Pediatric sex estimation using AI-enabled ECG analysis: influence of pubertal development.

AI-enabled ECGs have previously been shown to accurately predict patient sex in adults and correlate with sex hormone levels. We aimed to test the ability of AI-enabled ECGs to predict sex in the pediatric population and study the influence of pubertal development. AI-enabled ECG models were created using a convolutional neural network trained on pediatric 10-second, 12-lead ECGs. The first model was trained de novo using pediatric data. The second model used transfer learning from a previously validated adult data-derived algorithm. We analyzed the first ECG from 90,133 unique pediatric patients (aged ≤18 years) recorded between 1987-2022, and divided the cohort into training, validation, and testing datasets. Subgroup analysis was performed on prepubertal (0-7 years), peripubertal (8-14 years), and postpubertal (15-18 years) patients. The cohort was 46.7% male, with 21,678 prepubertal, 26,740 peripubertal, and 41,715 postpubertal children. The de novo pediatric model demonstrated 81% accuracy and an area under the curve (AUC) of 0.91. Model sensitivity was 0.79, specificity was 0.83, positive predicted value was 0.84, and the negative predicted value was 0.78, for the entire test cohort. The model's discriminatory ability was highest in postpubertal (AUC = 0.98), lower in the peripubertal age group (AUC = 0.91), and poor in the prepubertal age group (AUC = 0.67). There was no significant performance difference observed between the transfer learning and de novo models. AI-enabled interpretation of ECG can estimate sex in peripubertal and postpubertal children with high accuracy.

Atrial and Ventricular Arrhythmia in Adults With Shone Complex: A Single-Center Cohort Study.

Background: Multilevel obstruction in left ventricular inflow and outflow predisposes to arrhythmias in Shone's complex (SC). Objectives: The purpose of this study was to study the prevalence and outcomes (heart failure [HF] hospitalization, cardiac transplant, death) of cardiac arrhythmias in adults with SC. Methods: Adults with SC (defined as ≥2 lesions out of supramitral ring, parachute mitral valve, subvalvular/valvular aortic stenosis (AS), and aortic coarctation) seen at Mayo Clinic between January 1999 and March 2020 were identified and evaluated for the presence of sustained atrial fibrillation, atrial flutter, and ventricular arrhythmias (VA). Kaplan-Meier survival analysis was used to calculate the occurrence of these arrhythmias. Results: Seventy-three patients with SC (mean age at first visit 33 ± 13 years) were identified. Most common anomalies were valvular AS (88%), coarctation (85%), parachute mitral valve (44%), subvalvular AS (44%), and supramitral ring (25%). Atrial arrhythmias were diagnosed in 24 patients (33%) at a mean age of 34.6 ± 12.7 years. Patients with atrial fibrillation and atrial flutter had higher number of surgeries, left atrial size, right ventricular systolic pressure, and HF hospitalizations. A rhythm control approach was used in majority of patients (75% on antiarrhythmic drugs and 50% underwent catheter ablation). Sustained VA occurred in 6 of 73 patients of whom 4 had an ejection fraction <40%. Death and cardiac transplantation occurred in 11 and 3 patients, respectively, during a median follow-up of 7.3 ± 6.0 years. Conclusions: In adults with SC, atrial arrhythmias occurred in one-third of patients, were associated with more HF hospitalizations, and frequently required rhythm control. Prevalence of sustained VA was 8% and implantable cardioverter-defibrillator implantation should be considered in those with reduced ejection fraction.

An electrocardiogram-based AI algorithm for early detection of pulmonary hypertension.

