Recommendations for the Standardization and Interpretation of the Electrocardiogram

Determinants/Predictors of QT Abnormalities in Patients on Psychotropic Medications in a Nigerian Tertiary Hospital

Cardiovascular disease is a major global burden and a leading cause of premature death among patients with severe mental illness. Over time, research and clinical practice have paid increased attention to the impact of psychiatric medications on cardiac repolarization. In a resource-limited setting, it is common for psychotropic medications to be initiated and maintained in an outpatient setting without baseline or follow up ECG. This study evaluated the determinants and predictors of QT abnormalities among patient taking psychotropic drugs. We conducted a cross-sectional study in a population of 150 psychiatric patients on psychotropics and 75 controls. We studied the effects of various psychotropic drugs on QT dispersion (QTd) and corrected QT interval (QTc) as well as correlation with the types and dosages of psychotropic drugs used. All the subjects had detailed clinical examination and resting electrocardiogram (ECG) at 25 mm/sec done. QTc was determined using Bazett formula and QTd was determined by subtracting shortest from longest QT in 12-lead ECG. The prevalence of prolonged QTc and QTd as well as the mean QTc and QTd were significantly higher in patients than the control group. The mean QTc was significantly higher in patient on typical antipsychotics compared to those on atypical antipsychotics. Age, heart rate and antipsychotic dose in chlorpromazine equivalent were predictors of QTc with the heart rate being the most powerful predictor among them. Psychotropic drugs use is associated with QTc and QTd prolongation with age, heart rate and antipsychotic dose as predictors of QTc.

Interpreting Wide-Complex Tachycardia using Artificial Intelligence

BACKGROUND

Adopting artificial intelligence in medicine may improve speed and accuracy in patient diagnosis. We sought to develop an artificial intelligence (AI) algorithm to interpret wide complex tachycardia (WCT) electrocardiograms (ECG) and compare its diagnostic accuracy to cardiologists.

METHODS

Using 3330 WCT ECGs (2906 SVT and 424 VT), we created a training/validation (3131) and test set (199 ECGs). A convolutional neural network (CNN) structure using a modification of differentiable architecture search (DARTS), ZeroLess-DARTS, was developed to differentiate between SVT and VT.

RESULTS

The mean accuracy of electrophysiology (EP) cardiologists was 92.5% with a sensitivity of 91.7%, specificity of 93.4%, positive predictive value of 93.7%, negative predictive value of 91.7%. NonEP cardiologists had an accuracy of 73.2 ± 14.4% with a sensitivity, specificity, positive and negative predictive value of 59.8 ± 18.2%, 93.8 ± 3.7%, 93.6 ± 2.3%, and 73.2 ± 14.4%, respectively. AI had superior sensitivity and accuracy (91.9% and 93.0%, respectively) than NonEP cardiologists, and had similar performance of EP cardiologists. Mean time to interpret each ECG varied between 10.1-13.8 seconds for EP cardiologists and 3.1 -16.6 seconds for NonEP cardiologists. Conversely AI required a mean of 0.0092 ± 0.0035 seconds for each ECG interpretation.

CONCLUSIONS

AI appears to diagnose WCT with superior accuracy than Cardiologists and similar to those of Electrophysiologists. Using AI to assist with ECG interpretations may improve patient care.

Predicted Deleterious Variants in Cardiomyopathy Genes Prognosticate Mortality and Composite Outcomes in UK Biobank

BACKGROUND

Inherited cardiomyopathies present with broad variation of phenotype. Data are limited regarding genetic screening strategies and outcomes associated with predicted deleterious variants in cardiomyopathy-associated genes in the general population.

OBJECTIVES

The authors aimed to determine the risk of mortality and composite cardiomyopathy-related outcomes associated with predicted deleterious variants in cardiomyopathy-associated genes in the UK Biobank.

METHODS

Using whole exome sequencing data, variants in dilated, hypertrophic, and arrhythmogenic right ventricular cardiomyopathy-associated genes with at least moderate evidence of disease causality according to ClinGen Expert Panel curations were annotated using REVEL (≥0.65) and ANNOVAR (predicted loss-of-function) considering gene-disease mechanisms. Genotype-positive and genotype-negative groups were compared using time-to-event analyses for the primary (all-cause mortality) and secondary outcomes (diagnosis of cardiomyopathy; composite outcome of diagnosis of cardiomyopathy, heart failure, arrhythmia, stroke, and death).

RESULTS

Among 200,619 participants (age at recruitment 56.46 ± 8.1 years), 5,292 (2.64%) were found to host ≥1 predicted deleterious variants in cardiomyopathy-associated genes (CMP-G+). After adjusting for age and sex, CMP-G+ individuals had higher risk for all-cause mortality (HR: 1.13 [95% CI: 1.01-1.25]; P = 0.027), increased risk for being diagnosed with cardiomyopathy later in life (HR: 5.75 [95% CI: 4.58-7.23]; P < 0.0001), and elevated risk for composite outcome (HR: 1.29 [95% CI: 1.20-1.39]; P < 0.0001) than CMP-G- individuals. The higher risk for being diagnosed with cardiomyopathy and composite outcomes in the genotype-positive subjects remained consistent across all cardiomyopathy subgroups.

CONCLUSIONS

Adults with predicted deleterious variants in cardiomyopathy-associated genes exhibited a slightly higher risk of mortality and a significantly increased risk of developing cardiomyopathy, and cardiomyopathy-related composite outcomes, in comparison with genotype-negative controls.

Latest incidence and electrocardiographic predictors of atrial fibrillation: a prospective study from China

BACKGROUND

China bears the biggest atrial fibrillation (AF) burden in the world. However, little is known about the incidence and predictors of AF. This study aimed to investigate the current incidence of AF and its electrocardiographic (ECG) predictors in general community individuals aged over 60 years in China.

METHODS

This was a prospective cohort study, recruiting subjects who were aged over 60 years and underwent annual health checkups from April to July 2015 in four community health centers in Songjiang District, Shanghai, China. The subjects were then followed up from 2015 to 2019 annually. Data on sociodemographic characteristics, medical history, and the resting 12-lead ECG were collected. Kaplan-Meier curve was used for showing the trends in AF incidence and calculating the predictors of AF. Associations of ECG abnormalities and AF incidence were examined using Cox proportional hazard models.

RESULTS

This study recruited 18,738 subjects, and 351 (1.87%) developed AF. The overall incidence rate of AF was 5.2/1000 person-years during an observation period of 67,704 person-years. Multivariable Cox regression analysis indicated age (hazard ratio [HR], 1.07; 95% confidence interval [CI]: 1.06-1.09; P < 0.001), male (HR, 1.30; 95% CI: 1.05-1.62; P = 0.018), a history of hypertension (HR, 1.55; 95% CI: 1.23-1.95; P < 0.001), a history of cardiac diseases (HR, 3.23; 95% CI: 2.34-4.45; P < 0.001), atrial premature complex (APC) (HR, 2.82; 95% CI: 2.17-3.68; P < 0.001), atrial flutter (HR, 18.68; 95% CI: 7.37-47.31; P < 0.001), junctional premature complex (JPC) (HR, 3.57; 95% CI: 1.59-8.02; P = 0.002), junctional rhythm (HR, 18.24; 95% CI: 5.83-57.07; P < 0.001), ventricular premature complex (VPC) (HR, 1.76; 95% CI: 1.13-2.75, P = 0.012), short PR interval (HR, 5.49; 95% CI: 1.36-22.19; P = 0.017), right atrial enlargement (HR, 6.22; 95% CI: 1.54-25.14; P = 0.010), and pacing rhythm (HR, 3.99; 95% CI: 1.57-10.14; P = 0.004) were independently associated with the incidence of AF.

CONCLUSIONS

The present incidence of AF was 5.2/1000 person-years in the studied population aged over 60 years in China. Among various ECG abnormalities, only APC, atrial flutter, JPC, junctional rhythm, short PR interval, VPC, right atrial enlargement, and pacing rhythm were independently associated with AF incidence.

