The objective of this study was to test the vectorelectrocardiographic T-wave characteristics for their associations with oxygen consumption (VO2) and physical performance during a maximal cardiopulmonary exercise test (CPET) in highly trained cross-country skiers. Male highly trained cross-country skiers (n = 30) performed the maximal CPET on the bicycle ergospirometric \"Oxycon Pro\" system with simultaneous oxygen consumption (VO2) and electrocardiogram recording. The measurements were done at rest; the stage preceding anaerobic threshold (preAnT); peak load; and recovery. The anaerobic threshold was estimated by respiratory exchange ratio. Physical performance was estimated by maximal oxygen consumption (VO2max/kg). VECG characteristics were calculated using Kors transformation procedure. During the test, the magnitudes of T-vector, Tx and Ty components decreased until preAnT, then stayed relatively stable until peak load, and reversed during recovery. In univariate linear regression analysis, T-vector amplitude and Tx, Ty and Tz magnitudes were associated with VO2/kg during the test (p < 0.010). The baseline T-vector characteristics were not associated with physical performance. At the preAnT stage, Tx and T-vector amplitude were associated with VO2max/kg (RC 12.70, 95% CI 0.68-24.73, p = 0.039 and RC 10.64, 95% CI 1.62-19.67, p = 0.023, respectively).

BACKGROUND: Data on the prognostic significance of temporal variability of spatial heterogeneity of electrocardiographic repolarization in coronary artery disease (CAD) are limited.
OBJECTIVE: The purpose of this study was to evaluate the prognostic value of temporal variability of T-wave morphology analyzed from a 5-minute resting electrocardiogram in CAD.
METHODS: The standard deviation (SD) of T-wave morphology dispersion (TMD-SD) and the SD of total cosine R-to-T were analyzed on a beat-to-beat basis from a 5-minute period of the standard resting 12-lead electrocardiogram obtained before the clinical stress test in 1702 patients with angiographically verified CAD and well-preserved left ventricular function.
RESULTS: During an average of 8.7 ± 2.2 years of follow-up, 60 patients experienced sudden cardiac death/arrest (SCD/SCA) (3.5%), 69 patients nonsudden cardiac death (NSCD) (4.1%), and 161 patients noncardiac death (9.5%). TMD-SD was significantly higher in patients who experienced SCD/SCA than in other patients (1.72 ± 2.00 vs 1.12 ± 1.75; P = .01) and higher in patients who succumbed to NSCD than in other patients (1.57 ± 1.74 vs 1.12 ± 1.76; P = .04), but it did not differ significantly between patients who experienced noncardiac death and those without such an event (1.16 ± 1.42 vs 1.14 ± 1.79; P = .86). In the Cox multivariable hazards model, TMD-SD retained its significant association with the risk of SCD/SCA (hazard ratio 1.119; 95% confidence interval 1.015-1.233; P = .024) but not with the risk of NSCD (hazard ratio 1.089; 95% confidence interval 0.983-1.206; P = .103).
CONCLUSIONS: TMD-SD is independently associated with the long-term risk of SCD/SCA in patients with CAD.

BACKGROUND: Type 2 Diabetes Mellitus (T2DM) has become a major health concern with an increasing prevalence and is now one of the leading attributable causes of death globally. T2DM and cardiovascular disease are strongly associated and T2DM is an important independent risk factor for ischemic heart disease. T-wave abnormalities (TWA) on electrocardiogram (ECG) can indicate several pathologies including ischemia. In this study, we aimed to investigate the association between T2DM and T-wave changes using the Minnesota coding system.
METHODS: A cross-sectional study was conducted on the MASHAD cohort study population. All participants of the cohort population were enrolled in the study. 12-lead ECG and Minnesota coding system (codes 5-1 to 5-4) were utilized for T-wave observation and interpretation. Regression models were used for the final evaluation with a level of significance being considered at p < 0.05.
RESULTS: A total of 9035 participants aged 35-65 years old were included in the study, of whom 1273 were diabetic. The prevalence of code 5-2, 5-3, major and minor TWA were significantly higher in diabetics (p < 0.05). However, following adjustment for age, gender, and hypertension, the presence of TWAs was not significantly associated with T2DM (p > 0.05). Hypertension, age, and body mass index were significantly associated with T2DM (p < 0.05).
CONCLUSIONS: Although some T-wave abnormalities were more frequent in diabetics, they were not statistically associated with the presence of T2DM in our study.