BACKGROUND: Early diagnosis of pulmonary hypertension (PH) is critical for effective treatment and management. We aimed to develop and externally validate an artificial intelligence algorithm that could serve as a PH screening tool, based on analysis of a standard 12-lead electrocardiogram (ECG). METHODS: The PH Early Detection Algorithm (PH-EDA) is a convolutional neural network developed using retrospective ECG voltage-time data, with patients classified as "PH-likely" or "PH-unlikely" (controls) based on right heart catheterisation or echocardiography. In total, 39 823 PH-likely patients and 219 404 control patients from Mayo Clinic were randomly split into training (48%), validation (12%), and test (40%) sets. ECGs taken within 1 month of PH diagnosis (diagnostic dataset) were used to train the PH-EDA at Mayo Clinic. Performance was tested on diagnostic ECGs within the test sets from Mayo Clinic (n=16 175/87 998 PH-likely/controls) and Vanderbilt University Medical Center (VUMC; n=6045/24 256 PH-likely/controls). Performance was also tested on ECGs taken 6-18 months (pre-emptive dataset), and up to 5 years prior to a PH diagnosis at both sites. RESULTS: Performance testing yielded an area under the receiver operating characteristic curve (AUC) of 0.92 and 0.88 in the diagnostic test set at Mayo Clinic and VUMC, respectively, and 0.86 and 0.81, respectively, in the pre-emptive test set. The AUC remained a minimum of 0.79 at Mayo Clinic and 0.73 at VUMC up to 5 years before diagnosis. CONCLUSION: The PH-EDA can detect PH at diagnosis and 6-18 months prior, demonstrating the potential to accelerate diagnosis and management of this debilitating disease.

Machine learning for prediction of ventricular arrhythmia episodes from intracardiac electrograms of automatic implantable cardioverter-defibrillators.

BACKGROUND: Despite effectiveness of the implantable cardioverter-defibrillator (ICD) in saving patients with life-threatening ventricular arrhythmias (VAs), the temporal occurrence of VA after ICD implantation is unpredictable. OBJECTIVE: The study aimed to apply machine learning (ML) to intracardiac electrograms (IEGMs) recorded by ICDs as a unique biomarker for predicting impending VAs. METHODS: The study included 13,516 patients who received Biotronik ICDs and enrolled in the CERTITUDE registry between January 1, 2010, and December 31, 2020. Database extraction included IEGMs from standard quarterly transmissions and VA event episodes. The processed IEGM data were pulled from device transmissions stored in a centralized Home Monitoring Service Center and reformatted into an analyzable format. Long-range (baseline or first scheduled remote recording), mid-range (scheduled remote recording every 90 days), or short-range predictions (IEGM within 5 seconds before the VA onset) were used to determine whether ML-processed IEGMs predicted impending VA events. Convolutional neural network classifiers using ResNet architecture were employed. RESULTS: Of 13,516 patients (male, 72%; age, 67.5 ± 11.9 years), 301,647 IEGM recordings were collected; 27,845 episodes of sustained ventricular tachycardia or ventricular fibrillation were observed in 4467 patients (33.0%). Neural networks based on convolutional neural networks using ResNet-like architectures on far-field IEGMs yielded an area under the curve of 0.83 with a 95% confidence interval of 0.79-0.87 in the short term, whereas the long-range and mid-range analyses had minimal predictive value for VA events. CONCLUSION: In this study, applying ML to ICD-acquired IEGMs predicted impending ventricular tachycardia or ventricular fibrillation events seconds before they occurred, whereas midterm to long-term predictions were not successful. This could have important implications for future device therapies.

Cardiac Resynchronization Therapy for Patients With Mild to Moderately Reduced Ejection Fraction and Left Bundle Branch Block.

BACKGROUND: It is unknown whether cardiac resynchronization therapy (CRT) would improve or halt the progression of heart failure (HF) in patients with mild to moderately reduced ejection fraction (HFmmrEF) and left bundle branch block (LBBB). OBJECTIVE: This study aimed to investigate the outcomes of CRT in patients with HFmmrEF and left ventricular conduction delay. METHODS: A prospective, randomized clinical trial sponsored by the National Heart, Lung, and Blood Institute included 76 patients who met the study inclusion criteria (left ventricular ejection fraction [LVEF] of 36%-50% and LBBB). Patients received CRT-pacemaker and were randomized to CRT-OFF (right ventricular pacing 40 beats/min) or CRT-ON (biventricular pacing 60-150 beats/min). At a 6-month follow-up, pacing programming was changed to the opposite settings. New York Heart Association class, N-terminal pro-brain natriuretic peptide levels, and echocardiographic variables were collected at baseline, 6 months, and 12 months. The primary study end point was the left ventricular end-systolic volume (LVESV) change from baseline, and the primary randomized comparison was the comparison of 6-month to 12-month changes between randomized groups. RESULTS: The mean age of the patients was 68.4 ± 9.8 years (male, 71%). Baseline characteristics were similar between the 2 randomized groups (all P > .05). In patients randomized to CRT-OFF first, then CRT-ON, LVESV was reduced from baseline only after CRT-ON (baseline, 116.1 ± 36.5 mL; CRT-ON, 87.6 ± 26.0 mL; P < .0001). The randomized analysis of LVEF showed a significantly better change from 6 to 12 months in the OFF-ON group (P = .003). LVEF was improved by CRT (baseline, 41.3% ±.7%; CRT-ON, 46.0% ± 8.0%; P = .002). In patients randomized to CRT-ON first, then CRT-OFF, LVESV was reduced after both CRT-ON and CRT-OFF (baseline, 109.8 ± 23.5 mL; CRT-ON, 91.7 ± 30.5 mL [P < .0001]; CRT-OFF, 99.3 ± 28.9 mL [P = .012]). However, the LVESV reduction effect became smaller between CRT-ON and CRT-OFF (P = .027). LVEF improved after both CRT-ON and CRT-OFF (baseline, 42.7% ± 4.3%; CRT-ON, 48.5% ± 8.6% [P < .001]; CRT-OFF, 45.9% ± 7.7% [P = .025]). CONCLUSION: CRT for patients with HFmmrEF significantly improves LVEF and ventricular remodeling after 6 months of CRT. The study provides novel evidence that early CRT benefits patients with HFmmrEF with LBBB.

