Delayed QRS transition in the precordial leads of an electrocardiogram as a predictor of sudden cardiac death in the general population

Predicting long-term risk of sudden cardiac death with automatic computer-interpretations of electrocardiogram

Background

Computer-interpreted electrocardiogram (CIE) data is provided by almost all commercial software used to capture and store digital electrocardiograms. CIE is widely available, inexpensive, and accurate. We tested the potential of CIE in long-term sudden cardiac death (SCD) risk prediction.

Methods

This is a retrospective of 8,568 consecutive patients treated for acute coronary syndrome. The primary endpoint was five-year occurrence of SCDs or equivalent events (SCDs aborted by successful resuscitation or adequate ICD therapy). CIE statements were extracted from summary statements and measurements made by the GE Muse 12SL algorithm from ECGs taken during admission. Three supervised machine learning algorithms (logistic regression, extreme gradient boosting, and random forest) were then used for analysis to find risk features using a random 70/30% split for discovery and validation cohorts.

Results

Five-year SCD occurrence rate was 3.3% (n = 287). Regardless of the used ML algorithm, the most significant risk ECG risk features detected by the CIE included known risk features such as QRS duration and factors associated with QRS duration, heart rate-corrected QT time (QTc), and the presence of premature ventricular contractions (PVCs). Risk score formed by using most significant CIE features associated with the risk of SCD despite adjusting for any clinical risk factor (including left ventricular ejection fraction). Sensitivity of CIE data to correctly identify patients with high risk of SCD (over 10% 5-year risk of SCD) was usually low, but specificity and negative prediction value reached up to 96.9% and 97.3% when selecting only the most significant features identified by logistic regression modeling (p-value threshold <0.01 for accepting features in the model). Overall, CIE data showed a modest overall performance for identifying high risk individuals with area under the receiver operating characteristic curve values ranging between 0.652 and 0.693 (highest for extreme gradient boosting and lowest for logistic regression).

Conclusion

This proof-of-concept study shows that automatic interpretation of ECG identifies previously validated risk features for SCD.

Simple models vs. deep learning in detecting low ejection fraction from the electrocardiogram

Aims

Deep learning methods have recently gained success in detecting left ventricular systolic dysfunction (LVSD) from electrocardiogram (ECG) waveforms. Despite their high level of accuracy, they are difficult to interpret and deploy broadly in the clinical setting. In this study, we set out to determine whether simpler models based on standard ECG measurements could detect LVSD with similar accuracy to that of deep learning models.

Methods and results

Using an observational data set of 40 994 matched 12-lead ECGs and transthoracic echocardiograms, we trained a range of models with increasing complexity to detect LVSD based on ECG waveforms and derived measurements. The training data were acquired from the Stanford University Medical Center. External validation data were acquired from the Columbia Medical Center and the UK Biobank. The Stanford data set consisted of 40 994 matched ECGs and echocardiograms, of which 9.72% had LVSD. A random forest model using 555 discrete, automated measurements achieved an area under the receiver operator characteristic curve (AUC) of 0.92 (0.91-0.93), similar to a deep learning waveform model with an AUC of 0.94 (0.93-0.94). A logistic regression model based on five measurements achieved high performance [AUC of 0.86 (0.85-0.87)], close to a deep learning model and better than N-terminal prohormone brain natriuretic peptide (NT-proBNP). Finally, we found that simpler models were more portable across sites, with experiments at two independent, external sites.

Conclusion

Our study demonstrates the value of simple electrocardiographic models that perform nearly as well as deep learning models, while being much easier to implement and interpret.

Electrical Synchrony Optimization for Left Bundle Branch Area Pacing in Patients With Bradycardia and Heart Failure