Incidence of persistent left bundle branch block after rapid-deployment aortic valve replacement

BACKGROUND

We aimed to evaluate the incidence, prognosis and predictive factors of new onset of persistent left bundle branch block(NOP-LBBB) after rapid-deployment aortic valve replacement(RD-AVR).

METHODS

This study was an observational, retrospective, single-center study of 274 consecutive patients with no baseline ventricular conduction disorder and no previous permanent pacemaker implantation(PPI) who underwent RD-AVR with an INTUITY valve(n=55) and INTUITY Elite Valve(n=219). Twelve-lead electrocardiography and transthoracic echocardiography were performed preoperatively, upon discharge, at 1-month and 1-year intervals. The incidence, prognosis, and predictive factors of NOP-LBBB were evaluated.

RESULTS

NOP-LBBB occurred in 58 patients(21.2%) upon discharge. In multivariate analysis, age (p <0.01), Intuity valve diameter ≥ 23 mm (p = 0.02) and INTUITY ELITE implantation(p=0.01) were independent predictors of NOP-LBBB. By 1:1 propensity matching analysis between the NOP-LBBB group and the control group, there were no significant differences in one-year overall mortality(p=0.23), hospitalization for CHF(p=0.99) or PPI(p=0.99). NOP-LBBB exposed patients to a high rate of dysrhythmic events(12.1%vs.1.4%,p<0.01) and was associated with a significant decrease in LVEF (62±9.5% vs. 65.2±7.83%, p=0.02) without an impact on NYHA functional status(1.25±0.32 and 1.52±0.70,p=0.32). Seventeen patients(6.2%) had a PPI before discharge, including 14 NOP-LBBB patients.

CONCLUSIONS

NOP-LBBB after RD-AVR is prevalent in patients with no prior conduction disorders. INTUITY ELITE is associated with a significantly higher rate of NOP-LBBB. The persistence of NOP-LBBB predisposed patients to the occurrence of high-grade conduction disorders and might have led to PPI but did not increase mortality or hospitalization for CHF.

Frequency, Penetrance, and Variable Expressivity of Dilated Cardiomyopathy-Associated Putative Pathogenic Gene Variants in UK Biobank Participants

BACKGROUND

There is a paucity of data regarding the phenotype of dilated cardiomyopathy (DCM) gene variants in the general population. We aimed to determine the frequency and penetrance of DCM-associated putative pathogenic gene variants in a general adult population, with a focus on the expression of clinical and subclinical phenotype, including structural, functional, and arrhythmic disease features.

METHODS

UK Biobank participants who had undergone whole exome sequencing, ECG, and cardiovascular magnetic resonance imaging were selected for study. Three variant-calling strategies (1 primary and 2 secondary) were used to identify participants with putative pathogenic variants in 44 DCM genes. The observed phenotype was graded DCM (clinical or cardiovascular magnetic resonance diagnosis); early DCM features, including arrhythmia or conduction disease, isolated ventricular dilation, and hypokinetic nondilated cardiomyopathy; or phenotype-negative.

RESULTS

Among 18 665 individuals included in the study, 1463 (7.8%) possessed ≥1 putative pathogenic variant in 44 DCM genes by the main variant calling strategy. A clinical diagnosis of DCM was present in 0.34% and early DCM features in 5.7% of individuals with putative pathogenic variants. ECG and cardiovascular magnetic resonance analysis revealed evidence of subclinical DCM in an additional 1.6% and early DCM features in an additional 15.9% of individuals with putative pathogenic variants. Arrhythmias or conduction disease (15.2%) were the most common early DCM features, followed by hypokinetic nondilated cardiomyopathy (4%). The combined clinical/subclinical penetrance was ≤30% with all 3 variant filtering strategies. Clinical DCM was slightly more prevalent among participants with putative pathogenic variants in definitive/strong evidence genes as compared with those with variants in moderate/limited evidence genes.

CONCLUSIONS

In the UK Biobank, ≈1 of 6 of adults with putative pathogenic variants in DCM genes exhibited early DCM features potentially associated with DCM genotype, most commonly manifesting with arrhythmias in the absence of substantial ventricular dilation or dysfunction.

Physician Training for Electrocardiogram Interpretation: A Systematic Review and Meta-Analysis

PURPOSE

Using electrocardiogram (ECG) interpretation as an example of a widely taught diagnostic skill, the authors conducted a systematic review and meta-analysis to demonstrate how research evidence on instruction in diagnosis can be synthesized to facilitate improvement of educational activities (instructional modalities, instructional methods, and interpretation approaches), guide the content and specificity of such activities, and provide direction for research.

METHOD

The authors searched PubMed/MEDLINE, Embase, Cochrane CENTRAL, PsycInfo, CINAHL, ERIC, and Web of Science databases through February 21, 2020, for empirical investigations of ECG interpretation training enrolling medical students, residents, or practicing physicians. They appraised study quality with the Medical Education Research Study Quality Instrument and pooled standardized mean differences (SMDs) using random effects meta-analysis.

RESULTS

Of 1,002 articles identified, 59 were included (enrolling 17,251 participants). Among 10 studies comparing instructional modalities, 8 compared computer-assisted and face-to-face instruction, with pooled SMD 0.23 (95% CI, 0.09, 0.36) indicating a small, statistically significant difference favoring computer-assisted instruction. Among 19 studies comparing instructional methods, 5 evaluated individual versus group training (pooled SMD -0.35 favoring group study [95% CI, -0.06, -0.63]), 4 evaluated peer-led versus faculty-led instruction (pooled SMD 0.38 favoring peer instruction [95% CI, 0.01, 0.74]), and 4 evaluated contrasting ECG features (e.g., QRS width) from 2 or more diagnostic categories versus routine examination of features within a single ECG or diagnosis (pooled SMD 0.23 not significantly favoring contrasting features [95% CI, -0.30, 0.76]). Eight studies compared ECG interpretation approaches, with pooled SMD 0.92 (95% CI, 0.48, 1.37) indicating a large, statistically significant effect favoring more systematic interpretation approaches.

CONCLUSIONS

Some instructional interventions appear to improve learning in ECG interpretation; however, many evidence-based instructional strategies are insufficiently investigated. The findings may have implications for future research and design of training to improve skills in ECG interpretation and other types of visual diagnosis.

Electrocardiogram-Based Heart Age Estimation by a Deep Learning Model Provides More Information on the Incidence of Cardiovascular Disorders

Objective

The biological age progression of the heart varies from person to person. We developed a deep learning model (DLM) to predict the biological age via ECG to explore its contribution to future cardiovascular diseases (CVDs).

Methods

There were 71,741 cases ranging from 20 to 80 years old recruited from the health examination center. The development set used 32,707 cases to train the DLM for estimating the ECG-age, and 8,295 cases were used as the tuning set. The validation set included 30,469 ECGs to follow the outcomes, including all-cause mortality, cardiovascular-cause mortality, heart failure (HF), diabetes mellitus (DM), chronic kidney disease (CKD), acute myocardial infarction (AMI), stroke (STK), coronary artery disease (CAD), atrial fibrillation (AF), and hypertension (HTN). Two independent external validation sets (SaMi-Trop and CODE15) were also used to validate our DLM.

Results

The mean absolute errors of chronologic age and ECG-age was 6.899 years (r = 0.822). The higher difference between ECG-age and chronological age was related to more comorbidities and abnormal ECG rhythm. The cases with the difference of more than 7 years had higher risk on the all-cause mortality [hazard ratio (HR): 1.61, 95% CI: 1.23–2.12], CV-cause mortality (HR: 3.49, 95% CI: 1.74–7.01), HF (HR: 2.79, 95% CI: 2.25–3.45), DM (HR: 1.70, 95% CI: 1.53–1.89), CKD (HR: 1.67, 95% CI: 1.41–1.97), AMI (HR: 1.76, 95% CI: 1.20–2.57), STK (HR: 1.65, 95% CI: 1.42–1.92), CAD (HR: 1.24, 95% CI: 1.12–1.37), AF (HR: 2.38, 95% CI: 1.86–3.04), and HTN (HR: 1.67, 95% CI: 1.51–1.85). The external validation sets also validated that an ECG-age >7 years compare to chronologic age had 3.16-fold risk (95% CI: 1.72–5.78) and 1.59-fold risk (95% CI: 1.45–1.74) on all-cause mortality in SaMi-Trop and CODE15 cohorts. The ECG-age significantly contributed additional information on heart failure, stroke, coronary artery disease, and atrial fibrillation predictions after considering all the known risk factors.