Unlocking the potential of artificial intelligence in electrocardiogram biometrics: age-related changes, anomaly detection, and data authenticity in mobile health platforms.

Aims: Mobile devices such as smartphones and watches can now record single-lead electrocardiograms (ECGs), making wearables a potential screening tool for cardiac and wellness monitoring outside of healthcare settings. Because friends and family often share their smart phones and devices, confirmation that a sample is from a given patient is important before it is added to the electronic health record. Methods and results: We sought to determine whether the application of Siamese neural network would permit the diagnostic ECG sample to serve as both a medical test and biometric identifier. When using similarity scores to discriminate whether a pair of ECGs came from the same patient or different patients, inputs of single-lead and 12-lead medians produced an area under the curve of 0.94 and 0.97, respectively. Conclusion: The similar performance of the single-lead and 12-lead configurations underscores the potential use of mobile devices to monitor cardiac health.

Atrial Fibrillation Substrate and Catheter Ablation Outcomes in MYBPC3- and MYH7-Mediated Hypertrophic Cardiomyopathy.

BACKGROUND: The effects of disease-causing MYBPC3 or MYH7 genetic variants on atrial myopathy, atrial fibrillation (AF) clinical course, and catheter ablation efficacy remain unclear. OBJECTIVES: The aim of this study was to characterize the atrial substrate of patients with MYBPC3- or MYH7-mediated hypertrophic cardiomyopathy (HCM) and its impact on catheter ablation outcomes. METHODS: A retrospective single-center study of patients with HCM who underwent genetic testing and catheter ablation for AF was performed. Patients with MYBPC3- or MYH7-mediated HCM formed the gene-positive cohort; those without disease-causative genetic variants formed the control cohort. High-density electroanatomical mapping was performed using a 3-dimensional mapping system, followed by radiofrequency ablation. RESULTS: Twelve patients were included in the gene-positive cohort (mean age 55.6 ± 9.9 years, 83% men, 50% MYBPC3, 50% MYH7, mean ejection fraction 59.3% ± 13.7%, mean left atrial [LA] volume index 51.7 ± 13.1 mL/m2, mean LA pressure 20.2 ± 5.4 mm Hg) and 15 patients in the control arm (mean age 61.5 ± 12.6 years, 60% men, mean ejection fraction 64.9% ± 5.1%, mean LA volume index 54.1 ± 12.8 mL/m2, mean LA pressure 19.6 ± 5.41 mm Hg). Electroanatomical mapping demonstrated normal voltage in 87.7% ± 5.03% of the LA in the gene-positive cohort and 94.3% ± 3.58% of the LA in the control cohort (P < 0.001). Of the abnormal regions, intermediate scar (0.1-0.5 mV) accounted for 6.33% ± 1.97% in the gene-positive cohort and 3.07% ± 2.46% in the control cohort (P < 0.01). Dense scar (<0.1 mV) accounted for 5.93% ± 3.20% in the gene-positive cohort and 2.61% ± 2.19% in the control cohort (P < 0.01). Freedom from AF at 12 months was similar between the gene-positive (75%) and control (73%) cohorts (P = 0.92), though a greater number of procedures were required in the gene-positive cohort. CONCLUSIONS: Patients with MYBPC3- or MYH7-mediated HCM undergoing AF ablation have appreciably more low-amplitude LA signals, suggestive of fibrosis. However, catheter ablation remains an effective rhythm-control strategy.