Left bundle branch area pacing (LBBAP) has emerged as a promising physiological pacing modality. This study was designed to investigate the acute impact of the atrioventricular delay (AVD) on cardiac electrical characteristics and identify an optimal range of AVDs for LBBAP to achieve electrical atrioventricular and interventricular synchrony. Patients indicated for ventricular or biventricular pacing were studied during routine follow-ups at least 3 months after LBBAP implantation. Patients were excluded if they had a complete AV block or persistent atrial fibrillation. AVD was programed from 40 to 240 ms or until intrinsic conduction occurred. Optimal AVD was determined by the electrocardiography criteria, including QRS duration, reduced R-wave in lead V1, reduced notching or slurring in lateral leads, and more desirable precordial QRS transition. A total of 38 patients (age 68.7 ± 10.3 years; 16 male (42%); 18 dual-chamber pacemakers and 20 cardiac resynchronization therapy devices; average follow-up period 15.1 ± 10.2 months) were included. The fusion of LBBAP and intrinsic right ventricular conduction occurred in 21 patients with corresponding optimal AVD determined. A great proportion (∼85%) of the optimal AVDs ranged from 50% to 80% of the observed atrium-to-left bundle branch-sensing (A-LBBS) intervals. The linear correlation between the optimal AVD and corresponding A-LBBS interval (optimal AVD = 0.84 × [A-LBSs interval] - 36 ms) produced R = 0.86 and p <0.0001. In conclusion, AVD selection during LBBAP greatly impacted the ventricular electrical characteristics and the optimal AVD was linearly correlated with the corresponding A-LBBS interval.

Association between electrocardiographic QRS transition zone and mortality from all causes and cardiovascular diseases: A systematic review and meta-analysis

AIMS

To investigate whether clockwise rotation (CWR) and counterclockwise rotation (CCWR) of electrocardiographic QRS transition zone is associated with mortality from all causes and cardiovascular diseases (CVD).

METHODS

Studies were identified from searching of PubMed, EMBASE and the reference lists of relevant papers. Summary multivariate-adjusted hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs) and 95% prediction intervals (PIs) were computed through meta-analysis.

RESULTS

A total of five observational cohort studies fulfilled the inclusion criteria, which included 47,252 participants from the general population (8.8% CWR; 44.1% CCWR). Pooling data revealed that CWR was significantly associated with the increased risk of all-cause mortality (HR, 1.18; 95% CI: 1.12-1.24; 95% PI: 1.03-1.37) and CVD mortality (HR, 1.18; 95% CI: 1.08-1.29; 95% PI: 0.98-1.42) compared to NR pattern, with low heterogeneity among studies (P = 0.29, I² = 20%; P = 0.37; I² = 7%; respectively). However, CCWR was inversely associated with the risk of all-cause mortality (HR, 0.92; 95% CI: 0.89-0.95; 95% PI: 0.80-1.05) with low heterogeneity (P = 0.14; I² = 43%), while no significant association existed between CCWR and CVD mortality (HR, 0.89; 95% CI: 0.77-1.02; 95% PI: 0.53-1.48) with high heterogeneity (P < 0.01; I² = 78%).

CONCLUSION

Our meta-analysis demonstrated CWR was positively associated with higher risk of mortality from all-cause and CVD, while CCWR was negatively associated with the risk of all-cause mortality and no significant association with CVD mortality. These findings suggested that QRS transition zone carries important prognostic value, more attention should be paid in clinical practice.

QRS transitional zone rotations and the risk of atrial fibrillation: the Suita Study

ECG screening can detect people at risk of developing atrial fibrillation (AF). Recent literature indicated that QRS transitional zone rotations could predict several cardiovascular events. Herein, we investigated the association between QRS transitional zone rotations and the future risk of AF. This prospective cohort study included 6794 participants (3178 men and 3616 women), aged 30-84 years, from the urban Japanese city of Suita. QRS transitional zone rotations were diagnosed by ECG during baseline, while AF was diagnosed by ECG, hospital records, and checkups during follow-up. The Cox regression was used to compute the sex-specified hazard ratios (HRs) and 95% confidence intervals (CIs) of incident AF for participants with counterclockwise and clockwise QRS transitional zone rotations compared to those with normal rotation. Within a median follow-up period of 14.6 years, 311 participants (206 men and 105 women) developed AF. Counterclockwise rotation was associated with the reduced risk of AF among men, but not women, in the age-adjusted model: HR (95% CI) = 0.66 (0.44, 0.98) and the multivariable-adjusted model: HR (95% CI) = 0.65 (0.43, 0.97). Clockwise rotation was not associated with AF risk in either sex. To the best of our knowledge, this is the first study to indicate that counterclockwise rotation could be associated with the reduced risk of AF in men. More studies are needed to confirm our findings and elucidate possible mechanisms.

