Recommendations for the Standardization and Interpretation of the Electrocardiogram

Delineation of 12-Lead ECG Representative Beats Using Convolutional Encoder-Decoders with Residual and Recurrent Connections

The aim of this study is to address the challenge of 12-lead ECG delineation by different encoder-decoder architectures of deep neural networks (DNNs). This study compares four concepts for encoder-decoders based on a fully convolutional architecture (CED-Net) and its modifications with a recurrent layer (CED-LSTM-Net), residual connections between symmetrical encoder and decoder feature maps (CED-U-Net), and sequential residual blocks (CED-Res-Net). All DNNs transform 12-lead representative beats to three diagnostic ECG intervals (P-wave, QRS-complex, QT-interval) used for the global delineation of the representative beat (P-onset, P-offset, QRS-onset, QRS-offset, T-offset). All DNNs were trained and optimized using the large PhysioNet ECG database (PTB-XL) under identical conditions, applying an advanced approach for machine-based supervised learning with a reference algorithm for ECG delineation (ETM, Schiller AG, Baar, Switzerland). The test results indicate that all DNN architectures are equally capable of reproducing the reference delineation algorithm's measurements in the diagnostic PTB database with an average P-wave detection accuracy (96.6%) and time and duration errors: mean values (-2.6 to 2.4 ms) and standard deviations (2.9 to 11.4 ms). The validation according to the standard-based evaluation practices of diagnostic electrocardiographs with the CSE database outlines a CED-Net model, which measures P-duration (2.6 ± 11.0 ms), PQ-interval (0.9 ± 5.8 ms), QRS-duration (-2.4 ± 5.4 ms), and QT-interval (-0.7 ± 10.3 ms), which meet all standard tolerances. Noise tests with high-frequency, low-frequency, and power-line frequency noise (50/60 Hz) confirm that CED-Net, CED-Res-Net, and CED-LSTM-Net are robust to all types of noise, mostly presenting a mean duration error < 2.5 ms when compared to measurements without noise. Reduced noise immunity is observed for the U-net architecture. Comparative analysis with other published studies scores this research within the lower range of time errors, highlighting its competitive performance.

The Danish Nationwide Electrocardiogram (ECG) Cohort

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

Context-independent identification of myocardial ischemia in the prehospital ECG of chest pain patients

Non-traumatic chest pain is a frequent reason for an urgent ambulance visit of a patient by the emergency medical services (EMS). Chest pain (or chest pain-equivalent symptoms) can be innocent, but it can also signal an acute form of severe pathology that may require prompt intervention. One of these pathologies is cardiac ischemia, resulting from a disbalance between blood supply and demand. One cause of a diminished blood supply to the heart is acute coronary syndrome (ACS, i.e., cardiac ischemia caused by a reduced blood supply to myocardial tissue due to plaque instability and thrombus formation in a coronary artery). ACS is dangerous due to the unpredictable process that drives the supply problem and the high chance of fast hemodynamic deterioration (i.e., cardiogenic shock, ventricular fibrillation). This is why an ECG is made at first medical contact in most chest pain patients to include or exclude ischemia as the cause of their complaints. For speedy and adequate triaging and treatment, immediate assessment of this prehospital ECG is necessary, still during the ambulance ride. Human diagnostic efforts supported by automated interpretation algorithms seek to answer questions regarding the urgency level, the decision if and towards which healthcare facility the patient should be transported, and the indicated acute treatment and further diagnostics after arrival in the healthcare facility. In the case of an ACS, a catheter intervention room may be activated during the ambulance ride to facilitate the earliest possible in-hospital treatment. Prehospital ECG assessment and the subsequent triaging decisions are complex because chest pain is not uniquely associated with ACS. The differential diagnosis includes other cardiac, pulmonary, vascular, gastrointestinal, orthopedic, and psychological conditions. Some of these conditions may also involve ECG abnormalities. In practice, only a limited fraction (order of magnitude 10%) of the patients who are urgently transported to the hospital because of chest pain are ACS patients. Given the relatively low prevalence of ACS in this patient mix, the specificity of the diagnostic ECG algorithms should be relatively high to prevent overtreatment and overflow of intervention facilities. On the other hand, only a sufficiently high sensitivity warrants adequate therapy when needed. Here, we review how the prehospital ECG can contribute to identifying the presence of myocardial ischemia in chest pain patients. We discuss the various mechanisms of myocardial ischemia and infarction, the typical patient mix of chest pain patients, the shortcomings of the ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI) ECG criteria to detect a completely occluded culprit artery, the OMI ECG criteria (including the STEMI-equivalent ECG patterns) in detecting completely occluded culprit arteries, and the promise of neural networks in recognizing ECG patterns that represent complete occlusions. We also discuss the relevance of detecting any ACS/ischemia, not necessarily caused by a total occlusion, in the prehospital ECG. In addition, we discuss how serial prehospital ECGs can contribute to ischemia diagnosis. Finally, we discuss the diagnostic contribution of a serial comparison of the prehospital ECG with a previously made nonischemic ECG of the patient.