Conclusions

The ECG-age estimated via DLM provides additional information for CVD incidence. Older ECG-age is correlated with not only on mortality but also on other CVDs compared with chronological age.

Prognostic Significance of Feature-Tracking Right Ventricular Global Longitudinal Strain in Non-ischemic Dilated Cardiomyopathy

Aims: Left ventricular global longitudinal strain (GLS) by cardiac magnetic resonance feature tracking (CMR-FT) analysis has shown an incremental prognostic value compared to classical parameters in non-ischemic dilated cardiomyopathy (NICM). However, less is known about the role of right ventricular (RV) GLS. Our objective was to evaluate the prognostic impact of RV-GLS by CMR-FT analysis in a population of NICM patients.

Methods: In this multicenter study, we examined NICM patients evaluated with a comprehensive CMR-FT study. Major cardiac events (MACEs) were considered as the study primary outcome measure and were defined as a composite of (a) cardiovascular death, (b) cardiac transplant or destination therapy ventricular assist device, (c) hospitalization for life-threatening ventricular arrhythmias or implantable cardiac defibrillator appropriate intervention. Heart failure (HF) related events, including hospitalizations and life-threatening arrhythmia-related events were considered as secondary end-points. Receiver operating time-dependent analysis were used to calculate the possible additional effect of RV-GLS to standard evaluation.

Results: We consecutively enrolled 273 patients. During a median follow-up of 39 months, 41 patients (15%) experienced MACEs. RV-GLS and LV late gadolinium emerged as the strongest prognostic CMR-FT variables: their association provided an estimated 3-year MACEs rate of 29%. The addition of RV-GLS significantly improved the prognostic accuracy in predicting MACEs with respect to the standard evaluation including LGE (areas under the curve from 0.71 [0.66–0.82] to 0.76 [0.66–0.86], p = 0.03). On competing risk analysis, RV-GLS showed a significant ability to reclassify overall both HF-related and life-threatening arrhythmia-related events, regardless of LV and RV ejection fraction.

Conclusions: In NICM patients, RV-GLS showed a significant prognostic role in reclassifying the risk of MACEs, incremental with respect to standard evaluation with standard prognostic parameters.

ECG pathology and its association with death in critically ill COVID-19 patients, a cohort study

BACKGROUND

We investigated the prevalence of ECG abnormalities and their association with mortality, organ dysfunction and cardiac biomarkers in a cohort of COVID-19 patients admitted to the intensive care unit (ICU).

METHODS

This cohort study included patients with COVID-19 admitted to the ICU of a tertiary hospital in Sweden. ECG, clinical data and laboratory findings during ICU stay were extracted from medical records and ECGs obtained near ICU admission were reviewed by two independent physicians.

RESULTS

Eighty patients had an acceptable ECG near ICU-admission. In the entire cohort 30-day mortality was 28%. Compared to patients with normal ECG, among whom 30-day mortality was 16%, patients with ECG fulfilling criteria for prior myocardial infarction had higher mortality, 63%, odds ratio (OR) 9.61 (95% confidence interval (CI) 2.02-55.6) adjusted for Simplified Acute Physiology Score 3 and patients with ST-T abnormalities had 50% mortality and OR 6.05 (95% CI 1.82-21.3) in univariable analysis. Both prior myocardial infarction pattern and ST-T pathology were associated with need for vasoactive treatment and higher peak plasma levels of troponin-I, NT-pro-BNP (N-terminal pro-Brain Natriuretic Peptide), and lactate during ICU stay compared to patients with normal ECG.

CONCLUSION

ECG with prior myocardial infarction pattern or acute ST-T pathology at ICU admission is associated with death, need for vasoactive treatment and higher levels of biomarkers of cardiac damage and strain in severely ill COVID-19 patients, and should alert clinicians to a poor prognosis.

Natural Language Mapping of Electrocardiogram Interpretations to a Standardized Ontology

BACKGROUND

Interpretations of the electrocardiogram (ECG) are often prepared using software outside the electronic health record (EHR) and imported via an interface as a narrative note. Thus, natural language processing is required to create a computable representation of the findings. Challenges include misspellings, nonstandard abbreviations, jargon, and equivocation in diagnostic interpretations.

OBJECTIVES

Our objective was to develop an algorithm to reliably and efficiently extract such information and map it to the standardized ECG ontology developed jointly by the American Heart Association, the American College of Cardiology Foundation, and the Heart Rhythm Society. The algorithm was to be designed to be easily modifiable for use with EHRs and ECG reporting systems other than the ones studied.

METHODS

An algorithm using natural language processing techniques was developed in structured query language to extract and map quantitative and diagnostic information from ECG narrative reports to the cardiology societies' standardized ECG ontology. The algorithm was developed using a training dataset of 43,861 ECG reports and applied to a test dataset of 46,873 reports.

RESULTS

Accuracy, precision, recall, and the F1-measure were all 100% in the test dataset for the extraction of quantitative data (e.g., PR and QTc interval, atrial and ventricular heart rate). Performances for matches in each diagnostic category in the standardized ECG ontology were all above 99% in the test dataset. The processing speed was approximately 20,000 reports per minute. We externally validated the algorithm from another institution that used a different ECG reporting system and found similar performance.

CONCLUSION

The developed algorithm had high performance for creating a computable representation of ECG interpretations. Software and lookup tables are provided that can easily be modified for local customization and for use with other EHR and ECG reporting systems. This algorithm has utility for research and in clinical decision-support where incorporation of ECG findings is desired.

Performance and limitations of automated ECG interpretation statements in patients with suspected acute coronary syndrome

BACKGROUND

The 12‑lead ECG plays an important role in triaging patients with symptomatic coronary artery disease, making automated ECG interpretation statements of "Acute MI" or "Acute Ischemia" crucial, especially during prehospital transport when access to physician interpretation of the ECG is limited. However, it remains unknown how automated interpretation statements correspond to adjudicated clinical outcomes during hospitalization. We sought to evaluate the diagnostic performance of prehospital automated interpretation statements to four well-defined clinical outcomes of interest: confirmed ST- segment elevation myocardial infarction (STEMI); presence of actionable coronary culprit lesions, myocardial necrosis, or any acute coronary syndrome (ACS).

METHODS

An observational cohort study that enrolled consecutive patients with non-traumatic chest pain transported via ambulance. Prehospital ECGs were obtained with the Philips MRX monitor from the medical command center and re-processed using manufacturer-specific diagnostic algorithms to denote the likelihood of >>>Acute MI<<< or >>>Acute Ischemia<<<. Two independent reviewers retrospectively adjudicated the study outcomes and disagreements were resolved by a third reviewer.

RESULTS

Our study included 2400 patients (age 59 ± 16, 47% females, 41% Black), with 190 (8%) patients with documented automated diagnostic statements of acute MI or acute ischemia. The sensitivity/specificity of the automated algorithm for detecting confirmed STEMI (n = 143, 6%); presence of actionable coronary culprit lesions (n = 258, 11%), myocardial necrosis (n = 291, 12%), or any ACS (n = 378, 16%) were 62.9%/95.6%; 37.2%/95.6%; 38.5%/96.4%; and 30.7%/96.3%, respectively.

CONCLUSION

Although being very specific, automated interpretation statements of acute MI/acute ischemia on prehospital ECGs are not satisfactorily sensitive to exclude symptomatic coronary disease. Patients without these automated interpretation statements should be considered further for significant underlying coronary disease based on the clinical context.

TRIAL REGISTRATION

ClinicalTrials.gov # NCT04237688.