Poor R-wave progression as a predictor of sudden cardiac death in general population and subjects with coronary artery disease

BACKGROUND

Poor R wave progression (PRWP) is a common clinical finding in the standard 12-lead ECG, but its prognostic significance is unclear.

OBJECTIVE

The purpose of this study was to examine the prognosis associated with PRWP in terms of sudden cardiac death (SCD), cardiac death, and overall mortality in general population subjects with and without coronary artery disease (CAD).

METHODS

Data and 12-lead ECGs were collected from a Finnish general population health examination survey conducted during 1978-1980 with follow-up until 2011. The study population consisted of 6854 subjects. Main end-points were SCD, cardiac death, and overall mortality. PRWP was defined as R-wave amplitude ≤ 0.3mV in V₃ and R-wave amplitude in V₂ ≤ R-wave amplitude in V₃.

RESULTS

PRWP occurred in 213 subjects (3.1%). During the follow-up of 24.3 ± 10.4 years 3723 subjects died (54.3%). PRWP was associated with older age, higher prevalence of heart failure and CAD, and beta blocker medication. In multivariate analyses, PRWP was associated with SCD (hazard ratio [HR] 2.13, 95% confidence interval [CI] 1.34-3.39), cardiac death (HR 1.75, 95% CI 1.35-2.15), and all-cause mortality (HR 1.29, 95% CI 1.08-1.54). In the subgroup with CAD, PRWP had a stronger association with cardiac mortality (HR 1.71, 95% CI 1.19-2.46) compared to the subgroup without CAD, whilst the association with SCD was significant only in subgroup with CAD (HR 2.62, 95% CI 1.38-4.98).

CONCLUSION

PRWP was associated with adverse prognosis in general population and with SCD among subjects with CAD.

Predicting sudden cardiac death in a general population using an electrocardiographic risk score

OBJECTIVE

We investigated whether combining several ECG abnormalities would identify general population subjects with a high sudden cardiac death (SCD) risk.

METHODS

In a sample of 6830 participants (mean age 51.2±13.9 years; 45.5% male) in the Mini-Finland Health Survey, a general population cohort representative of the Finnish adults aged ≥30 years conducted in 1978-1980, we examined their ECGs, following subjects for 24.3±10.4 years. We analysed the association between individual ECG abnormalities and 10-year SCD risk and developed a risk score using five ECG abnormalities independently associated with SCD risk: heart rate >80 beats per minute, PR duration >220 ms, QRS duration >110 ms, left ventricular hypertrophy and T-wave inversion. We validated the score using an external general population cohort of 10 617 subjects (mean age 44.0±8.5 years; 52.7% male).

RESULTS

No ECG abnormalities were present in 4563 subjects (66.8%), while 96 subjects (1.4%) had ≥3 ECG abnormalities. After adjusting for clinical factors, the SCD risk increased progressively with each additional ECG abnormality. Subjects with ≥3 ECG abnormalities had an HR of 10.23 (95% CI 5.29 to 19.80) for SCD compared with those without abnormalities. The risk score similarly predicted SCD risk in the validation cohort, in which subjects with ≥3 ECG abnormalities had HR 10.82 (95% CI 3.23 to 36.25) for SCD compared with those without abnormalities.

CONCLUSION

The ECG risk score successfully identified general population subjects with a high SCD risk. Combining ECG risk markers may improve the risk stratification for SCD.

The role of implantable cardioverter-defibrillators and sudden cardiac death prevention: indications, device selection, and outcome

Multiple randomized multicentre clinical trials have established the role of the implantable cardioverter-defibrillator (ICD) as the mainstay in the treatment of ventricular tachyarrhythmias and sudden cardiac death (SCD) prevention. These trials have focused mainly on heart failure patients with advanced left ventricular dysfunction and were mostly conducted two decades ago, whereas a more recent trial has provided conflicting results. Therefore, much remains to be determined on how best to balance the identification of patients at high risk of SCD together with who would benefit most from ICD implantation in a contemporary setting. Implantable cardioverter-defibrillators have also evolved from the simple, defibrillation-only devices implanted surgically to more advanced technologies of multi-chamber devices, with physiologic bradycardic pacing, including cardiac resynchronization therapy, atrial and ventricular therapeutic pacing algorithms, and subcutaneous ICDs. These multiple options necessitate individualized approach to device selection and programming. This review will focus on the current knowledge on selection of patients for ICD treatment, device selection and programming, and future directions of implantable device therapy for SCD prevention.

