and whether these changes are associated with severity of Fabry disease. In the current study, we sought to investigate the ECG changes in different stages of Fabry disease and the value of these parameters in evaluating the progression of Fabry disease.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy patients\u003c/h2\u003e\u003cp\u003e62 patients with Fabry disease and 45 healthy controls were included in current study. All Fabry disease patients were confirmed by genetic detection of GLA mutation with or without reduced α-galactosidase A activity. The inclusion criteria were as follows: 1. Genetic analysis confirmed Fabry disease patients; 2. Fabry disease patients received ECG examination, echocardiographic assessment with or without CMR assessment. The exclusion criteria were as follows: 1. Patients under the age of 18; 2. Patients received Fabry disease-specific therapies; 3. Patients with coronary artery disease or chronic ischemic heart disease; 4. Patients with a history of cardiac surgery or cardiac arrhythmia ablation; 5. Patients with pacemaker implantation. The healthy controls that without any medical history of cardiovascular disease and free of medical treatment were also received ECG examination and echocardiographic assessment at the same day. The basic characteristics recorded included gender, age, systolic and diastolic blood pressure, body surface area (BSA), GLA variant, activity of α-galactosidase A and serum level of lyso-Gb3.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eECG analysis\u003c/h3\u003e\n\u003cp\u003eTwelve-lead ECG examination was performed at rest with recording at a sweep of 25mm/s and an amplitude of 1mV/10mm (GE Healthcare, MAC 2000 Electrocardiograph) and analyzed manually with the aid of calipers for all parameters by two experts (Y.W. and J.K.) blinded to clinical status, echocardiographic assessment and CMR assessment.\u003c/p\u003e\u003cp\u003eHeart rate (HR), P wave and AV conduction\u003c/p\u003e\u003cp\u003eHeart rate was recorded by calculating 60 divided by the average of R-R interval. Duration of P wave, PR interval and Pe-Q interval were recorded in lead II. Duration of P wave was measured from the beginning of P wave to the end of P wave and PR interval was measured from the beginning of P wave to the beginning of QRS wave. To better describing AV conduction, Pe-Q interval was measured from the end of P wave to the beginning of QRS wave.\u003c/p\u003e\u003cp\u003eQRS complex Form\u003c/p\u003e\u003cp\u003eDuration of QRS wave was recorded in lead II and measured from the beginning of QRS complex to the end of QRS complex. The presence of delta wave at the beginning of QRS complex, left bundle block (LBBB), right bundle branch block (RBBB) and fractionated QRS were recorded. Sokolow-Lyon index was employed to detect left ventricular hypertrophy. In brief, Sokolow-Lyon index was calculated by S wave voltage in V1 plus R wave voltage in V5 or V6 (which larger). The left ventricular hypertrophy (LVH) positive criteria were 3.5mV for female and 4.0mV for male.\u003c/p\u003e\u003cp\u003eT wave and ST segment\u003c/p\u003e\u003cp\u003eThe presence of negative or biphasic T wave in lead II or lead V5, ST segment depression in lead II or lead V5 or U wave in lead V1-V6 were recorded. The time interval from the peak of T wave to the end of T wave (Tp-e) was recorded in lead II or lead V5 (which T wave was larger). The peak was measured from the nadir of the T wave in case of negative or biphasic T wave. Duration of QT interval was recorded and corrected by heart rate. The ratio of Tp-e and QT interval was also calculated and recorded.\u003c/p\u003e\n\u003ch3\u003eEchocardiographic analysis\u003c/h3\u003e\n\u003cp\u003eStandardized transthoracic echocardiographic assessment was performed using a GE Vivid E95 echocardiographic system (GE Vingmed Ultrasound AS, Horten, Norway) with a 3.5-MHz phased-array transducer and off-line analysis was conducted using the EchoPAC system (GE Healthcare) by two experts (J.-L. F. and H.W.) independently, blinded to clinical status, ECG assessment and CMR. All measurement were conducted in accordance with American Society of Echocardiography and the European Association of Cardiovascular Imaging guidelines.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Inter-ventricular septal dimension at end-diastole (IVSd), posterior wall thickness (PWT), left ventricular ejection fraction (LVEF), left ventricular end-diastolic dimension (LVEDD) and left ventricular end-systolic dimension (LVESD) were recorded in the parasternal long-axis and short-axis views. Left ventricular mass was calculated based on the following formula: LV mass\u0026thinsp;=\u0026thinsp;0.8*1.04*[(IVSd\u0026thinsp;+\u0026thinsp;LVEDD\u0026thinsp;+\u0026thinsp;PWT)\u003csup\u003e3\u003c/sup\u003e - LVEDD\u003csup\u003e3\u003c/sup\u003e]\u0026thinsp;+\u0026thinsp;0.6 and LV mass index (LVMI) was represented as LV mass divided by BSA (BSA\u0026thinsp;=\u0026thinsp;0.0057*Height\u0026thinsp;+\u0026thinsp;0.0121*Weight\u0026thinsp;+\u0026thinsp;0.0882 for male or BSA\u0026thinsp;=\u0026thinsp;0.0073*Height\u0026thinsp;+\u0026thinsp;0.0127*Weight \u0026ndash; 0.2106 for female). The LVEF was measured using the biplane method. Additionally, two-dimensional speckle tracking echocardiography (2D-STE) was performed offline with EchoPAC software (GE Healthcare) to evaluate the global longitudinal strain (GLS) of the LV. GLS was derived using a 17-segment model, averaging strain values from the apical four-chamber, two-chamber, and three-chamber views, with an emphasis on peak systolic strain values.\u003c/p\u003e\n\u003ch3\u003eCMR assessment\u003c/h3\u003e\n\u003cp\u003eAll participants underwent standard CMR on a 3.0T scanner (MAGNETOM Skyra, Siemens Healthcare, Erlangen, Germany) using an anterior 18-channel phased-array surface coil. The LGE images were visually analyzed for the presence or absence of enhancement by two experts (J. W. and J.-F. Z.) independently, blinded to clinical status, ECG assessment and echocardiographic analysis. Native T1 mapping (3 short-axis images, including basal, mid-ventricular, and apical) were acquired using the shortened modified look-locker inversion recovery sequence (shMOLLI) in 11 cardiac cycles with varying inversion times. Then the images were transferred to a dedicated research software package (CVI42 v5.11.3, Circle Cardiovascular Imaging, Alberta, Canada) to create parametric T1 maps and corresponding values. All the analysis was conducted following the recommendations of the Society for Cardiovascular Magnetic Resonance.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e In current study, 55 patients received CMR assessment. Among these patients, LGE images analysis were not performed in eleven patients due to their reluctance or contrast contraindication.\u003c/p\u003e\n\u003ch3\u003eClinical Staging\u003c/h3\u003e\n\u003cp\u003eTo analyze the ECG changes in different clinical stage, we defined 4 stages of Fabry disease cardiomyopathy according to echocardiographic assessment and CMR results. Pre-detectable stage: Fabry disease patients with normal native T1 value, normal LVMI and negative LGE; Non-hypertrophic stage: Fabry disease patients with low native T1 value, normal LVMI and negative LGE; hypertrophic and pre-fibrotic stage: Fabry disease patients with hypertrophic ventricle and negative LGE; Hypertrophic and Fibrotic stage: Fabry disease patients with positive LGE. We defined hypertrophic ventricle according to LVMI (male: LVMI\u0026thinsp;\u0026gt;\u0026thinsp;115; female: LVMI\u0026thinsp;\u0026gt;\u0026thinsp;95).