Artificial intelligence-enhanced electrocardiogram for arrhythmogenic right ventricular cardiomyopathy detection.

Aims: ECG abnormalities are often the first signs of arrhythmogenic right ventricular cardiomyopathy (ARVC) and we hypothesized that an artificial intelligence (AI)-enhanced ECG could help identify patients with ARVC and serve as a valuable disease-detection tool. Methods and results: We created a convolutional neural network to detect ARVC using a 12-lead ECG. All patients with ARVC who met the 2010 task force criteria and had disease-causative genetic variants were included. All case ECGs were randomly assigned in an 8:1:1 ratio into training, validation, and testing groups. The case ECGs were age- and sex-matched with control ECGs at our institution in a 1:100 ratio. Seventy-seven patients (51% male; mean age 47.2 ± 19.9), including 56 patients with PKP2, 7 with DSG2, 6 with DSC2, 6 with DSP, and 2 with JUP were included. The model was trained using 61 case ECGs and 5009 control ECGs; validated with 7 case ECGs and 678 control ECGs and tested in 22 case ECGs and 1256 control ECGs. The sensitivity, specificity, positive and negative predictive values of the model were 77.3, 62.9, 3.32, and 99.4%, respectively. The area under the curve for rhythm ECG and median beat ECG was 0.75 and 0.76, respectively. Conclusion: Our study found that the model performed well in excluding ARVC and supports the concept that the AI ECG can serve as a biomarker for ARVC if a larger cohort were available for network training. A multicentre study including patients with ARVC from other centres would be the next step in refining, testing, and validating this algorithm.

First-in-man report of transsubclavian venous implantation of the Aveir leadless cardiac pacing system.

INTRODUCTION: Transsubclavian venous implantation of the Aveir leadless cardiac pacemaker (LCP) has not been previously reported. METHODS AND RESULTS: Three cases of transsubclavian implantation of the Aveir LCP are reported. Two cases were postbilateral orthotopic lung transplant, without appropriate femoral or jugular access due to recent ECMO cannulation and jugular central venous catheters. In one case, there was strong patient preference for same-day discharge. Stability testing confirmed adequate fixation and electrical testing confirmed stable parameters in all cases. All patients tolerated the procedure well without significant immediate complications. CONCLUSIONS: We demonstrate the feasibility of transsubclavian implantation of the Aveir LCP.

Long-term outcomes with abandoning versus extracting sterile leads: A 10-year population-based study.

BACKGROUND: Long-term outcomes of sterile lead management strategies of lead abandonment (LA) or transvenous lead extraction (TLE) remain unclear. METHODS: We performed a retrospective study of a population residing in southeastern Minnesota with follow-up at the Mayo Clinic and its health systems. Patients who underwent LA or TLE of sterile leads from January 1, 2000, to January 1, 2011, and had follow-up for at least 10 years or until their death were included. RESULTS: A total of 172 patients were included in the study with 153 patients who underwent LA and 19 who underwent TLE for sterile leads. Indications for subsequent lead extraction arose in 9.1% (n = 14) of patients with initial LA and 5.3% (n = 1) in patients with initial TLE, after an average of 7 years. Moreover, 28.6% of patients in the LA cohort who required subsequent extraction did not proceed with the extraction, and among those who proceeded, 60% had clinical success and 40% had a clinical failure. Subsequent device upgrades or revisions were performed in 18.3% of patients in the LA group and 31.6% in the TLE group, with no significant differences in procedural challenges (5.2% vs. 5.3%). There was no difference in 10-year survival probability among the LA group and the TLE group (p = .64). CONCLUSION: An initial lead abandonment strategy was associated with more complicated subsequent extraction procedures compared to patients with an initial transvenous lead extraction strategy. However, there was no difference in 10-year survival probability between both lead management approaches.

Cardiac implantable electronic devices in female patients: Esthetic, breast implant, and anatomic considerations.