The History and Challenges of SCP-ECG: The Standard Communication Protocol for Computer-Assisted Electrocardiography

Ever since the first publication of the standard communication protocol for computer-assisted electrocardiography (SCP-ECG), prENV 1064, in 1993, by the European Committee for Standardization (CEN), SCP-ECG has become a leading example in health informatics, enabling open, secure, and well-documented digital data exchange at a low cost, for quick and efficient cardiovascular disease detection and management. Based on the experiences gained, since the 1970s, in computerized electrocardiology, and on the results achieved by the pioneering, international cooperative research on common standards for quantitative electrocardiography (CSE), SCP-ECG was designed, from the beginning, to empower personalized medicine, thanks to serial ECG analysis. The fundamental concept behind SCP-ECG is to convey the necessary information for ECG re-analysis, serial comparison, and interpretation, and to structure the ECG data and metadata in sections that are mostly optional in order to fit all use cases. SCP-ECG is open to the storage of the ECG signal and ECG measurement data, whatever the ECG recording modality or computation method, and can store the over-reading trails and ECG annotations, as well as any computerized or medical interpretation reports. Only the encoding syntax and the semantics of the ECG descriptors and of the diagnosis codes are standardized. We present all of the landmarks in the development and publication of SCP-ECG, from the early 1990s to the 2009 International Organization for Standardization (ISO) SCP-ECG standards, including the latest version published by CEN in 2020, which now encompasses rest and stress ECGs, Holter recordings, and protocol-based trials.

Expert consensus document on automated diagnosis of the electrocardiogram: The task force on automated diagnosis of the electrocardiogram in Japan. Part 1: Nomenclature for diagnosis and abnormal findings

As these terms should accurately represent the abnormal findings and conditions as much as possible, we propose to unify these terms into terminologies that are not confusing and easy to understand for everyone.

Single limb electrocardiogram using vector mapping: Evaluation and validation of a novel medical device

INTRODUCTION

The Tiger Tech Warfighter Monitor (WFM) is a novel single-limb device for ECG acquisition. The WFM provides true (not derived) single limb Electrocardiogram monitoring (ECG) to provide heart rate and R-R interval monitoring between QRS complexes. Herein, we evaluate the diagnostic accuracy of the WFM heart rate, R-R interval monitoring, and heart rate variability monitoring in comparison to a 2‑lead chest ECG.

METHODS

Data was collected under Institutional Review Board (IRB) approval. Patients available within our institution's pre-operative holding unit were randomly selected to undergo simultaneous chest and WFM ECG monitoring. 3-5-min measurements were taken depending on the patient's availability. Data was saved to two separate mobile phones and time-stamped for synchronization. A proprietary Tiger Tech extraction algorithm was used to tag proper features on both the WFM 1-Limb ECG and Chest ECG data files. A separate algorithm was then used to compare the beat-to-beat variations between the ECGs.

RESULTS

Data was extracted and analyzed on 26 subjects. Linear regression of heart rate analysis revealed excellent correlations with an R² of 0.99 (p < 0.05). Similar linear regression evaluation of R-R interval correlation demonstrated a mean R² value of 0.95 (p < 0.05). Statistically significant correlation was achieved in all 26 included study participants. Heart rate variability also achieved excellent correlation (SDNN R² = 0.997, RMSSD R² = 0.995, LnRMSSD R² = 0.992, p << 0.05).

CONCLUSION

Results demonstrate that the WFM achieves excellent correlation with chest ECG for heart rate, R-R internals, and heart rate variability.

Cardiovascular risk assessment and association with novel biomarkers in patients with Type 2 diabetes mellitus

Aim: To investigate the association between cardiovascular risk and biomarkers in patients with Type 2 diabetes (T2DM). Methods: Cross-sectional study, with evaluation of traditional and new biomarkers (serum FGF-23, Syndecan-1 [Sdc-1] and vascular cell adhesion molecule-1 [VCAM-1] and urinary VEGF and kidney injury molecule-1 [KIM-1]) and risk scores (Framingham-FRS and UK Prospective Diabetes Study [UKPDS]). Results: 128 diabetics were included, with predominance of high risk by FRS and low risk by UKPDS. There was an independent association of VCAM-1 and VEGF with higher risk by FRS-lipids and UKPDS. Conclusion: There was an independent association of VCAM-1 and VEGF with higher cardiovascular risk, showing a subclinical endothelial dysfunction in T2DM. The inclusion of novel biomarkers to risk scores may increase accuracy when assessing cardiovascular risk of diabetic individuals.

Diagnostic Interpretation of Non-Uniformly Sampled Electrocardiogram

We present a set of three fundamental methods for electrocardiogram (ECG) diagnostic interpretation adapted to process non-uniformly sampled signal. The growing volume of ECGs recorded daily all over the world (roughly estimated to be 600 TB) and the expectance of long persistence of these data (on the order of 40 years) motivated us to challenge the feasibility of medical-grade diagnostics directly based on arbitrary non-uniform (i.e., storage-efficient) ECG representation. We used a refined time-independent QRS detection method based on a moving shape matching technique. We applied a graph data representation to quantify the similarity of asynchronously sampled heartbeats. Finally, we applied a correlation-based non-uniform to time-scale transform to get a multiresolution ECG representation on a regular dyadic grid and to find precise P, QRS and T wave delimitation points. The whole processing chain was implemented and tested with MIT-BIH Database (probably the most referenced cardiac database) and CSE Multilead Database (used for conformance testing of medical instruments) signals arbitrarily sampled accordingly to a perceptual model (set for variable sampling frequency of 100-500 Hz, compression ratio 3.1). The QRS detection shows an accuracy of 99.93% with false detection ratio of only 0.18%. The classification shows an accuracy of 99.27% for 14 most frequent MIT-BIH beat types and 99.37% according to AAMI beat labels. The wave delineation shows cumulative (i.e., sampling model and non-uniform processing) errors of: 9.7 ms for P wave duration, 3.4 ms for QRS, 6.7 ms for P-Q segment and 17.7 ms for Q-T segment, all the values being acceptable for medical-grade interpretive software.

Importance Ranking of Electrocardiogram Rhythms: A Primer for Curriculum Development

INTRODUCTION

Electrocardiogram interpretation is an essential skill for emergency and critical care nurses and physicians. There remains a gap in standardized curricula and evaluation strategies used to achieve and assess competence in electrocardiogram interpretation. The purpose of this study was to develop an importance ranking of the 120 American Heart Association electrocardiogram diagnostic labels with interdisciplinary perspectives to inform curriculum development.

METHODS

Data for this mixed methods study were collected through focus groups and individual semi-structured interviews. A card sort was used to assign relative importance scores to all 120 American Heart Association electrocardiogram diagnostic labels. Thematic analysis was used for qualitative data on participants' rationale for the rankings.

RESULTS

The 18 participants included 6 emergency and critical care registered nurses, 5 cardiologists, and 7 emergency medicine physicians. The 5 diagnoses chosen as the most important by all disciplines were ventricular tachycardia, ventricular fibrillation, atrial fibrillation, complete heart block, and normal electrocardiogram. The "top 20" diagnoses by each discipline were also reported. Qualitative thematic content analysis revealed that participants from all 3 disciplines identified skill in electrocardiogram interpretation as clinically imperative and acknowledged the importance of recognizing normal, life threatening, and time-sensitive electrocardiogram rhythms. Additional qualitative themes, identified by individual disciplines, were reported.

DISCUSSION

This mixed-methods approach provided valuable interdisciplinary perspectives concerning electrocardiogram curriculum case selection and prioritization. Study findings can provide a foundation for emergency and critical care educators to create local ECG educational programs. Further work is recommended to validate the list amongst a larger population of emergency and critical care frontline nurses and physicians.

A qualitative study on negative attitude toward electrocardiogram learning among undergraduate medical students

Objective:

Negative affect state toward learning has a substantial impact on the learning process, academic performance, and practice of a particular subject, but such attitude toward electrocardiogram (ECG) learning has still received relatively little attention in medical education research. In spite of the significant emphasis in investigating ECG teaching method, the educators would not be able to address ECG incompetency without understanding the negative perception and attitude toward ECG learning. The purpose of this study was to assess the undergraduate students' difficulties in ECG learning and hence help educators design appropriate ECG learning curriculum to instill competent skill in ECG interpretation based on this outcome.