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eAll data were analyzed by SPSS Statistics (version 27.0, IBM Corporation, Armonk, NY, USA). The results are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of the mean (SEM) (continuous variables and normally distribution), the median and interquartile ranges (continuous variables and abnormally distribution) or frequencies of patients with percentages (discrete variables). Kolmogorov-Smirnov test and visual Q-Q plots assessment were adopted for normal distribution test. Reproducibility analysis of ECG data was adopted using intraclass correlation coefficients. Our results showed interobserver variability of ECG parameters was good (\u003cb\u003eSupplemental Table\u0026nbsp;1\u003c/b\u003e). Parametric continuous variables were evaluated using independent Students\u0026rsquo; t-test or Mann-Whitney U test as appropriate. Categorical variables were evaluated using Pearson\u0026rsquo;s chi-square test or Fisher\u0026rsquo;s exact test. Bivariate correlation analysis was performed using the Pearson correlation coefficient or Spearman\u0026rsquo;s rank correlation coefficient. For multiple groups analysis, one-way ANOVA with Tukey post hoc test or Kruskal-Wallis test with Bonferroni post hoc test were adopted as appreciate. A two-sided p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was regarded as a significant difference. Linear regression analysis was adopted to assess the correlation between ECG parameters and GLS or LVMI. Demographics (age and gender) and all the ECG parameters were included in the univariate analysis and significant factors in univariable analysis were selected for the following multivariate model and inputted using an \u0026ldquo;stepwise\u0026rdquo; method. Receiver-operator characteristics (ROC) was adopted to test the performance of parameters in the final multivariate linear regression model to assess the degree of cardiac involvement. Logistic regression analysis was adopted to assess the correlation between ECG parameters and Low T1 or LGE positive in CMR. Demographics (age and gender) and all the ECG parameters were included in the univariate analysis and significant factors in univariable analysis were selected for the following multivariate model and inputted using an \u0026ldquo;stepwise\u0026rdquo; method.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003ePatient characteristics\u003c/h2\u003e\u003cp\u003eIn this study, sixty-two Fabry disease patients and forty-five healthy controls were recruited (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The percentage of female (35% vs. 27%, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), age (40.5 years vs. 43 years, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), systolic blood pressure (121mmHg vs. 118mmHg, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) and diastolic blood pressure (78mmHg vs. 72mmHg, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) were similar between Fabry disease and Control groups. For ECG analysis, compared with control group, decreased PR interval, Pe-Q interval and Tp-e/QT as well as increased QRS width, percentage of Delta wave, Sokolow-Lyon index, percentage of fractionated QRS and percentage of U wave were observed in Fabry disease group (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). There was no significant difference on heart rate, P wave width, percentage of atrial fibrillation, percentage of LBBB or RBBB and duration of QTc between control and Fabry disease groups. For echocardiographic analysis, compared with control group, increased ventricular wall thickness and LVMI were detected in Fabry disease group (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and lower GLS was also observed in Fabry disease group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). LVEF, LVEDD and LVESD were similar between these two groups. Moreover, 56.36% patients were observed low native T1 value and 38.64% patients showed positive LGE in Fabry disease group.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe characteristics of patients.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;45)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFabry Disease (n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27 (60.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e35 (56.45%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.714\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43 (36.5, 50.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e40.5 (33.75, 51.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.270\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSBP (mmHg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e118 (108, 128.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e121 (113.5, 134.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.391\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDBP (mmHg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e72 (68, 82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e78 (71, 86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.153\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eElectrocardiographic Data\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHR (bpm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e67 (63, 80.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e68 (60.5, 78) (n\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.143\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP wave width (msec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e102.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e99.31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.74 (n\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.155\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePR interval (msec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e156.16\u0026thinsp;\u0026plusmn;\u0026thinsp;2.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e139.49\u0026thinsp;\u0026plusmn;\u0026thinsp;3.12 (n\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePe-Q interval (msec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e53.69\u0026thinsp;\u0026plusmn;\u0026thinsp;2.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e40.19\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04 (n\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAtrial fibrillation (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3 (0.05%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.262\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQRS width (without LBBB or RBBB) (msec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90 (88, 93) (n\u0026thinsp;=\u0026thinsp;43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e92 (86, 106) (n\u0026thinsp;=\u0026thinsp;58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDelta wave (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e6 (10.17%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.035\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLBBB (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1 (0.02%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRBBB (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (0.04%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3 (0.05%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQTc (msec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e424.33\u0026thinsp;\u0026plusmn;\u0026thinsp;3.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e428.69\u0026thinsp;\u0026plusmn;\u0026thinsp;4.11 (n\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.458\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTp-e/QT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSokolow-Lyon index (mV)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.0 (1.51. 2.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e3.38 (2.65, 4.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003efQRS (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (17.78%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e26 (41.94%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eU wave (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e18 (29.03%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEchocardiographic Data\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLVEF (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e64.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e64.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.987\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIVS (mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (8, 9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e13 (10, 15.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePWT (mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (8, 9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e11 (9, 14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLVEDD (mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46 (43, 48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e45 (43, 49)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.957\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLVESD (mm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30 (28, 32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e30 (28, 32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.987\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLVMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70.57 (63.36, 76.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e109.16 (84.43, 160.