Impact of automatic acquisition of key clinical information on the accuracy of electrocardiogram interpretation: a cross-sectional study

BACKGROUND

The accuracy of electrocardiogram (ECG) interpretation by doctors are affected by the available clinical information. However, having a complete set of clinical details before making a diagnosis is very difficult in the clinical setting especially in the early stages of the admission process. Therefore, we developed an artificial intelligence-assisted ECG diagnostic system (AI-ECG) using natural language processing to provide screened key clinical information during ECG interpretation.

METHODS

Doctors with varying levels of training were asked to make diagnoses from 50 ECGs using a common ECG diagnosis system that does not contain clinical information. After a two-week-blanking period, the same set of ECGs was reinterpreted by the same doctors with AI-ECG containing clinical information. Two cardiologists independently provided diagnostic criteria for 50 ECGs, and discrepancies were resolved by consensus or, if necessary, by a third cardiologist. The accuracy of ECG interpretation was assessed, with each response scored as correct/partially correct = 1 or incorrect = 0.

RESULTS

The mean accuracy of ECG interpretation was 30.2% and 36.2% with the common ECG system and AI-ECG system, respectively. Compared to the unaided ECG system, the accuracy of interpretation was significantly improved with the AI-ECG system (P for paired t-test = 0.002). For senior doctors, no improvement was found in ECG interpretation accuracy, while an AI-ECG system was associated with 27% higher mean scores (24.3 ± 9.4% vs. 30.9 ± 10.6%, P = 0.005) for junior doctors.

CONCLUSION

Intelligently screened key clinical information could improve the accuracy of ECG interpretation by doctors, especially for junior doctors.

Practical intelligent diagnostic algorithm for wearable 12-lead ECG via self-supervised learning on large-scale dataset

Cardiovascular disease is a major global public health problem, and intelligent diagnostic approaches play an increasingly important role in the analysis of electrocardiograms (ECGs). Convenient wearable ECG devices enable the detection of transient arrhythmias and improve patient health by making it possible to seek intervention during continuous monitoring. We collected 658,486 wearable 12-lead ECGs, among which 164,538 were annotated, and the remaining 493,948 were without diagnostic. We present four data augmentation operations and a self-supervised learning classification framework that can recognize 60 ECG diagnostic terms. Our model achieves an average area under the receiver-operating characteristic curve (AUROC) and average F1 score on the offline test of 0.975 and 0.575. The average sensitivity, specificity and F1-score during the 2-month online test are 0.736, 0.954 and 0.468, respectively. This approach offers real-time intelligent diagnosis, and detects abnormal segments in long-term ECG monitoring in the clinical setting for further diagnosis by cardiologists.

Association between cumulative dose of hydroxychloroquine and electrocardiographic abnormalities in patients with systemic lupus erythematosus

OBJECTIVE

Hydroxychloroquine (HCQ) is one of the most used drugs in patients with systemic lupus erythematosus (SLE). In these patients, where heart involvement is common, cardiac HCQ toxicity may lead to fatal outcomes. The aim of this work is to study the influence of cumulative HCQ (cHCQ) in a selected group of patients with SLE and its association with electrocardiographic (EKG) abnormalities.