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Re-evaluating the electro-vectorcardiographic criteria for left bundle branch block

The criteria for left bundle branch block have gained growing interest in the last few years. In this overview, we discuss diagnostic and prognostic aspects of different criteria. It was already shown that stricter criteria, including longer QRS duration and slurring/notching of the QRS, better identify responders to cardiac resynchronization therapy. We also include aspects of ST/T concordance and discordance and vectorcardiography, which could further improve in the fine-tuning of the left bundle branch criteria.

Electrical risk score beyond the left ventricular ejection fraction: prediction of sudden cardiac death in the Oregon Sudden Unexpected Death Study and the Atherosclerosis Risk in Communities Study

Aims

There is an urgent need to extend sudden cardiac death (SCD) risk stratification beyond the left ventricular ejection fraction (LVEF). We evaluated whether a cumulative electrocardiogram (ECG) risk score would improve identification of individuals at high risk of SCD.

Methods and results

In the community-based Oregon Sudden Unexpected Death Study (catchment population ∼1 million), 522 SCD cases with archived 12-lead ECG available (65.3 ± 14.5 years, 66% male) were compared with 736 geographical controls to assess the incremental value of multiple ECG parameters in SCD prediction. Heart rate, LV hypertrophy, QRS transition zone, QRS-T angle, QTc, and Tpeak-to-Tend interval remained significant in the final model, which was externally validated in the Atherosclerosis Risk in Communities (ARIC) Study. Sixteen percent of cases and 3% of controls had ≥4 abnormal ECG markers. After adjusting for clinical factors and LVEF, increasing ECG risk score was associated with progressively greater odds of SCD. Overall, subjects with ≥4 ECG abnormalities had an odds ratio (OR) of 21.2 for SCD [95% confidence interval (CI) 9.4-47.7; P < 0.001]. In the LVEF >35% subgroup, the OR was 26.1 (95% CI 9.9-68.5; P < 0.001). The ECG risk score increased the C-statistic from 0.625 to 0.753 (P < 0.001), with net reclassification improvement of 0.319 (P < 0.001). In the ARIC cohort validation, risk of SCD associated with ≥4 ECG abnormalities remained significant after multivariable adjustment (hazard ratio 4.84; 95% CI 2.34-9.99; P < 0.001; C-statistic improvement 0.759-0.774; P = 0.019).

Conclusion

This novel cumulative ECG risk score was independently associated with SCD and was particularly effective for LVEF >35% where risk stratification is currently unavailable. These findings warrant further evaluation in prospective clinical investigations.

Counterclockwise and Clockwise Rotation of QRS Transitional Zone: Prospective Correlates of Change and Time-Varying Associations With Cardiovascular Outcomes

BACKGROUND

A few studies have recently reported clockwise and counterclockwise rotations of QRS transition zone as predictors of mortality. However, their prospective correlates and associations with individual cardiovascular disease (CVD) outcomes are yet to be investigated.

METHODS AND RESULTS

Among 13 567 ARIC (Atherosclerosis Risk in Communities) study participants aged 45 to 64 years, we studied key correlates of changes in the status of clockwise and counterclockwise rotation over time as well as the association of rotation status with incidence of coronary heart disease (2408 events), heart failure (2196 events), stroke (991 events), composite CVD (4124 events), 898 CVD deaths, and 3469 non-CVD deaths over 23 years of follow-up. At baseline, counterclockwise rotation was most prevalent (52.9%), followed by no (40.5%) and clockwise (6.6%) rotation. Of patients with no rotation, 57.9% experienced counterclockwise or clockwise rotation during follow-up, with diabetes mellitus and black race significantly predicting clockwise and counterclockwise conversion, respectively. Clockwise rotation was significantly associated with higher risk of heart failure (hazard ratio, 1.20; 95% confidence interval [CI], 1.02-1.41) and non-CVD death (hazard ratio, 1.28; 95% CI, 1.12-1.46) after adjusting for potential confounders including other ECG parameters. On the contrary, counterclockwise rotation was significantly related to lower risk of composite CVD (hazard ratio, 0.93; 95% CI, 0.87-0.99]), CVD mortality (hazard ratio, 0.76; 95% CI, 0.65-0.88), and non-CVD deaths (hazard ratio, 0.92; 95% CI, 0.85-0.99 [borderline significance with heart failure]).