Materials and Methods:

A total of 324 undergraduate preclinical (year 2) and clinical (year 3–5) medical students participated in this study. The research design used thematic analysis of an open-ended questionnaire to analyze the qualitative data.

Results:

The thematic analysis detected five major emergent themes: lack of remembering (18.2%), lack of understanding (28.4%), difficulty in applying (3.6%), difficulty in analysis (15.1%), and difficulty in interpretation (17.8%), of which addressing these challenges could be taken as a foundation step upon which medical educators put an emphasis on in order to improve ECG teaching and learning.

Conclusion:

Negative attitude toward ECG learning poses a serious threat to acquire competency in ECG interpretation skill. The concept of student's memorizing ECG is not a correct approach; instead, understanding the concept and vector analysis is an elementary key for mastering ECG interpretation skill. The finding of this study sheds light into a better understanding of medical students' deficient points of ECG learning in parallel with taxonomy of cognitive domain and enables the medical teachers to come up with effective and innovative strategies for innovative ECG learning in an undergraduate medical curriculum.

Electrocardiogram analysis of patients with different types of COVID-19

Background

Severe acute respiratory syndrome coronavirus 2 causes acute myocardial damage and arrhythmia in coronavirus disease 2019 (COVID‐19) patients. Studying the changes of electrocardiogram is of great significance for the diagnosis of patients with COVID‐19.

Methods

A retrospective analysis method was adopted to compare the electrocardiogram changes between COVID‐19 critically severe and severe patients. Univariate and multivariate logistic regression were used to analyze the correlation of the levels of serum indexes and past medical history with ST‐T changes and atrial fibrillation. And the correlation of ECG parameters with in‐hospital death and ventilator use were investigated by using the same methods.

Results

The incidence of male, stroke, elevated cardiac troponin I (cTnI), N‐terminal of the prohormone brain natriuretic peptide (NT‐proBNP), d‐dimer, high‐sensitivity C‐reactive protein (hs‐CRP), hyperkalemia, and hypocalcemia in the critically ill patients was higher than that in severe patients. There were differences in ST‐T changes, sinus tachycardia, atrial fibrillation, and atrial tachycardia between the two groups. Multivariate logistic regression analysis showed that elevated cTnI and NT‐proBNP were the independent risk factors of ST‐T changes. Elevated NT‐proBNP and age were the independent risk factors of atrial fibrillation. Sinus tachycardia and atrial fibrillation were the independent risk factors of in‐hospital death and ventilator use.

Conclusion

ST‐T changes, sinus tachycardia, and atrial fibrillation are with great significance in the diagnosis of the severity, myocardia injury, and cardiac insufficiency of COVID‐19 patients. Sinus tachycardia and atrial fibrillation could be used as independent variables predicting in‐hospital death and ventilator use.

QTc evaluation in patients with bundle branch block

Proper measurement of the QT interval on the 12-lead body-surface ECG is challenging in daily practice. Even more difficult is its correct estimation in the presence of repolarization abnormalities, arrhythmias or bundle-branch blocks (BBB). The QT interval results from two parts of the ECG: (1) the QRS complex, describing the excitation of the ventricles and (2) the JT interval, describing the repolarisation of the ventricles. Prolongation of the QRS width – like in the presence of BBB – entails prolongation of the QT interval, making the estimation of the true repolarisation time challenging. The US recommendations for the standardization and interpretation of the ECG suggest focusing on the JT interval in presence of BBB. However, in clinical practice physicians have become more familiar with the interpretation of QT-interval measurements than with the interpretation of the JT Interval.

In the last decade, a simple formula for the estimation of the “modified QT interval” in the presence of left or right BBB has been developed and evaluated. In this formula, the modified QT interval is calculated by subtracting 50% of the length of the BBB-QRS from the measured QT interval (QT_m = QT_BBB − 50% QRS_BBB). Subsequently, rate-correction formula should be applied as usual. In this review, we discuss the determination of the QT-interval in the presence of BBB and summarize the origin and application of the modified QT-interval formula.

PTB-XL, a large publicly available electrocardiography dataset

Electrocardiography (ECG) is a key non-invasive diagnostic tool for cardiovascular diseases which is increasingly supported by algorithms based on machine learning. Major obstacles for the development of automatic ECG interpretation algorithms are both the lack of public datasets and well-defined benchmarking procedures to allow comparison s of different algorithms. To address these issues, we put forward PTB-XL, the to-date largest freely accessible clinical 12-lead ECG-waveform dataset comprising 21837 records from 18885 patients of 10 seconds length. The ECG-waveform data was annotated by up to two cardiologists as a multi-label dataset, where diagnostic labels were further aggregated into super and subclasses. The dataset covers a broad range of diagnostic classes including, in particular, a large fraction of healthy records. The combination with additional metadata on demographics, additional diagnostic statements, diagnosis likelihoods, manually annotated signal properties as well as suggested folds for splitting training and test sets turns the dataset into a rich resource for the development and the evaluation of automatic ECG interpretation algorithms.

Computational approaches for detection of cardiac rhythm abnormalities: Are we there yet?

The analysis of an electrocardiogram (ECG) is able to provide vital information on the electrical activity of the heart and is crucial for the accurate diagnosis of cardiac arrhythmias. Due to the nature of some arrhythmias, this might be a time-consuming and difficult to accomplish process. The advent of novel machine learning technologies in this field has a potential to revolutionise the use of the ECG. In this review, we outline key advances in ECG analysis for atrial, ventricular and complex multiform arrhythmias, as well as discuss the current limitations of the technology and the barriers that must be overcome before clinical integration is feasible.

Differential Watermarking of Multilead ECG Baseline

Digital watermarking has been widely recognized as an effective tool for embedment of auxiliary data in the host record. This paper presents a new method of watermarking using lead-to-lead difference of values in the baseline of the host electrocardiogram. The method starts with delineation of the baseline and uses Kirchoff voltage law or interpolation to predict any selected lead from the remaining ones. Next, the difference between the predicted and actual value is considered as noise and subjects to measurement of level and distribution in the time frame of baseline. The watermark with patient data or results of accompanying measurements is coded accordingly to mimic the noise. Replacement of the baseline noise with the watermark data ends the process. With 12-lead CSE files and respective reference borders of PQ and TP segments, the capacity of watermark achieved 3875 bits per second, while the diagnostic value of the ECG remains untouched.

A Direct Transform of Discrete Non-Uniform ECG to a Time-Scale Representation

Adaptive sampling is an interesting alternative for biosignal acquisition, transmission and storage, however further processing of non uniform representations is still waiting for development. In this paper a direct non-uniform to time-scale (NUTS) transform is presented and applied to the ECG signal. Well accepted limits of bandwidth in particular sections of the ECG and established standards for the assessment of diagnostic quality help in evaluation of the influence the transform has to the diagnostic result. The transform uses a regular-grid Coiflet 5-th order nearly symmetric wavelet, but the novelty is a pointwise calculating of its correlation accordingly to non-uniform distribution of the electrocardio-gram samples. In tests with CSE Database files the proposed transform method yields not bit-accurate ECG signals, but the diagnostic results are more influenced by the non-uniform representation (for QRS mean deviation: +0.7 ms vs. original files) than by the transform itself (for QRS additionally: +0.6 ms) and all the results remain within the accuracy tolerance of the CEN industrial standard.

ECG in dilated cardiomyopathy: specific findings and long-term prognostic significance

OBJECTIVE

The objective was to provide an exhaustive characterization of ECG features in a large cohort of dilated cardiomyopathies (DCMs) and then investigate their possible prognostic role in the long term.

BACKGROUND

ECG is an accessible, reproducible, low-cost diagnostic and prognostic tool. However, an extensive description of ECG features and their long-term prognostic role in a large cohort of DCM is lacking.