INTRODUCTION: The implantation of a cardiac implantable electronic device (CIED) can have esthetic and psychological consequences on patients. We explore a heart team model for care coordination and discuss esthetic approaches for improved cosmetic outcomes in patients undergoing (CIED)-related procedures or de novo implantation. METHODS: Patients undergoing CIED surgery for approved indications between June 2015 and June 2022 were identified. Patients were included when surgical care was provided by a collaborative relationship between the primary electrophysiologist and the plastic surgeon. Patient demographics, details of the surgical procedure, information on breast implants, complications, and outcomes related to cosmesis were recorded. RESULTS: Twenty-two female patients were included in this study. The mean age was 50.2 ± 18.2 years. The mean follow-up duration was 2.2 ± 5.5 months. The top two indications for the procedure included CIED generator change (n = 9, 41%) and implantable cardioverter-defibrillator (ICD) implantation (n = 7, 32%). The most common reasons for involving plastic surgery in the procedure included surgery near breast implants (n = 10, 45%) and device displacement or discomfort (n = 8, 36%). CIED pocket position was prepectoral in 10 cases (45%), subpectoral in 11 patients (50%), and intramuscular in one patient (4.5%). The majority of the patients (20, 91%) had cosmetically acceptable results postprocedure. One patient (4.5%) had breast asymmetry on the CIED side, and another continued to have skin erosion over the CIED and leads. CONCLUSION: A heart team approach incorporating the expertize of cardiac electrophysiology and plastic surgery is essential for providing optimal care for patients with breast implants and patients requesting esthetic appeal.

Incidence and Outcomes of New-Onset Right Bundle Branch Block Following Transcatheter Aortic Valve Replacement.

BACKGROUND: The incidence and prognosis of right bundle branch block (RBBB) following transcatheter aortic valve replacement (TAVR) are unknown. Hence, we sought to characterize the incidence of post-TAVR RBBB and determine associated risks of permanent pacemaker (PPM) implantation and mortality. METHODS: All patients 18 years and above without preexisting RBBB or PPM who underwent TAVR at US Mayo Clinic sites and Mayo Clinic Health Systems from June 2010 to May 2021 were evaluated. Post-TAVR RBBB was defined as new-onset RBBB in the postimplantation period. The risks of PPM implantation (within 90 days) and mortality following TAVR were compared for patients with and without post-TAVR RBBB using Kaplan-Meier analysis and Cox proportional hazards modeling. The risks of PPM implantation (within 90 days) and mortality following TAVR were compared for patients with and without post-TAVR RBBB using Kaplan-Meier analysis and Cox proportional hazards modeling. RESULTS: Of 1992 patients, 15 (0.75%) experienced new RBBB post-TAVR. There was a higher degree of valve oversizing among patients with new RBBB post-TAVR versus those without (17.9% versus 10.0%; P=0.034). Ten patients (66.7%) with post-TAVR RBBB experienced high-grade atrioventricular block and underwent PPM implantation (median 1 day; Q1, 0.2 and Q3, 4), compared with 268/1977 (13.6%) without RBBB. Following propensity score adjustment for covariates (age, sex, balloon-expandable valve, annulus diameter, and valve oversizing), post-TAVR RBBB was significantly associated with PPM implantation (hazard ratio, 8.36 [95% CI, 4.19-16.7]; P<0.001). No statistically significant increase in mortality was seen with post-TAVR RBBB (hazard ratio, 0.83 [95% CI, 0.33-2.11]; P=0.69), adjusting for age and sex. CONCLUSIONS: Although infrequent, post-TAVR RBBB was associated with elevated PPM implantation risk. The mechanisms for its development and its clinical prognosis require further study.

Artificial intelligence-enabled ECG for left ventricular diastolic function and filling pressure.