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGLS (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-22.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e-16.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCMR Data\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow T1 (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e31/55 (56.36%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLGE (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e17/44 (38.64%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eGene mutations and activity of enzyme\u003c/h2\u003e\u003cp\u003eAll Fabry disease patients under gene mutation analysis, activation of α-galactosidase A test and detection of the level of lyso-Gb3. Patients with pathogenic variant under gene analysis and patients with uncertain variant together with reduced α-galactosidase A activation as well as elevated lyso-Gb3 level were diagnosed as Fabry disease. The mutations and types of variants in Fabry disease patients were listed in \u003cb\u003eSupplemental Fig.\u0026nbsp;2\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eTo determine whether the activation of α-galactosidase A and the serum lyso-Gb3 level were associated the severity of cardiac involvement in Fabry disease, the correlation analysis between α-galactosidase A or globotriaosylsphingosine with GLS, LVMI, Low T1 or LGE were performed. Our results showed that the activation of enzyme and accumulation of lyso-Gb3 were only corelated with low native T1 value (\u003cb\u003eSupplemental Table\u0026nbsp;3\u003c/b\u003e). Activation of enzyme and accumulation of lyso-Gb3 have been well documented to be associated with the severity of the Fabry disease. Nonetheless, increased myocardial inflammation and fibrosis as well as microvascular dysfunction were all the key factors to assess the cardiac involvement in Fabry disease. Therefore, we performed this study to better describe the progression of Fabry disease in the heart.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eECG findings in different clinical stages\u003c/h2\u003e\u003cp\u003eThe echocardiographic, MRI and ECG characteristics in different clinical stages were shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. To determine the ECG changes in different clinical stages, we summarized the ECG parameters based on different clinical stages in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Our results showed that no significant difference on P wave width, Pe-Q interval or QRS width was observed between different clinical stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-C). The duration of QTc markedly reduced in Non-hypertrophic stage compared with Hypertrophic and pre-fibrotic stage as well as Hypertrophic and fibrotic stage. There was no significant difference on the duration of QTc between Control group, Pre-detectable, Hypertrophic and pre-fibrotic as well as Hypertrophic and fibrotic stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). Compared with control group, Tp-e/QT significant decreased in Hypertrophic and pre-fibrotic as well as Hypertrophic and fibrotic stages. There was no significant difference between Control group, Pre-detectable and Non-hypertrophic stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). Compared with Control group, Sokolow-Lyon index significantly increased in Non-hypertrophic, Hypertrophic and pre-fibrotic as well as Hypertrophic and fibrotic stages (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). In addition, Sokolow-Lyon index in Hypertrophic and pre-fibrotic stage was higher than Pre-detectable stage (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe ECG findings of patients.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl (n\u0026thinsp;=\u0026thinsp;45)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePre-detectable stage (n\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon-hypertrophic stage (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHypertrophic and pre-fibrotic stage (n\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHypertrophic and Fibrotic stage (n\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP wave width (msec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e102.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e103.17\u0026thinsp;\u0026plusmn;\u0026thinsp;6.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99.87\u0026thinsp;\u0026plusmn;\u0026thinsp;2.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e93.50\u0026thinsp;\u0026plusmn;\u0026thinsp;4.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e98.63\u0026thinsp;\u0026plusmn;\u0026thinsp;3.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePR interval (msec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e156.16\u0026thinsp;\u0026plusmn;\u0026thinsp;2.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e149.67\u0026thinsp;\u0026plusmn;\u0026thinsp;11.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e141.20\u0026thinsp;\u0026plusmn;\u0026thinsp;4.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e128.00\u0026thinsp;\u0026plusmn;\u0026thinsp;10.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e138.31\u0026thinsp;\u0026plusmn;\u0026thinsp;7.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePe-Q interval (msec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e53.69\u0026thinsp;\u0026plusmn;\u0026thinsp;2.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46.50\u0026thinsp;\u0026plusmn;\u0026thinsp;6.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41.33\u0026thinsp;\u0026plusmn;\u0026thinsp;3.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e34.50\u0026thinsp;\u0026plusmn;\u0026thinsp;6.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e39.69\u0026thinsp;\u0026plusmn;\u0026thinsp;4.40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQRS width (msec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e92 (88, 97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e91 (84, 96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e90 (82, 102)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100 (93, 113)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e104 (86, 120)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDelta wave (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (33.33%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2 (11.76%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLBBB (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (5.88%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRBBB (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (5.88%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQTc (msec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e424.33\u0026thinsp;\u0026plusmn;\u0026thinsp;3.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e431.67\u0026thinsp;\u0026plusmn;\u0026thinsp;6.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e402.80\u0026thinsp;\u0026plusmn;\u0026thinsp;7.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e447.50\u0026thinsp;\u0026plusmn;\u0026thinsp;9.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e436.13\u0026thinsp;\u0026plusmn;\u0026thinsp;8.31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTp-e/QT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSokolow-Lyon index (mV)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.00 (1.51. 2.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.37 (1.85, 2.80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.29 (2.59, 4.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.94 (4.88, 7.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.91 (2.75, 5.51)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eII ST depression (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (16.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 (20.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4 (66.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9 (52.94%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eII negative or biphasic T (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (16.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5 (83.33%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10 (58.82%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV5 ST depression (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (16.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (13.33%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5 (83.33%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6 (35.29%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV5 negative or biphasic T (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (16.