METHODS

All available baseline ECGs of DCM patients enrolled from 1992 to 2013 were systematically analysed. Patients underwent to a complete clinical-laboratory evaluation. The study outcome measures were death or heart transplant (D/HT) and sudden death or malignant ventricular arrhythmias (SD/MVA).

RESULTS

Four hundred and fourteen DCM patients were enrolled. During a median follow-up of 125 months, 55 and 57 patients experienced D/HT and SD/MVA, respectively. At multivariate analysis, left ventricular hypertrophy (P = 0.017), heart rate (HR, P = 0.005) and anterolateral T-wave inversion (P = 0.041) predicted D/HT. Regarding SD/MVA, S wave amplitude in V2 (P = 0.008), R wave amplitude in DIII (P = 0.007), anterolateral T-wave inversion (P = 0.017) emerged as predictors. At receiver-operating curve analyses, the addition of ECG models to the clinical-laboratory evaluation significantly increased the area under the curve both for D/HT (from 0.68 to 0.74, P = 0.042) and SD/MVA (from 0.70 to 0.77, P = 0.048).

CONCLUSION

The exhaustive systematic evaluation of ECG has an incremental impact in the prognostication of a large cohort of DCM patients, also regarding the arrhythmic stratification.

Simultaneously acquired data from contactless and wearable devices for direct and indirect heart-rate measurement

The proposed dataset provides a complete set of simultaneously acquired data from contactless and wearable devices for direct and indirect heart-rate measurement. Data were acquired on a total of 20 healthy white Caucasian subjects wearing no makeup (10 males and 10 females; age: 22.50 ± 1.57 years; height: 173 ± 10 cm; weight: 62.80 ± 9.52 kg) and consisted of: i) videos of the subject's face acquired by a RGB-D (Red, Green, Blue and Depth) camera (Microsoft Kinect v2), which is a contactless device; ii) electrocardiographic (ECG) recordings acquired by a clinical Holter ECG recorder (Global Instrumentation's M12R Holter), which is a wearable device; and iii) heart-rate measurements acquired from a commercial smartwatch (Moto 360 smartwatch by Motorola), which is also a wearable device. ECG recordings were processed to extract the R-peaks position and obtain a reference indirect measurement of the heart rate. A direct measurement of the heart rate was provided by the commercial smartwatch. The dataset here presented could be useful to develop new algorithms for heart-rate detection from contactless devices and to validate contactless heart-rate estimation in comparison to reference heart rate from clinical wearable devices and to heart rate from commercial wearable devices.

Diagnostic approach for cardiac involvement in sarcoidosis

Aims

Cardiac sarcoidosis (CS) is a potentially life-threatening condition. Early detection of CS is therefore important. The aim of this study was to eludicate the usefulness of different investigations in a subgroup of patients with sarcoidosis regarded as having an increased risk for cardiac involvement.

Methods

42 sarcoidosis patients, who had an abnormal resting electrocardiogram (ECG) and/or symptoms indicating possible cardiac involvement (i.e. palpitations, pre-syncope or syncope), were included in the study. They were identified in a consecutive manner among patients followed-up at outpatient clinics for respiratory disorders. Holter monitoring, exercise test, transthoracic echocardiogram (TTE), cardiovascular magnetic resonance (CMR) and analysis of N-terminal pro B-type natriuretic peptide (NT-pro-BNP) in serum were performed. Note, that the role of FDG-PET was not investigated in this study.

Results

In the group with a pathologic ECG 11/25 (44%) were ultimately diagnosed with CS (all with pathologic CMR). However, in the group with only symptoms but a normal ECG just 1/17 got the diagnosis CS (p<0.05). This patient had a pathologic Holter monitoring. The risk for CS was increased if serum NT-pro-BNP was elevated (i.e. NT-pro-BNP>125 ng/L), sensitivity 78% (p<0.05), specificity 67%. By adding a pathologic ECG to an elevated NT-pro-BNP increased specificity to 93% and sensitivity remained at 78%.

Conclusion

Our findings indicate that CMR should be performed at an early stage in sarcoidosis patients with an abnormal resting ECG. Holter monitoring and elevated levels of NT-pro-BNP may enhance the diagnostic accuracy whereas exercise testing and TTE in this study had less impact on the identification of CS.

Case report: Posterior myocardial infarction in presence of right bundle branch block: an old concept with new findings

Background

The diagnosis of acute ischaemic coronary syndromes in presence of an intra-ventricular conduction disturbance represents a clinical challenge. In the cardiac segmentation model the posterior wall is replaced by the basal inferior segment. However, in the clinical scenario of acute coronary syndrome the concept of posterior myocardial infarction (PMI) endures. The association of a PMI and right bundle branch block (RBBB) is a rare condition characterised by broad R waves and ventricular repolarization disorders in right precordial leads in both entities, which could lead to misinterpretation and delay in reperfusion therapy.

Case Summary

We describe a case report of a 74-year-old man with acute chest pain and an electrocardiogram with broad R waves, a 4 mm ST-segment downsloping (excessively discordant) in right precordial leads, RBBB, and ST-segment elevation in posterior leads. There was resolution of ST-segment downsloping in right precordial leads after percutaneous coronary intervention and stenting of the circumflex artery, with disturbance of the repolarization process only attributable to RBBB.

Discussion

Patients with acute chest pain with RBBB and a ST segment with an excessive downsloping (out of proportion of what is expected in isolated RBBB) suggest PMI with occlusion of the circumflex coronary artery.

ECG interpretation skill acquisition: A review of learning, teaching and assessment

The recording of 12 lead electrocardiograms (ECG) is one of the most useful and commonly performed medical procedures. ECGs are used in diagnosis, risk-stratification management decision-making, and assessment in response to therapy. The correct interpretation of 12 lead ECG recordings is complex and clinically challenging with misinterpretation having the potential to result in poor outcomes or even patient fatality. Despite its widespread use, several studies have highlighted deficiencies in ECG interpretation skills among health professionals. The literature suggests that up to 33% of ECG interpretations have some error when compared to the expert reference and up to 11% resulted in inappropriate management. The pedagogy of ECG interpretation lacks universal establishment; time allocation, faculty training and teaching format vary considerably within the literature. This review of the literature reports how a lack of established ECG reporting methods may contribute to the variation in reported ECG interpretation competence across many healthcare professionals. The ubiquity of the ECG in clinical practice and an over reliance on computer assisted ECG interpretation are additionally explored as factors affecting acquisition and retention of this clinical skill.

Heart rate fragmentation: using cardiac pacemaker dynamics to probe the pace of biological aging

This perspectives article discusses the use of a novel set of dynamical biomarkers in the assessment of biological versus chronological age. The basis for this development is a recently delineated property of altered sinoatrial pacemaker-neuroautonomic function, termed heart rate fragmentation (HRF). Fragmented rhythms manifest as an increase in the density of changes in heart rate acceleration sign, not mechanistically explicable by physiological cardiac vagal tone modulation. We reported that HRF increased monotonically with cross-sectional age and that HRF measures, but not conventional heart rate variability metrics, were significantly associated with major incident cardiovascular events in the Multi-Ethnic Study of Atherosclerosis (MESA). Furthermore, HRF measures added value to both Framingham and MESA cardiovascular risk indices. Here, we propose that interventions that fundamentally slow or reverse the pace of biological aging, via system-wide effects, should be associated with a decrease in the degree of HRF and possibly with a reemergence of the nonfragmented ("fluent") patterns associated with more youthful heart rate dynamics.

Can Intradetrusor OnabotulinumtoxinA Injections Alter Heart Function in Patients with Cardiac Arrhythmia?