BACKGROUND: The cardiotoxicity of prenatal exposure to mercury has been suggested in populations having regular contaminated seafood intake, though replications in the literature are inconsistent.
METHODS: The Timoun Mother-Child Cohort Study was set up in Guadeloupe, an island in the Caribbean Sea where seafood consumption is regular. At seven years of age, 592 children underwent a medical examination, including cardiac function assessment. Blood pressure (BP) was taken using an automated blood pressure monitor, heart rate variability (HRV, 9 parameters) and electrocardiogram (ECG) characteristics (QT, T-wave parameters) were measured using Holter cardiac monitoring during the examination. Total mercury concentrations were measured in cord blood at birth (median = 6.6 μg/L, N = 399) and in the children\'s blood at age 7 (median = 1.7 μg/L, N = 310). Adjusted linear and non-linear modelling was used to study the association of each cardiac parameter with prenatal and childhood exposures. Sensitivity analyses included co-exposures to lead and cadmium, adjustment for maternal seafood consumption, selenium and polyunsaturated fatty acids (n3-PUFAs), and for sporting activity.
RESULTS: Higher prenatal mercury was associated with higher systolic BP at 7 years of age (βlog2 = 1.02; 95% Confidence Interval (CI) = 0.10, 1.19). In boys, intermediate prenatal exposure was associated with reduced overall HRV and parasympathetic activity, and longer QT was observed with increasing prenatal mercury (βlog2 = 4.02; CI = 0.48, 7.56). In girls, HRV tended to increase linearly with prenatal exposure, and no association was observed with QT-wave related parameters. Mercury exposure at 7 years was associated with decreased BP in girls (βlog2 = -1.13; CI = -2.22, -0.004 for diastolic BP). In boys, the low/high-frequency (LF/HF) ratio increased for intermediate levels of exposure.
CONCLUSIONS: Our study suggests sex-specific and non-monotonic modifications in some cardiac health parameters following prenatal exposure to mercury in pre-pubertal children from an insular fish-consuming population.

BACKGROUND: Periodic repolarization dynamics (PRD) is an electrocardiographic biomarker that quantifies low-frequency (LF) instabilities of repolarization. PRD is a strong predictor of mortality in patients with ischaemic and non-ischaemic cardiomyopathy. Until recently, two methods for calculating PRD have been proposed. The wavelet analysis has been widely tested and quantifies PRD in deg2 units by application of continuous wavelet transformation (PRDwavelet). The phase rectified signal averaging method (PRDPRSA) is an algebraic method, which quantifies PRD in deg. units. The correlation, as well as a conversion formula between the two methods remain unknown.
METHODS: The first step for quantifying PRD is to calculate the beat-to-beat change in the direction of repolarization, called dT°. PRD is subsequently quantified by means of either wavelet or PRSA-analysis. We simulated 1.000.000 dT°-signals. For each simulated signal we calculated PRD using the wavelet and PRSA-method. We calculated the ratio between PRDwavelet and PRDPRSA for different values of dT° and RR-intervals and applied this ratio in a real-ECG validation cohort of 455 patients after myocardial infarction (MI). We finally calculated the correlation coefficient between real and calculated PRDwavelet. PRDwavelet was dichotomized at the established cut-off value of ≥5.75 deg2.
RESULTS: The ratio between PRDwavelet and PRDPRSA increased with increasing heart-rate and mean dT°-values (p < 0.001 for both). The correlation coefficient between PRDwavelet and PRDPRSA in the validation cohort was 0.908 (95% CI 0.891-0.923), which significantly (p < 0.001) improved to 0.945 (95% CI 0.935-0.955) after applying the formula considering the ratio between PRDwavelet and PRDPRSA obtained from the simulation cohort. The calculated PRDwavelet correctly classified 98% of the patients as low-risk and 87% of the patients as high-risk and correctly identified 97% of high-risk patients, who died within the follow-up period.
CONCLUSIONS: This is the first analytical investigation of the different methods used to calculate PRD using simulated and clinical data. In this article we propose a novel algorithm for converting PRDPRSA to the widely validated PRDwavelet, which could unify the calculation methods and cut-offs for PRD.

A16-year-old female underwent tilt table testing, which resulted positive for reflex vasodepressive syncope. 12‑lead ECG during syncope showed T-wave inversion in infero-lateral leads, along with QTc interval increase >100 msec compared to baseline. These abnormalities rapidly disappeared in supine position with resumption of consciousness. Complete cardiac evaluation excluded heart disease. T-wave changes and moderate QTc prolongation are relatively common in young (mainly female) patients undergoing tilt table testing and they appear benign in nature. However, in a minority of cases, on the basis of the clinical context and after an accurate ECG analysis, further examinations may be warranted.