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (13.33%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5 (83.33%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e11 (64.71%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003efQRS (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (17.78%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (16.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (40.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (16.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8 (47.06%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eU wave (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (6.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5 (83.33%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5 (29.41%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eDeterminants of cardiac involvement\u003c/h2\u003e\u003cp\u003eEchocardiographic parameters including GLS and LVMI as well as CMR parameters including low native T1 value and LGE are widely used to evaluate cardiac involvement and disease progression. To determine which ECG change was associated with cardiac involvement and disease progression of Fabry disease, bivariate correlation analysis, univariate and multivariate analysis were performed between ECG parameters and GLS, LVMI, low native T1 value or LGE.\u003c/p\u003e\u003cp\u003eOur results showed that gender, age, Tp-e/QT, QRS width, ST segment depression or negative or biphasic T wave in lead II or lead V5, Sokolow-Lyon index and U wave were significantly associated with GLS in the correlation coefficient analysis and univariate model (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Nonetheless, in multivariate model, gender, age, Tp-e/QT, QRS width and Sokolow-Lyon index were significantly related to GLS (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The final multivariate model was showed in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and \u003cb\u003eSupplemental Table\u0026nbsp;4\u003c/b\u003e. Moreover, our results demonstrated that gender, age, Tp-e/QT, QRS width, ST segment depression or negative or biphasic T wave in lead II or lead V5, Sokolow-Lyon index and U wave were also significantly associated with LVMI in the correlation coefficient analysis and univariate model (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Nevertheless, in multivariate analysis, gender, Tp-e/QT, QRS width were associated with LVMI (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The final multivariate model was showed in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and \u003cb\u003eSupplemental Table\u0026nbsp;4\u003c/b\u003e. To assess the robustness of these changes, the significant factors in multivariate models were computed in ROC curve analysis. A ROC curve of Tp-e/QT had the best discriminative ability in both ROC curve analysis of GLS and ROC curve analysis of LVMI with area under the curve (AUC) 0.83 and 0.82 respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-D)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePredictors for GLS.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eCorrelation Coefficient analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eUnivariate analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eMultivariate analysis\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGander (Female)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.294\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.021\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-2.923\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.025\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.609\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.479\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.220\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP wave width\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.049\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.712\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.712\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePe-Q interval\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.048\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTp-e/QT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.574\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-85.408\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-35.818\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQRS width\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.582\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.186\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eII ST depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.479\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.701\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eII negative or biphasic T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.517\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.108\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003efQRS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.188\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.649\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.215\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSokolow-Lyon index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.495\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.447\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.710\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV5 ST depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.453\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.655\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV5 negative or biphasic T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.569\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.732\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eU wave\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.384\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.564\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePredictors for LVMI.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eCorrelation Coefficient analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eUnivariate analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eMultivariate analysis\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGander (Female)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.299\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.018\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-42.704\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-36.644\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.561\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.694\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP wave width\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.943\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.564\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.407\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePe-Q interval\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.161\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.224\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.852\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.138\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTp-e/QT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.581\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-977.959\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-559.648\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQRS width\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.570\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.769\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.343\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eII ST depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.468\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e49.402\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eII negative or biphasic T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.519\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56.855\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003efQRS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.453\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.058\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSokolow-Lyon index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.429\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.558\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV5 ST depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.440\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43.972\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV5 negative or biphasic T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.585\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65.393\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eU wave\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.367\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45.761\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eNext, in correlation coefficient analysis, gender and Sokolow-Lyon index were associated with low native T1 value (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Nonetheless, no ECG parameter was significantly related to low native T1 value (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Age, Tp-e/QT, negative and biphasic T wave in lead II or lead V5 were associated with LGE positive in correlation coefficient analysis (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Age, Tp-e/QT, QRS width, negative and biphasic T wave in lead II or lead V5 were associated with LGE positive in univariate analysis (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Nevertheless, none of ECG parameters was significantly related to LGE positive in multivariate analysis (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePredictors for Low T1.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eCorrelation Coefficient analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eUnivariate analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eMultivariate analysis\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eExp(B)(95%CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eExp(B)(95%CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGander (Female)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.405\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.166 (0.049\u0026ndash;0.564)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.017 (1.773\u0026ndash;20.416)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.535\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.985 (0.941\u0026ndash;1.031)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.512\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP wave width\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.771\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.002 (0.961\u0026ndash;1.044)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.926\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePe-Q interval\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.863\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.998 (0.963\u0026ndash;1.034)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.900\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTp-e/QT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.321\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1307.154 (0.000-7.805*10\u003csup\u003e9\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.367\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQRS width\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.644\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.986 (0.954\u0026ndash;1.018)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.390\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eII ST depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.828\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.884 (0.298\u0026ndash;2.621)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.824\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eII negative or biphasic T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.146\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.288\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.550 (0.185\u0026ndash;1.631)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.281\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003efQRS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.929\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.053 (0.351\u0026ndash;3.155)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSokolow-Lyon index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.281\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.038\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.321 (0.938\u0026ndash;1.860)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV5 ST depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.929\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.053 (0.351\u0026ndash;3.155)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV5 negative or biphasic T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.377\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.611 (0.209\u0026ndash;1.789)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.369\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eU wave\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.992\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.994 (0.307\u0026ndash;3.211)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.991\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePredictors for LGE.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eCorrelation Coefficient analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eUnivariate analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eMultivariate analysis\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eExp(B)(95%CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eExp(B)(95%CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGander (Female)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.091\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.559\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.682 (0.195\u0026ndash;2.383)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.549\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.495\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.106 (1.034\u0026ndash;1.184)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.106 (1.034\u0026ndash;1.184)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP wave width\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.892\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.997 (0.950\u0026ndash;1.045)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.891\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePe-Q interval\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.980\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.995 (0.956\u0026ndash;1.035)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.796\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTp-e/QT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.340\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.024\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000 (0.000-0.513)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.043\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQRS width\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.106\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.041 (1.000 -1.084)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.048\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eII ST depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.233\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.672 (0.757\u0026ndash;9.426)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eII negative or biphasic T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.329\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.029\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.082 (1.119\u0026ndash;14.883)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.033\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003efQRS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.176\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.111 (0.598\u0026ndash;7.448)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.245\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSokolow-Lyon index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.722\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.100 (0.781\u0026ndash;1.548)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.585\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV5 ST depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.059\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.703\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.295 (0.356\u0026ndash;4.720)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.695\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eV5 negative or biphasic T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.345\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.354 (1.195\u0026ndash;15.865)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.026\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eU wave\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.081\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.602\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.458 (0.366\u0026ndash;5.812)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.593\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTaken together, our results demonstrated that Tp-e/QT, QRS width and Sokolow-Lyon index were associated with GLS and Tp-e/QT and QRS width were associated with LVMI. Moreover, Tp-e/QT had the best ability to discriminate patients with impaired GLS or increased LVMI from normal controls.