The prevalence of overactive bladder (OAB) increases with age and can be associated with other co-morbidities, such as cardiac arrhythmia. Unfortunately, commonly used anticholinergic drugs for OAB can affect the cardiovascular system, leading to tachycardia. However, there are no data, which consider the influence of intradetrusor onabotulinumtoxinA injections on heart function in idiopathic OAB patients. The aim of the present study was to evaluate the influence of intradetrusor onabotulinumtoxinA injections on electrocardiogram (ECG) parameters. Additionally, changes in ECG were analyzed in OAB patients without cardiac arrhythmia. Thirty-one patients with cardiac arrhythmia and 31 participants without irregular heart rate (HR) completed the study. ECG measurements were performed in supine positions 2 h before onabotulinumtoxinA injections, 1 h after treatment, and at 2 weeks of follow-up. At week 6, a phone-call survey was conducted to collect data about adverse events. OnabotulinumtoxinA injections were performed with rigid cystoscopy under local anesthesia. We did not observe any clinically significant changes in the analyzed ECG parameters between consecutive measurements. While a slight increase of HR was observed in patients without cardiac arrhythmia, it remained within normal range. Intravesical onabotulinumtoxinA injections are, hence, safe for female patients with cardiac arrhythmia and do not significantly influence changes in ECG.

Right ventricular function in elite male athletes meeting the structural echocardiographic task force criteria for arrhythmogenic right ventricular cardiomyopathy

Athlete pre-participation screening is focused on detecting pathological conditions like arrhythmogenic right ventricular cardiomyopathy (ARVC). The diagnosis of ARVC is established by applying the revised 2010 ARVC Task Force Criteria (TFC) that assesses RV structure and function. Some athletes may meet structural TFC without having ARVC but we do not know the consequences for RV function. This study compared RV structural and functional indices in male athletes that meet the structural TFC (MTFC) for ARVC and those that do not (NMTFC). We recruited 214 male elite athletes. All participants underwent 2D, Doppler, tissue Doppler and strain (ε) echocardiography with a focused and comprehensive assessment of the right heart. Athletes were grouped on RV structural data: MTFC n = 34; NMTFC n = 180. Functional data were compared between groups. By selection, MTFC had larger absolute and scaled RV outflow tract (RVOT) diameter compared to NMTFC (P ˂0.05) but these athletes did not develop a proportional increase in the RV inflow dimensions. There was no difference in global conventional RV systolic function between both groups however, there was significantly lower global RV ε in athletes that MTFC which can be explained, in part, by the RVOT dimension.

Prognostic Value of Electrocardiography in Patients With Fulminant Myocarditis Supported by Percutaneous Venoarterial Extracorporeal Membrane Oxygenation - Analysis From the CHANGE PUMP Study

BACKGROUND

Fulminant myocarditis (FM) presents various abnormal findings on ECG, the prognostic impact of which has not been not fully elucidated. The aim of this study was therefore to clarify the prognostic value of ECG data in FM patients supported by venoarterial extracorporeal membrane oxygenation (VA-ECMO).Methods and Results:In this multicenter chart review, we investigated 99 patients with FM supported by VA-ECMO. The final cohort consisted of 87 patients (mean age, 52±16 years; female, 42%) after 12 patients who required conversion to other forms of mechanical circulatory support were excluded. The median LVEF was 14.5%. At the time of VA-ECMO initiation, 38 patients (44%) had arrhythmias including atrial fibrillation (6%), complete atrioventricular block (CAVB; 17%), and ventricular tachycardia or fibrillation (VT/VF; 15%). Of the 49 patients with sinus rhythm (SR), 26 had QRS duration ≥120 ms (wide QRS). On logistic regression analysis, wide QRS predicted in-hospital death in patients with SR (OR, 3.6; 95% CI: 1.07-13.61, P=0.04). Compared with SR with narrow QRS (QRS duration <120 ms), CAVB and VT/VF had a higher risk of in-hospital death (CAVB: OR, 7.20; 95% CI: 1.78-34.15, P=0.005; VT/VF: OR, 8.10; 95% CI: 1.86-42.31, P=0.005).

CONCLUSIONS

In patients with FM, CAVB and VT/VF carried a higher risk of in-hospital death. Wide QRS also predicted a higher risk of in-hospital death in patients with SR.

SCReening Evaluation of the Evolution of New Heart Failure Study (SCREEN-HF): early detection of chronic heart failure in the workplace

Objective The aim of the present study was to determine whether asymptomatic heart failure (HF) in the workplace is subject to the health worker effect, making screening using conventional risk factors combined with a cardiac biomarker, namely N-terminal pro B-type natriuretic peptide (NT-proBNP), as useful as in the general population. Methods Between June 2007 and December 2009 a 'well' population deemed at high risk for development of HF was identified through health insurance records. Blood was collected from volunteer participants for analysis of urea, electrolytes and creatinine, a full blood count and NT-proBNP. An echocardiogram was performed on selected participants based on high NT-proBNP concentrations. Results The mean left ventricular ejection fraction (LVEF) was significantly reduced in participants with the highest compared with the lowest NT-proBNP quintile. In multivariate analysis, log-transformed NT-proBNP was independently associated with impaired LVEF and with moderate to severe diastolic dysfunction after adjustment for age, sex, coronary artery disease, diabetes, hypertension and obesity. Conclusions A large burden of asymptomatic left ventricular dysfunction (AVLD) was observed in subjects aged 60 and over with plasma NT-proBNP in the top quintile that was independent of conventional risk factors and work status. HWE does not appear to operate in AVLD. NT-proBNP testing in a population with HF risk factors may cost-effectively identify those at greatest risk of developing HF in a working population and facilitate early diagnosis, treatment and maintenance of work capacity. What is known about the topic? Chronic heart failure (CHF) has several causes, the most common being hypertension and coronary ischaemia. CHF is a major health problem of increasing prevalence that severely impacts quality of life, shortens lives and reduces worker productivity. It is often not diagnosed early enough to take full advantage of ameliorating medication. What does this paper add? Population screening for CHF is not currently advocated. This may be because conventional risk factors must be used in combination and there is no useful biomarker available. Yet evidence (SOLVD (Studies of Left Ventricular Dysfunction trials) recommends early diagnosis. We believe the work place is an area of potential screening where there is little supporting evidence. This paper provides evidence that the biomarker NT-proBNP is a useful new tool that improves cost-effectiveness of screening in a selected population. Specifically, the paper recommends CHF screening in the population with the highest potential health gain (i.e. the working population) by the sector with the highest economic gain (i.e. employers). What are the implications for practitioners? The paper presents important health screening recommendations for medical and health and safety practitioners within a selected population of workers. We feel practitioners should consider screening for incipient heart failure, particularly within Australia's working population, to save lives, provide economic benefit and extend working longevity.

Right ventricular systolic function in hypertensive heart failure

BACKGROUND

Heart failure (HF) is a major cause of cardiovascular admissions and hypertensive heart failure (HHF) is the most common cause of HF admissions in sub-Saharan Africa, Nigeria inclusive. Right ventricular (RV) dysfunction is being increasingly recognized in HF and found to be an independent predictor of adverse outcomes in HF. This study aimed to determine the prevalence of RV systolic dysfunction in HHF by several echocardiographic parameters.

METHODOLOGY

One hundred subjects with HHF were recruited consecutively into the study along with 50 age and sex-matched controls. All study participants gave written informed consent, and had a full physical examination, blood investigations, 12-lead electrocardiogram, and transthoracic echocardiography. RV systolic function was assessed in all subjects using different methods based on the American Society of Echocardiography guidelines for echocardiographic assessment of the right heart in adults. This included tricuspid annular plane systolic excursion (TAPSE), RV myocardial performance index (MPI), and RV systolic excursion velocity by tissue Doppler (S').

RESULTS

RV systolic dysfunction was found in 53% of subjects with HHF by TAPSE, 56% by RV MPI, and 48% by tissue Doppler systolic excursion S'. RV systolic dysfunction increased with reducing left ventricular ejection fraction (LVEF) in subjects with HHF.

CONCLUSION

A high proportion of subjects with HHF were found to have RV systolic functional abnormalities using TAPSE, RV MPI, and RV S'. Prevalence of RV systolic dysfunction increased with reducing LVEF.