BACKGROUND: Implantable cardioverter-defibrillators (ICDs) need to reliably detect ventricular tachycardia (VT) and ventricular fibrillation (VF) while avoiding T-wave oversensing (TWOS), which is associated with a risk of inappropriate therapies. The incidence of TWOS with endovascular ICDs appears to differ between manufacturers.
OBJECTIVE: We aimed to evaluate the incidence and clinical consequences of TWOS with contemporary Medtronic and Boston Scientific ICDs.
METHODS: Consecutive patients implanted with a recent Medtronic or Boston Scientific ICD and remotely monitored at three French centers were included. All transmitted EGMs labelled as VF, VT, non-sustained VT (NSVT), or ventricular oversensing (Medtronic) were screened for TWOS.
RESULTS: Among 7589 transmitted episodes from 674 patients with a Boston Scientific ICD, we did not identify a single case of TWOS. Among 16,790 transmitted episodes from 1733 patients with a Medtronic ICD, we identified 60 patients (3.4%) with at least one episode of TWOS. In 46 patients, TWOS was intermittent (NSVT episodes). In the remaining 14 patients, TWOS resulted in 60 sustained episodes (completed counters). No inappropriate therapies were delivered in 12 of these patients because no therapies were programmed (in monitor zones, 11 episodes) or because therapies were inhibited by the morphology discriminator (Wavelet, 19 episodes) or by the anti-TWOS algorithm (26 episodes). Two patients received inappropriate therapies due to TWOS (0.1% of patients with Medtronic ICDs).
CONCLUSIONS: On review of 24,379 transmitted episodes from 2407 patients with endovascular ICDs, we found no case of TWOS with Boston Scientific devices, whereas TWOS was not uncommon with Medtronic devices. However, the risk of inappropriate therapy with Medtronic ICDs was very low (0.1%) due to the often intermittent nature of this phenomenon, the morphology discriminator, and the anti-TWOS algorithm.

Whereas the electrocardiogram (ECG) changes in hypokalemia are well known, they often receive less attention than the more striking features of hyperkalemia. Furthermore, there is a need for further discussion as to the subtleties of ECG changes that can aid in the differential diagnoses. This case study presents the ECG changes of a patient with severe hypokalemia due to diarrhea. It highlights how bifid T-waves in hypokalemia can be distinguished from other conditions such as coronary artery disease or pericarditis. Furthermore, it also shows the gradual reversal of ECG changes in the same patient when potassium is normalized.

T-wave analysis from standard electrocardiogram (ECG) remains one of the most available clinical and research methods for evaluating myocardial repolarization. T-wave morphology was recently evaluated to aid with diagnosis and characterization of diastolic dysfunction. Unfortunately, PDF stored ECG datasets limit additional numerical post-processing of ECG waveforms. In this study, we apply a simple custom process pipeline to extract and re-digitize T-wave signals and subject them to principal component analysis (PCA) to define primary T-wave shape variations.
We propose simple pre-processing and digitization algorithms programmable as a MATLAB tool using standard thresholding functions without the need for advanced signal analysis. To validate digitized datasets, we compared clinically standard measurements in 20 different ECGs with the original ECG machine interpreted values as a gold standard. Afterwards, we analyzed 212 individual ECGs for T-wave shape analysis using PCA.
The re-digitized signal was shown to preserve the original information as evidenced by excellent agreement between original - machine interpreted and re-digitized clinical variables including heart rate: bias ~ 1 bpm (95% CI: -1.0 to 3.5), QT interval: bias ~ 0.000 ms (95% CI: -0.012 to 0.012), PR interval: bias = -0.015 ms (95% CI: -0.015 to 0.003), and QRS duration: bias = -0.001 ms (95% CI: -0.007 to 0.006). PCA revealed that the first principal component universally modulates the T-wave height or amount of repolarization voltage regardless of the investigated ECG lead. The second and third principal components described variation in the T-wave peak onset and the T-wave peak morphology, respectively.
This study presents a straightforward method for re-digitizing ECGs stored in the PDF format utilized in many academic electronic medical record systems. This process can yield re-digitized lead specific signals which can be retrospectively analyzed using advanced custom post-processing numerical analysis independent of commercially available platforms.

Myocardial ischemia is a pathophysiological state characterized by inadequate perfusion of the myocardium, resulting in an imbalance between myocardial oxygen demand and supply. It is most commonly caused by coronary artery disease, in which atherosclerotic plaques lead to luminal narrowing and reduced blood flow to the heart. Myocardial ischemia can manifest as angina pectoris or silent myocardial ischemia and can progress to myocardial infarction or heart failure if left untreated. Diagnosis of myocardial ischemia typically involves a combination of clinical evaluation, electrocardiography and imaging studies. Electrocardiographic parameters, as assessed by 24 h Holter ECG monitoring, can predict the occurrence of major adverse cardiovascular events in patients with myocardial ischemia, independent of other risk factors. The T-waves in patients with myocardial ischemia have prognostic value for predicting major adverse cardiovascular events, and their electrophysiological heterogeneity can be visualized using various techniques. Combining the electrocardiographic findings with the assessment of myocardial substrate may offer a better picture of the factors that can contribute to cardiovascular death.