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussions","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eMain findings\u003c/h2\u003e\u003cp\u003eIn this study, we summarized the ECG changes in different clinical stages of Fabry disease. Our results showed that compared with Control group, decreased PR interval, Pe-Q interval and Tp-e/QT as well as increased QRS width, delta wave, Sokolow-Lyon index, fractionated QRS wave and U wave were observed in Fabry disease group. Following the progression of cardiac involvement, Tp-e/QT progressively decreased whereas Sokolow-Lyon index gradually increased from Pre-detectable stage to Hypertrophic and pre-fibrotic stage and tended to reduce in Hypertrophic and fibrotic stage. In addition, our results provide the proof-of-principle evidence the Tp-e/QT, QRS width and Sokolow-Lyon index were associated with GLS and LVMI. Tp-e/QT had the best discrimination ability in clinical staging.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eClinical Stage\u003c/h2\u003e\u003cp\u003eIn this study, we define cardiac involvement of Fabry disease into four stages: Pre-detectable stage, Non-hypertrophic stage, Hypertrophic and pre-fibrotic stage as well as Hypertrophic and fibrotic stage. Previous study defined cardiac involvement into four stages, including non-hypertrophic, hypertrophic-pre-fibrotic, hypertrophic-fibrotic and overt dysfunction stage\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Nevertheless, recent studies showed that earlier detection of Fabry disease and earlier beginning of Fabry disease-specific therapies could benefit the progression of cardiac involvement of Fabry disease. Therefore, we included a pre-detectable stage in our study. As few Fabry disease patients with severe systolic dysfunction or diastolic dysfunction in our study, we did not include an overt dysfunction stage in current study. Recent studies showed that lysosomal storage was insufficient to represent the severity of cardiac involvement as cardiac inflammation and fibrosis were all contributed to cardiac involvement of Fabry disease\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Therefore, we did not include lysosomal storage and activity of enzyme in staging of Fabry disease. In this study, we defined cardiac involvement of Fabry disease mainly according to the results of echocardiographic assessment and CMR.\u003c/p\u003e\u003cp\u003ePrevious study showed that RBBB, Sokolow-Lyon index and repolarization abnormalities were associated with ventricular hypertrophy\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Nonetheless, our result showed that repolarization abnormalities and QRS width were associated with ventricular hypertrophy. Ventricular fibrosis in patients with Fabry disease might lead to a decrease in Sokolow-Lyon index. Previous study demonstrated that Sokolow-Lyon index, ratio between P-wave and PR-segment duration, QRS width and QRS duration were predictors of low T1 value\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. In our study, there was no ECG parameter associate with low T1 value. The T1 values of some Fabry disease patients with increased LVMI, decreased GLS and LGE positive were normal. Increased myocardial inflammation and fibrosis might influence the T1 value. Therefore, in this study, we sought to investigate whether any ECG changes could be detected prior to appearance of echocardiographic and CMR changes. Fortunately, there was no significant difference on ECG parameters between Control and Pre-detected stage in current study. Prior study showed decreased P wave duration and Pe-Q interval in pre-hypertrophic Fabry disease patient with normal T1 compared with control\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Nonetheless, in our study, the duration of P wave was similar between Control and Pre-detectable stage. Although a decreasing tendency of Pe-Q interval was observed in Pre-detectable stage compared with control group, no statistic difference was detected. Augusto JB, et al. included Fabry disease patients with or without Fabry disease-specific therapies in their study and only two groups including pre-hypertrophy with normal native T1 and pre-hypertrophy with low T1 groups were included in their study\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Nevertheless, only Fabry disease patients without any Fabry disease-specific therapies was recruited in our studies and both pre-hypertrophic as well as hypertrophic and fibrotic patents was included in current study. Whether any ECG changes could be detected prior to echocardiographic and CMR detections remains unclear. Future studies can be launched to explore different ECG changes in different clinical staging.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eThe ECG parameters related with cardiac involvement of Fabry disease\u003c/h2\u003e\u003cp\u003eCardiac involvement of Fabry disease starts prior to the appearance of clinical symptoms. Previous studies demonstrated that LVMI, GLS, native T1 value and LGE were associated with the progression of cardiac involvement\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Interesting, we performed correlation coefficient analysis between the activity of α-galactosidase A and the serum level of Gb3 with GLS, LVMI, Low T1 and LGE. Only low native T1 value was associated with decreased activity of α-galactosidase A and increased serum level of Gb3. Accumulation of Gb3, microvascular dysfunction, myocardial inflammation and cardiac fibrosis are all involved in progression of cardiac involvement of Fabry disease\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. That is why Fabry disease-specific therapies targeting on the activity of enzyme has limited effect on cardiac involvement and why only echocardiographic assessment or CMR is insufficient to define cardiac involvement of Fabry disease. Therefore, studies on ECG parameters in Fabry disease is of parameter important to define the progression of cardiac changes and evaluate cardiac response to Fabry disease-specific therapies.\u003c/p\u003e\u003cp\u003ePrior studies demonstrated that short Pe-Q interval, high QRS voltages and pathological repolarization contributed to the diagnosis of Fabry disease\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Consistent with previous studies, reduced Pe-Q interval and Tp-e/QT as well as increased QRS width and Sokolow-Lyon index were detected in Fabry disease patients in our study. Moreover, increased presence of delta wave, fractionated QRS wave and U wave were also observed in Fabry disease patients. To better describe the progression of cardiac involvement in Fabry disease, we sought to investigated which ECG parameters were relevant to cardiac involvement of Fabry disease. Correlation coeffective analysis was performed between parameters mentioned above and ECG changes. Our results showed that Tp-e/QT, Sokolow-Lyon index and QRS width were associated with GLS whereas Tp-e/QT and QRS width were associated with LVMI. The area under curve (AUC) showed that Tp-e/QT was the best ECG parameters to predict impaired GLS and increased LVMI. As the CMR parameters in different cardiovascular center is different, we define low native T1 value and LGE positive according to the recommendation commercially available. Unfortunately, our results demonstrated that there was no significant difference between ECG parameters and CMR parameters.