Association between vectorcardiographic QRS area and incident heart failure diagnosis and mortality among patients with left bundle branch block: A register-based cohort study

QRS 3D Voltage-Time Integral in Narrow QRS Complex - Establishing the Normal Reference Range

Background

Vectorcardiographic 3D QRS voltage-time integral (VTI QRS-3D ) is a novel marker of ventricular dyssynchrony pertinent for cardiac resynchronization therapy. It may have additional clinical utility but its normal reference ranges have not been established. We sought to define reference ranges for VTI QRS-3D in healthy individuals.

Methods

We retrospectively analyzed 12-lead ECGs of healthy adults (2010-2014) and compared them to patients with cardiomyopathy with reduced ejection fraction (EF) <50%. Using the Kors matrix, 12-lead ECGs with QRS duration ≤120 ms were converted to vectorcardiographic X, Y, and Z leads. VTI QRS-3D was calculated as the instantaneous root-mean-square (3D) voltage integrated over the QRS duration. Reference range limits were defined as the 2.5th to 97.5th percentiles respectively for healthy females and males in age groups 18-34, 35-54 and ≥55 years.

Results

The study included 468 healthy adults (age 44.6 ± 17.0 years; 63.9% female) and 314 patients with cardiomyopathy (age 62.1 ± 14.0 years; 34.4% female). VTI QRS-3D was significantly larger in the cardiomyopathy patients compared to the healthy population (48.2±21.4 vs. 38.1±9.3 µVs, p<0.0001). Increased age and female sex were significant predictors of lower VTI QRS-3D in the healthy population (both p<0.0001). VTI QRS-3D reference ranges for respective age groups for healthy females were 23.2-55.0, 23.9-56.4 and 19.6-50.9 µVs, and for healthy males were 29.9-57.2, 28.2-56.7 and 21.4-55.9 µVs.

Conclusion

VTI QRS-3D is higher at younger age in healthy population, male sex and in patients having cardiomyopathy with reduced EF. Age and sex need to be accounted for using VTI QRS-3D as a marker for structural heart disease.

The Danish Nationwide Electrocardiogram (ECG) Cohort

The electrocardiogram (ECG) is a non-invasive diagnostic tool holding significant clinical importance in the diagnosis and risk stratification of cardiac disease. However, access to large-scale, population-based digital ECG data for research purposes remains limited and challenging. Consequently, we established the Danish Nationwide ECG Cohort to provide data from standard 12-lead digital ECGs in both pre- and in-hospital settings, which can be linked to comprehensive Danish nationwide administrative registers on health and social data with long-term follow-up. The Danish Nationwide ECG Cohort is an open real-world cohort including all patients with at least one digital pre- or in-hospital ECG in Denmark from January 01, 2000, to December 31, 2021. The cohort includes data on standardized and uniform ECG diagnostic statements and ECG measurements including global parameters as well as lead-specific measures of waveform amplitudes, durations, and intervals. Currently, the cohort comprises 2,485,987 unique patients with a median age at the first ECG of 57 years (25th-75th percentiles, 40-71 years; males, 48%), resulting in a total of 11,952,430 ECGs. In conclusion, the Danish Nationwide ECG Cohort represents a novel and extensive population-based digital ECG dataset for cardiovascular research, encompassing both pre- and in-hospital settings. The cohort contains ECG diagnostic statements and ECG measurements that can be linked to various nationwide health and social registers without loss to follow-up.

Machine learning derived ECG risk score improves cardiovascular risk assessment in conjunction with coronary artery calcium scoring

Background

Precision estimation of cardiovascular risk remains the cornerstone of atherosclerotic cardiovascular disease (ASCVD) prevention. While coronary artery calcium (CAC) scoring is the best available non-invasive quantitative modality to evaluate risk of ASCVD, it excludes risk related to prior myocardial infarction, cardiomyopathy, and arrhythmia which are implicated in ASCVD. The high-dimensional and inter-correlated nature of ECG data makes it a good candidate for analysis using machine learning techniques and may provide additional prognostic information not captured by CAC. In this study, we aimed to develop a quantitative ECG risk score (eRiS) to predict major adverse cardiovascular events (MACE) alone, or when added to CAC. Further, we aimed to construct and validate a novel nomogram incorporating ECG, CAC and clinical factors for ASCVD.