Assessment of left ventricular diastolic function plays a major role in the diagnosis and prognosis of cardiac diseases, including heart failure with preserved ejection fraction. We aimed to develop an artificial intelligence (AI)-enabled electrocardiogram (ECG) model to identify echocardiographically determined diastolic dysfunction and increased filling pressure. We trained, validated, and tested an AI-enabled ECG in 98,736, 21,963, and 98,763 patients, respectively, who had an ECG and echocardiographic diastolic function assessment within 14 days with no exclusion criteria. It was also tested in 55,248 patients with indeterminate diastolic function by echocardiography. The model was evaluated using the area under the curve (AUC) of the receiver operating characteristic curve, and its prognostic performance was compared to echocardiography. The AUC for detecting increased filling pressure was 0.911. The AUCs to identify diastolic dysfunction grades ≥1, ≥2, and 3 were 0.847, 0.911, and 0.943, respectively. During a median follow-up of 5.9 years, 20,223 (20.5%) died. Patients with increased filling pressure predicted by AI-ECG had higher mortality than those with normal filling pressure, after adjusting for age, sex, and comorbidities in the test group (hazard ratio (HR) 1.7, 95% CI 1.645-1.757) similar to echocardiography and in the indeterminate group (HR 1.34, 95% CI 1.298-1.383). An AI-enabled ECG identifies increased filling pressure and diastolic function grades with a good prognostic value similar to echocardiography. AI-ECG is a simple and promising tool to enhance the detection of diseases associated with diastolic dysfunction and increased diastolic filling pressure.

Ventricular Tachycardia Ablation in Patients With Desmoplakin Cardiomyopathy.

BACKGROUND: Desmoplakin (DSP) pathogenic variants are rare causes of arrhythmogenic cardiomyopathy and often involve the right and left ventricles. Ventricular tachycardia (VT) ablations may be required in these patients, but procedural characteristics have not been reported. OBJECTIVES: In this study, the authors sought to report a multicenter experience of VT ablation in patients with DSP pathogenic variants. METHODS: VT ablations performed in patients with known DSP pathogenic variants were analyzed across 6 centers in 3 countries. Patient characteristics and acute and long-term procedural outcomes were reported. RESULTS: A total of 20 patients (13 men, median age 43 years [Q1-Q3: 41.5-53.0 years], left ventricular ejection fraction 43.0% [Q1-Q3: 41.5%-53.0%], 11 previous failed ablations) were referred for VT ablation procedures. All patients had symptomatic VTs, with ICD therapy in 19 patients. Epicardial procedures were performed in 16 of the 20 patients. VT target sites were located in the right ventricular (RV) endocardium (n = 11), the RV epicardium (n = 4), the left ventricular (LV) endocardium (n = 2) and the LV epicardium (n = 7). In 3 patients, the VT target sites were in close proximity to coronary arteries, limiting ablation. During follow-up, VTs recurred in 11 patients, and repeated ablations were performed in 9 patients. Allowing for multiple procedures, 19 of the 20 patients remained free of VT recurrence after a median follow-up of 18 months [Q1-Q3: 5-60 months]. CONCLUSIONS: Patients with DSP cardiomyopathy often have biventricular involvement, and ablation procedures often require ablation in both ventricles and the epicardium. Recurrences are not uncommon, and the pathologic substrate can be located in close proximity to epicardial coronary arteries, limiting the success rate of ablations.

Anatomy of the Ventricular Outflow Tracts: An Electrophysiology Perspective.

Outflow tract ventricular arrhythmias are the most common type of idiopathic ventricular arrhythmia. A systematic understanding of the outflow tract anatomy improves procedural efficacy and enables electrophysiologists to anticipate and prevent complications. This review emphasizes the three-dimensional spatial relationships between the ventricular outflow tracts using seven anatomical principles. In turn, each principle is elaborated on from a clinical perspective relevant for the practicing electrophysiologist. The developmental anatomy of the outflow tracts is also discussed and reinforced with a clinical case.

Mayo Clinic VT calculator: A practical tool for accurate wide complex tachycardia differentiation.

The discrimination of ventricular tachycardia (VT) versus supraventricular wide complex tachycardia (SWCT) via 12-lead electrocardiogram (ECG) is crucial for achieving appropriate, high-quality, and cost-effective care in patients presenting with wide QRS complex tachycardia (WCT). Decades of rigorous research have brought forth an expanding arsenal of applicable manual algorithm methods for differentiating WCTs. However, these algorithms are limited by their heavy reliance on the ECG interpreter for their proper execution. Herein, we introduce the Mayo Clinic ventricular tachycardia calculator (MC-VTcalc) as a novel generalizable, accurate, and easy-to-use means to estimate VT probability independent of ECG interpreter competency. The MC-VTcalc, through the use of web-based and mobile device platforms, only requires the entry of computerized measurements (i.e., QRS duration, QRS axis, and T-wave axis) that are routinely displayed on standard 12-lead ECG recordings.