\u003c/p\u003e\u003cp\u003ePrior studies demonstrated that progressive accumulation of Gb3 and lyso-Gb3 in AV node resulted in accelerated AV conduction and reduced Pe-Q interval\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. As cardiac involvement progressed, increased cardiac inflammation and fibrosis decreased AV conduction, culminating in normal Pe-Q interval even AV blockage\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. That is why short Pe-Q interval was observed in Fabry disease patients, whereas no significant relationship was detected between the severity of cardiac involvement and Pe-Q interval. Recent studies discussed the value of echocardiographic assessment and CMR in evaluation of cardiac damage of Fabry disease\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Our study demonstrated that Tp-e/QT and QRS width were of value in assessing cardiac damage and cardiac involvement in Fabry disease.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eLimitation\u003c/h2\u003e\u003cp\u003eFirst of all, this is a single center cross-sectional study. How ECG parameters changed during the development of Fabry disease was hypothesized rather than detected. Longitudinal studies would be helpful to confirm the ECG changes. Moreover, the small sample size in the Pre-detectable stage and Hypertrophic and pre-fibrotic stage limited the robustness of subgroup analysis. Secondly, Fabry disease patients without disease-specific therapies were recruited in our study. How disease-specific therapies influence the ECG changes remains unclear. Thirdly, native T2 value of CMR were not included in current study. Previous studies showed that native T2 value was associated with cardiac inflammation\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Further model could include native T1/T2 value, LGE, LVMI, GLS as well as ECG parameters, such as QRS width and Tp-e/QT to predict cardiac involvement and damage in patients with Fabry disease. Last but not least, our study showed that no significant difference on regular ECG assessment was observed between Pre-detectable stage and Non-hypertrophic stages. Holter examination which includes more ECG information would be benefit to detect subtle ECG changes in Pre-detectable stage and might be helpful in early diagnosis of Fabry disease.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study summarized ECG changes in different stages of cardiac involvement of Fabry disease patients. QRS width and Tp-e/QT were associated with the severity of cardiac involvement in patients with Fabry disease. Future studies can be launched to investigate the value of these ECG parameters in defining the optimal intervention timepoint and assessing the severity of cardiac involvement and response to disease-specific therapies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAUC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eArea under curve\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBSA\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBody surface area\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCMR\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCardiovascular magnetic resonance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eECG\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eelectrocardiographic\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGb3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGlobotriaosylceramide\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGLA\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGalactosidase-α\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGLS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGlobal longitudinal strain\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHeart rate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIVSd\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInter-ventricular septal dimension\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLBBB\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeft bundle branch block\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLGE\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLate gadolinium enhancement\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLV\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeft ventricle\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLVEDD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeft ventricular end-diastolic dimension\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLVEF\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeft ventricular ejection fraction\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLVH\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeft ventricular hypertrophy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLVMI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeft ventricular mass index\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLVESD\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLeft ventricular end-systolic dimension\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLyso-Gb3\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGlobotriaosylsphingosine\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePWT\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePosterior wall thickness\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRBBB\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRight bundle branch block\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eROC\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReceiver-operator characteristics\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSEM\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStandard error of the mean\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTp-e\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThe peak of T wave to the end of T wave\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003e2D-STE\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTwo-dimensional speckle tracking echocardiography\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cp\u003e This study was approved by the Ethics Committee of the First Affiliated Hospital of Soochow University (2024\u0026thinsp;\u0026minus;\u0026thinsp;468). Patients were recruited in our cardiovascular center from January 2021 to June 2024 and Written informed consent was obtained from all patients.\u003c/p\u003e\u003ch2\u003eConsent for publication\u003c/h2\u003e\u003cp\u003eAll the authors have agreed with manuscript well for its submission for BMC cardiovascular disorders. The manuscript has not been published and is not being considered for publication elsewhere in whole or in part in any language.\u003c/p\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eAll authors have no conflict of interest.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis research was supported by the National Natural Science Foundation of China (82200283), the Scientific Research Project of Gusu Health Talents Program of Suzhou (GSWS2022017), the Innovation and Entrepreneurship Team in Jiangsu Province (JSSCT202353), the Multi-center Clinical Research Project for Major Diseases in Suzhou (DZXYJ202302). The funder had no roles in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eY.W. and J.K. performed ECG data collection and analysis. J.W. and J.F.Z. performed CMR recording and anaylsis. R.Z. and S.J.S. checked the ECG data. H.W. and C.S.M. performed echocardiographic data collection. B.Y.Z. and J.L.F. performed echocardiographic data analysis. C.Z., T.B.J., J.L.F. and S.J.S. designed study. Y.W., J.K. wrote the manuscript. J.K. and J.W performed the figures and tables. S.J.S and J.L.F. revised the manuscript, figures and tables.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eNo.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll the data are available from the corresponding authors (Dr. S.-J. S.) upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYuri A, Zarate, Robert J. Hopkin. Fabry\u0026rsquo;s disease. Lancet. 2008;372:1427\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKnott KD, Augusto JB, Nordin S, Kozor R, Camaioni C, Xue H, Hughes RK, Manisty C, Brown LAE, Kellman P, Ramaswami U, Hughes D, Plein S, Moon JC. Quantitative Myocardial Perfusion in Fabry Disease. Circ Cardiovasc Imaging. 2019;12:e008872.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYogasundaram H, Nikhanj A, Putko BN, Boutin M, Jain-Ghai S, Khan A, Auray-Blais C, West ML, Oudit GY. Elevated Inflammatory Plasma Biomarkers in Patients With Fabry Disease: A Critical Link to Heart Failure With Preserved Ejection Fraction. J Am Heart Assoc. 2018;7:e009098.