Methods

We analyzed 5,864 patients with at least 1 cardiovascular risk factor who underwent CAC scoring and a standard ECG as part of the CLARIFY study (ClinicalTrials.gov Identifier: NCT04075162). Events were defined as myocardial infarction, coronary revascularization, stroke or death. A total of 649 ECG features, consisting of measurements such as amplitude and interval measurements from all deflections in the ECG waveform (53 per lead and 13 overall) were automatically extracted using a clinical software (GE Muse™ Cardiology Information System, GE Healthcare). The data was split into 4 training (S_tr) and internal validation (S_v) sets [S_tr (1): S_v (1): 50:50; S_tr (2): S_v (2): 60:40; S_tr (3): S_v (3): 70:30; S_tr (4): S_v (4): 80:20], and the results were compared across all the subsets. We used the ECG features derived from S_tr to develop eRiS. A least absolute shrinkage and selection operator-Cox (LASSO-Cox) regularization model was used for data dimension reduction, feature selection, and eRiS construction. A Cox-proportional hazards model was used to assess the benefit of using an eRiS alone (M_ecg), CAC alone (M_cac) and a combination of eRiS and CAC (M_ecg+cac) for MACE prediction. A nomogram (M_nom) was further constructed by integrating eRiS with CAC and demographics (age and sex). The primary endpoint of the study was the assessment of the performance of M_ecg, M_cac, M_ecg+cac and M_nom in predicting CV disease-free survival in ASCVD.

Findings

Over a median follow-up of 14 months, 494 patients had MACE. The feature selection strategy preserved only about 18% of the features that were consistent across the various strata (S_tr). The M_ecg model, comprising of eRiS alone was found to be significantly associated with MACE and had good discrimination of MACE (C-Index: 0.7, p = <2e-16). eRiS could predict time-to MACE (C-Index: 0.6, p = <2e-16 across all S_v). The M_ecg+cac model was associated with MACE (C-index: 0.71). Model comparison showed that M_ecg+cac was superior to M_ecg (p = 1.8e-10) or M_cac (p < 2.2e-16) alone. The M_nom, comprising of eRiS, CAC, age and sex was associated with MACE (C-index 0.71). eRiS had the most significant contribution, followed by CAC score and other clinical variables. Further, M_nom was able to identify unique patient risk-groups based on eRiS, CAC and clinical variables.

Conclusion

The use of ECG features in conjunction with CAC may allow for improved prognostication and identification of populations at risk. Future directions will involve prospective validation of the risk score and the nomogram across diverse populations with a heterogeneity of treatment effects.

The relationship between vitamin B12 levels and electrocardiographic ventricular repolarization markers

BACKGROUND

it has been shown that vitamin B12 deficiency, which can cause hematological and neuropsychiatric disorders, may also be associated with cardiac autonomic dysfunction, heart rate variability, endothelial dysfunction, and a decrease in myocardial deformation.

AIMS

the aim of our study is to evaluate the relationship between vitamin B12 levels and electrocardiographic repolarization disorders, which are indicators of arrhythmogenic predisposition in healthy individuals.

METHODS

our study population consisted of 214 healthy adults. Considering the distribution of vitamin B12 levels and accepting 25 % and 75 % percentiles as the cut-off values, the participants were divided into 3 groups. Laboratory, echocardiography and electrocardiography (ECG) measurements were compared between three groups. ECG measurements were performed manually and Tpeak-Tend (Tp-e), Tp-e corrected (Tp-ec), QT and QT corrected (QTc) intervals were calculated.

RESULTS

the patients in Group 1 (vitamin B12 < 253 pg/ml) were found to have significantly higher QT and QTc dispersions, Tp-e interval, Tp-e/QT and Tp-e/QTc ratios when compared to those in Group 2 (253 pg/ml < vitamin B12 > 436 pg/ml) and Group 3 (vitamin B12 > 436 pg/ml). On the other hand, a negative significant correlation was detected between vitamin B12 levels and Tp-e, Tp-e/QT, Tp-e/QTc ratios, QT and QTc dispersions.

CONCLUSION

a low level of vitamin B12 in healthy individuals can be a significant indicator of arrhythmogenic susceptibility. A close follow-up of these subjects in terms of arrhythmogenic predisposition can be useful.