CONCLUSIONS

Counterclockwise rotation, the most prevalent QRS transition zone pattern, demonstrated the lowest risk of CVD and mortality, whereas clockwise rotation was associated with the highest risk of heart failure and non-CVD mortality. These results have implications on how to interpret QRS transition zone rotation when ECG was recorded.

Cardiac structural and functional profile of patients with delayed QRS transition zone and sudden cardiac death

AIMS

Delayed QRS transition zone in the precordial leads of the 12-lead electrocardiogram (ECG) has been recently associated with increased risk of sudden cardiac death (SCD), but the underlying mechanisms are unknown. We correlated echocardiographic findings with ECG and clinical characteristics to investigate how alterations in cardiac structure and function contribute to this risk marker.

METHODS AND RESULTS

From the ongoing population-based Oregon Sudden Unexpected Death Study (catchment population ∼1 million), SCD cases with prior ECG available (n = 627) were compared with controls (n = 801). Subjects with delayed transition at V5 or later were identified, and clinical and echocardiographic patterns associated with delayed transition were analysed. Delayed transition was present in 31% of the SCD cases and 17% of the controls. These subjects were older and more likely to have cardiovascular risk factors and history of myocardial infarction. Delayed transition was associated with increased left ventricular (LV) mass (122.7 ± 40.2 vs. 102.9 ± 33.7 g/m2; P < 0.001), larger LV diameter (53.3 ± 10.4 vs. 49.2 ± 8.0 mm; P < 0.001), and lower LV ejection fraction (LVEF) (46.4 ± 15.7 vs. 55.6 ± 12.5%; P < 0.001). In multivariate analysis, delayed transition was independently associated with myocardial infarction, reduced LVEF, and LV hypertrophy. The association between delayed transition and SCD was independent of the LVEF (OR 1.57; 95% CI 1.04-2.38; P = 0.032).

CONCLUSION

The underpinnings of delayed QRS transition zone extend beyond previous myocardial infarction and reduced LVEF. Since the association with sudden death is independent of these factors, this novel marker of myocardial electrical remodelling should be explored as a potential risk predictor of SCD.

12-Lead electrocardiogram as a predictor of sudden cardiac death: from epidemiology to clinical practice

Sudden cardiac death (SCD) causes a high burden of premature deaths in the population affecting subjects of all ages. The identification of subjects at high risk for SCD is of great importance as the prevention of many of these events would be possible with the treatment of underlying cardiac diseases and the use of implantable cardioverter-defibrillators (ICD). However, the current selection of patients for ICD therapy is based solely on left ventricular ejection fraction, and thus a substantial portion of patients at high risk does not qualify for the therapy. Role of the standard electrocardiogram (ECG) in SCD risk stratification has been under active research during the last decade and multiple abnormalities of depolarization and repolarization on the ECG associated with an increased risk of SCD have been identified. In this review, we describe the basic pathophysiological principles behind these changes. We also review the current knowledge of the prognostic significance of ECG predictors of SCD in the general population, and in patients with coronary heart disease (CHD), heart failure, cardiomyopathies, and in inheritable arrhythmia syndromes. Also, insights into the novel digital ECG signal processing techniques are provided.

Sudden Cardiac Death Risk Stratification - An Update

Sudden cardiac death (SCD) remains a major public health problem worldwide, yet current methods to identify those at greatest risk are inadequate. High-risk individuals may benefit from potentially life-saving treatment, such as insertion of an implantable-cardioverter defibrillator (ICD). However, such treatments are expensive and have their own associated risks. Furthermore, most cases of SCD occur in the general adult population who may be relatively asymptomatic but yet have an underlying predisposition to SCD. Hence, there is great interest and clinical need in improving methods for risk stratification of SCD to identify those at greatest risk and implement the most appropriate treatment. This review provides an update on current risk-stratification methods for SCD in high-risk groups, in particular patients with reduced left ventricular function following acute myocardial infarction and those with non-ischaemic dilated cardiomyopathy, and highlights some novel methods that may have a role to play in future risk-stratification schemes. Approaches and challenges for SCD risk stratification among the general public are also discussed.