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchiffmann R, Kopp JB, Austin HA, Sabnis S, Moore DF, Weibel T, Balow JE, Brady RO. Enzyme replacement therapy in Fabry disease: a randomized controlled trial. JAMA. 2001;285:2743\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGermain DP, Hughes DA, Nicholls K, Bichet DG, Giugliani R, Wilcox WR, Feliciani C, Shankar SP, Ezgu F, Amartino H, Bratkovic D, Feldt-Rasmussen U, Nedd K, Din SE, Lourenco U, Banikazemi CM, Charrow M, Dasouki J, Finegold M, Giraldo D, Goker-Alpan P, Longo O, Scott N, Torra CR, Tuffaha R, Jovanovic A, Waldek A, Packman S, Ludington S, Viereck E, Kirk C, Yu J, Benjamin J, Johnson ER, Lockhart F, Skuban DJ, Castelli N, Barth J, Barlow J, Schiffmann C. Treatment of Fabry's Disease with the Pharmacologic Chaperone Migalastat. N Engl J Med. 2016;375:545\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHughes DA, Nicholls K, Shankar SP, Sunder-Plassmann G, Koeller D, Nedd K, Vockley G, Hamazaki T, Lachmann R, Ohashi T, Olivotto I, Sakai N, Deegan P, Dimmock D, Eyskens F, Germain DP, Goker-Alpan O, Hachulla E, Jovanovic A, Lourenco CM, Narita I, Thomas M, Wilcox WR, Bichet DG, Schiffmann R, Ludington E, Viereck C, Kirk J, Yu J, Johnson F, Boudes P, Benjamin ER, Lockhart DJ, Barlow C, Skuban N, Castelli JP, Barth J, Feldt-Rasmussen U. Oral pharmacological chaperone migalastat compared with enzyme replacement therapy in Fabry disease: 18-month results from the randomised phase III ATTRACT study. J Med Genet. 2017;54:288\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePieroni M, Moon JC, Arbustini E, Barriales-Villa R, Camporeale A, Vujkovac AC, Elliott PM, Hagege A, Kuusisto J, Linhart A, Nordbeck P, Olivotto I, Pietil\u0026auml;-Effati P, Namdar M. Cardiac Involvement in Fabry Disease: JACC Review Topic of the Week. J Am Coll Cardiol. 2021;77:922\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFan J, Ma C, Wang H, Zhou B. The value of myocardial work in patients with left ventricular hypertrophy. Int J Cardiovasc Imaging. 2023;39:1105\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAugusto JB, Johner N, Shah D, Nordin S, Knott KD, Rosmini S, Lau C, Alfarih M, Hughes R, Seraphim A, Vijapurapu R, Bhuva A, Lin L, Ojrzyńska N, Geberhiwot T, Captur G, Ramaswami U, Steeds RP, Kozor R, Hughes D, Moon JC, Namdar M. The myocardial phenotype of Fabry disease pre-hypertrophy and pre-detectable storage. Eur Heart J Cardiovasc Imaging. 2021;22:790\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNamdar M, Steffel J, Vidovic M, Brunckhorst CB, Holzmeister J, L\u0026uuml;scher TF, Jenni R, Duru F. ECG changes in early recognition of Fabry disease. Heart. 2011;97:485\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoy A, Cumberland MJ, O'Shea C, Holmes A, Kalla M, Gehmlich K, Geberhiwot T, Steeds RP. Arrhythmogenesis in Fabry Disease. Curr Cardiol Rep. 2024;26:545\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLang RM, Badano LP, Mor-Avi V, Afilalo J, Armstrong A, Ernande L, Flachskampf FA, Foster E, Goldstein SA, Kuznetsova T, Lancellotti P, Muraru D, Picard MH, Rietzschel ER, Rudski L, Spencer KT, Tsang W, Voigt JU. 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;16:233\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchulz-Menger J, Bluemke DA, Bremerich J, Flamm SD, Fogel MA, Friedrich MG, Kim RJ, von Knobelsdorff-Brenkenhoff F, Kramer CM, Pennell DJ, Plein S, Nagel E. Standardized image interpretation and post-processing in cardiovascular magnetic resonance \u0026ndash;\u0026thinsp;2020 update: Society for Cardiovascular Magnetic Resonance (SCMR): Board of Trustees Task Force on Standardized Post-Processing. J Cardiovasc Magn Reson. 2020;22:19.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDel Franco A, Iannaccone G, Meucci MC, Lillo R, Cappelli F, Zocchi C, Pieroni M, Graziani F, Olivotto I. Clinical staging of Anderson-Fabry cardiomyopathy: An operative proposal. Heart Fail Rev. 2024;29:431\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eParisi V, Baldassarre R, Ferrara V, Ditaranto R, Barlocco F, Lillo R, Re F, Marchi G, Chiti C, Di Nicola F, Catalano C, Barile L, Schiavo MA, Ponziani A, Saturi G, Caponetti AG, Berardini A, Graziosi M, Pasquale F, Salamon I, Ferracin M, Nardi E, Capelli I, Girelli D, Gimeno Blanes JR, Biffi M, Gali\u0026egrave; N, Olivotto I, Graziani F, Biagini E. Electrocardiogram analysis in Anderson-Fabry disease: a valuable tool for progressive phenotypic expression tracking. Front Cardiovasc Med. 2023;10:1184361.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFigliozzi S, Camporeale A, Boveri S, Pieruzzi F, Pieroni M, Lusardi P, Spada M, Mignani R, Burlina A, Graziani F, Pica S, Tondi L, Bernardini A, Chow K, Namdar M, Lombardi M. ECG-based score estimates the probability to detect Fabry Disease cardiac involvement. 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JACC Cardiovasc Imaging. 2013;6:392\u0026ndash;406.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXu Y, Sun J, Wan K, Yu L, Wang J, Li W, Yang F, Sun J, Cheng W, Mui D, Zhang Q, Xie Q, Chen Y. Multiparametric cardiovascular magnetic resonance characteristics and dynamic changes in myocardial and skeletal muscles in idiopathic inflammatory cardiomyopathy. J Cardiovasc Magn Reson. 2020;22:22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAugusto JB, Nordin S, Vijapurapu R, Baig S, Bulluck H, Castelletti S, Alfarih M, Knott K, Captur G, Kotecha T, Ramaswami U, Tchan M, Geberhiwot T, Fontana M, Steeds RP, Hughes D, Kozor R, Moon JC. Myocardial Edema, Myocyte Injury, and Disease Severity in Fabry Disease. Circ Cardiovasc Imaging. 2020;13:e010171.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Electrocardiograph, Cardiomyopathy, Echocardiograph, Fabry Disease","lastPublishedDoi":"10.21203/rs.3.rs-7384760/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7384760/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eCardiac involvement of the disease is a leading cause of death and disability in Fabry disease characterized by pathological accumulation of globotriaosylceramide (Gb3) and lyso-globotriaosylceramide (lyso-Gb3) in multiple organs. In this study, we sought to investigate the electrocardiographic (ECG) changes in different clinical stages and evaluate the value of these parameters in assessing cardiac involvement.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003e62 patients with Fabry disease and 45 healthy controls were recruited in this study. ECG assessment, echocardiographic assessment and cardiac magnetic resonance (CMR) were recorded at rest in the same day. We defined 4 clinical stages of Fabry disease cardiomyopathy according to echocardiographic assessment and CMR: Pre-detectable stage, Non-hypertrophic stage, Hypertrophic and pre-fibrotic stage as well as Hypertrophic and fibrotic stage.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOur results showed that Tp-e/QT was significantly decreased and Sokolow-Lyon index was markedly increased following the development of disease. QRS width and Tp-e/QT was associated with the severity of cardiac involvement in Fabry disease.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eOur results demonstrated that QRS width and Tp-e/QT were associated with the severity of cardiac involvement in patients with Fabry disease and contributed to define the optimal intervention timepoint and assess the severity of cardiac involvement and response to disease-specific therapies.\u003c/p\u003e","manuscriptTitle":"ECG parameters to Detect Cardiac Involvement in Fabry Disease Original Articles","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-17 02:22:59","doi":"10.21203/rs.3.rs-7384760/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-10-22T16:39:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"270966802724407504449344161012993890638","date":"2025-10-17T07:10:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"30461742206825305436664103877580554037","date":"2025-10-17T06:30:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-05T18:47:33+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-02T18:11:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-01T13:03:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-01T13:01:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2025-08-16T03:23:07+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"090190a7-3f70-4d41-b06d-b1298cb05f1b","owner":[],"postedDate":"October 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-17T02:22:59+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-17 02:22:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7384760","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7384760","identity":"rs-7384760","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}