Computer-Interpreted Electrocardiograms: Benefits and Limitations

Computerized interpretation of the electrocardiogram (CIE) was introduced to improve the correct interpretation of the electrocardiogram (ECG), facilitating health care decision making and reducing costs. Worldwide, millions of ECGs are recorded annually, with the majority automatically analyzed, followed by an immediate interpretation. Limitations in the diagnostic accuracy of CIE were soon recognized and still persist, despite ongoing improvement in ECG algorithms. Unfortunately, inexperienced physicians ordering the ECG may fail to recognize interpretation mistakes and accept the automated diagnosis without criticism. Clinical mismanagement may result, with the risk of exposing patients to useless investigations or potentially dangerous treatment. Consequently, CIE over-reading and confirmation by an experienced ECG reader are essential and are repeatedly recommended in published reports. Implementation of new ECG knowledge is also important. The current status of automated ECG interpretation is reviewed, with suggestions for improvement.

ANMCO/AIIC/SIT Consensus Information Document: definition, precision, and suitability of electrocardiographic signals of electrocardiographs, ergometry, Holter electrocardiogram, telemetry, and bedside monitoring systems

The electrocardiogram (ECG) signal can be derived from different sources. These include systems for surface ECG, Holter monitoring, ergometric stress tests, and telemetry systems and bedside monitoring of vital parameters, which are useful for rhythm and ST-segment analysis and ECG screening of electrical sudden cardiac death predictors. A precise ECG diagnosis is based upon correct recording, elaboration, and presentation of the signal. Several sources of artefacts and potential external causes may influence the quality of the original ECG waveforms. Other factors that may affect the quality of the information presented depend upon the technical solutions employed to improve the signal. The choice of the instrumentations and solutions used to offer a high-quality ECG signal are, therefore, of paramount importance. Some requirements are reported in detail in scientific statements and recommendations. The aim of this consensus document is to give scientific reference for the choice of systems able to offer high quality ECG signal acquisition, processing, and presentation suitable for clinical use.

Prognostic indices among hypertensive heart failure patients in Nigeria: the roles of 24-hour Holter electrocardiography and 6-minute walk test

Background

Hypertensive heart failure (HHF) is associated with a poor prognosis. There is paucity of data in Nigeria on prognosis among HHF patients elucidating the role of 24-hour Holter electrocardiogram (ECG) in concert with other risk factors.

Objective

The aim of this study was to determine the prognostic utility of 24-hour Holter ECG, the 6-minute walk test (6-MWT), echocardiography, clinical and laboratory parameters among HHF patients.

Methods

A total of 113 HHF patients were recruited and followed up for 6 months. Thirteen of these patients were lost to follow-up, and as a result only 100 HHF patients were analyzed. All the patients underwent baseline laboratory tests, echocardiography, 24-hour Holter ECG and the 6-MWT. HHF patients were analyzed as “mortality vs alive” and as “events vs no-events” based on the outcome at the end of 6 months. Events was defined as HHF patients who were rehospitalized for heart failure (HF), had prolonged hospital stay or died. No-events group was defined as HHF patients who did not meet the criteria for the events group.

Results

HHF patients in the mortality group (n = 7) had significantly higher serum urea (5.71 ± 2.07 mmol/L vs 3.93 ± 1.45 mmol/L, p = 0.003) than that in those alive. After logistic regression, high serum urea conferred increased mortality risk (p = 0.035). Significant premature ventricular complexes (PVCs) on 24-hour Holter ECG following logistic regression were also significantly higher (p = 0.015) in the mortality group than in the “alive” group (n = 93) at the end of the 6-month follow-up period. The 6-minute walk distance (6-MWD) was least among the HHF patients who died (167.26 m ± 85.24 m). However, following logistic regression, the 6-MWT was not significant (p = 0.777) for predicting adverse outcomes among HHF patients. Patients in the events group (n = 41) had significantly higher New York Heart Association (NYHA) class (p = 0.001), Holter-detected ventricular tachycardia (VT; p = 0.009), Holter-detected atrial fibrillation (AF; p = 0.028) and PVCs (p = 0.017) following logistic regression than those in the no-events group (n = 59).

Conclusion

High NYHA class, elevated serum urea, Holter ECG-detected AF and ventricular arrhythmias are predictive of a poor outcome among HHF patients. The 6-MWT was not a useful prognostic index in this study.

Screening for Congenital Heart Disease in Infants with Down Syndrome: Is Universal Echocardiography Necessary?

Current guidelines recommend that all neonates with Down syndrome (DS) be screened for congenital heart disease (CHD) with an echocardiogram. We sought to determine the effectiveness of a more accessible and less expensive screening strategy consisting of physical examination, electrocardiogram (ECG), and chest X-ray. The Intermountain Healthcare Enterprise Data Warehouse was used to identify infants with a positive karyotype for DS who were born between January 1, 2000, and June 30, 2012. Infants with the results of an echocardiogram, physical examination, ECG, and chest X-ray documented at age ≤6 months were included. Infants with an abnormality on physical examination, ECG, or chest X-ray were considered to have a positive screen. Echocardiography was the gold standard for calculating sensitivity, specificity, positive and negative predictive values for major CHD, defined as any heart defect that would typically require intervention during early childhood. Of 408 eligible infants, 240 (59 %) had major CHD, of whom 228 (95 %) had a positive screen. Screening missed eight infants with moderate/large patent ductus arteriosus and four infants with a moderate/large atrial septal defect. In 11 of these infants, the defect resolved spontaneously by age ≤4 months. One infant had a moderate atrial septal defect persisting at 2-year follow-up. Sensitivity and specificity of the screening for detecting CHD were 95 % (CI 92-98 %) and 41 % (CI 32-47 %); positive and negative predictive values were 69 % (CI 63-73 %) and 85 % (CI 75-92 %). Screening with physical examination, ECG, and chest X-ray is an effective method of identifying which infants with DS should have an echocardiogram. This method would have resulted in 69 (17 %) fewer echocardiograms without missing infants with major CHD.

Computational Electrocardiography: Revisiting Holter ECG Monitoring

BACKGROUND

Since 1942, when Goldberger introduced the 12-lead electrocardiography (ECG), this diagnostic method has not been changed.

OBJECTIVES

After 70 years of technologic developments, we revisit Holter ECG from recording to understanding.

METHODS

A fundamental change is fore-seen towards "computational ECG" (CECG), where continuous monitoring is producing big data volumes that are impossible to be inspected conventionally but require efficient computational methods. We draw parallels between CECG and computational biology, in particular with respect to computed tomography, computed radiology, and computed photography. From that, we identify technology and methodology needed for CECG.

RESULTS

Real-time transfer of raw data into meaningful parameters that are tracked over time will allow prediction of serious events, such as sudden cardiac death. Evolved from Holter's technology, portable smartphones with Bluetooth-connected textile-embedded sensors will capture noisy raw data (recording), process meaningful parameters over time (analysis), and transfer them to cloud services for sharing (handling), predicting serious events, and alarming (understanding). To make this happen, the following fields need more research: i) signal processing, ii) cycle decomposition; iii) cycle normalization, iv) cycle modeling, v) clinical parameter computation, vi) physiological modeling, and vii) event prediction.

CONCLUSIONS

We shall start immediately developing methodology for CECG analysis and understanding.

The evaluation of an open source online training system for teaching 12 lead electrocardiographic interpretation

INTRODUCTION

The aim of this study is to present and evaluate the integration of a low resource JavaScript based ECG training interface (CrowdLabel) and a standardised curriculum for self-guided tuition in ECG interpretation.

METHODS

Participants practiced interpreting ECGs weekly using the CrowdLabel interface to assist with the learning of the traditional didactic taught course material during a 6 week training period. To determine competency students were tested during week 7.

RESULTS

A total of 245 unique ECG cases were submitted by each student. Accuracy scores during the training period ranged from 0-59.5% (median = 33.3%). Conversely accuracy scores during the test ranged from 30 - 70% (median = 37.5%) (p < 0.05). There was no correlation between students who interpreted high numbers of ECGs during the training period and their marks obtained.

CONCLUSIONS

CrowdLabel is shown to be a readily accessible dedicated learning platform to support ECG interpretation competency.