METHODS

Single-center retrospective, observational study in which data were collected from the medical records of consecutive patients with a diagnosis of SLE who started treatment with HCQ and who had a 12-lead EKG before starting treatment and during follow-up. EKG abnormalities were grouped as conduction or structural abnormalities. The association of cHCQ with the occurrence of EKG disturbances was analyzed together with other demographic and clinical variables through univariate and multivariate logistic regression models.

RESULTS

105 patients were selected with median cHCQ of 913 g. The sample was classified into two groups, above or below 913 g. Significantly, more conduction disturbances were observed in the group above the median (OR: 2.89; 95%CI: 1.01-8.23). In the multivariate analysis, the OR per 100 g of cHCQ dose was 1.06 (95%CI: 0.99-1.14). Age was the only variable associated with conduction disturbances. There were no significant differences in the development of structural abnormalities and a tendency for more high-grade atrioventricular block was shown.

CONCLUSION

Our study suggests an association between the cHCQ and the development of EKG conduction disturbances that disappears after multivariate adjustment. No increased number of structural abnormalities was observed.

Mortality risk prediction of the electrocardiogram as an informative indicator of cardiovascular diseases

Background

The electrocardiogram (ECG) may be the most popular test in the management of cardiovascular disease (CVD). Although wide applications of artificial intelligence (AI)-enabled ECG have been developed, an integrating indicator for CVD risk stratification was not investigated. Since mortality may be the most important global outcome, this study aimed to develop a survival deep learning model (DLM) to establish a critical ECG value and explore the associations with various CVD events.

Methods

We trained a DLM with 451,950 12-lead resting ECGs obtained from 210,552 patients, for whom 23,592 events occurred. The internal validation set included 27,808 patients with one ECG for each patient. The external validations were performed in a community hospital with 33,047 patients and two transnational data sets with 233,647 and 1631 ECGs. We distinguished the cause of mortality and additionally investigated CVD-related outcomes, including new-onset acute myocardial infarction (AMI), stroke (STK), and heart failure (HF).

Results

The DLM achieved C-indices of 0.858/0.836 in internal/external validation sets by using ECG over a 10-year period. The high-mortality-risk group identified by the proposed DLM presented a hazard ratio (HR) of 14.16 (95% confidence interval (CI): 11.33-17.70) compared to the low-risk group in the internal validation and presented a higher risk of cardiovascular (CV) mortality (HR: 18.50, 95% CI: 9.82-34.84), non-CV mortality (HR: 13.68, 95% CI: 10.76-17.38), AMI (HR: 4.01, 95% CI: 2.24-7.17), STK (HR: 2.15, 95% CI: 1.70-2.72), and HF (HR: 6.66, 95% CI: 4.54-9.77), which was consistent in an independent community hospital. The transnational validation also revealed HRs of 4.91 (95% CI: 2.63-9.16) and 2.29 (95% CI: 2.15-2.44) for all-cause mortality in the SaMi-Trop and Clinical Outcomes in Digital Electrocardiography 15% (CODE15) cohorts.

Conclusions

The mortality risk by AI-enabled ECG may be applied in passive electronic-health-record-based CVD risk screening, which may identify more asymptomatic and unaware high-risk patients.

Electrocardiographic abnormalities in childhood cancer survivors treated with cardiotoxic therapy: a systematic review

PURPOSE

The purpose of this study is to assess the available literature on the prevalence and risk factors of electrocardiographic (ECG) abnormalities after cardiotoxic treatment in childhood cancer survivors (CCS).

METHODS

A literature search was performed within MEDLINE, EMBASE, and CENTRAL (1966-11/2020) and reference lists of relevant studies. Studies were eligible for inclusion if they reported ECG abnormalities ≥2 years after cancer diagnosis in ≥50 CCS treated with anthracyclines, RT involving the heart region and/or mitoxantrone. Information about population, treatment, outcome, and risk factors were extracted and risk of bias was assessed.

RESULTS

Of 934 identified publications, 10 studies were included. Outcome definitions, treatment regimens, follow-up period, and risk of bias varied. These ECG abnormalities and prevalences were reported: major (5%-23%) and minor (12%) abnormalities according to the Minnesota Code, rhythm abnormalities (0%-12%), conduction abnormalities (0.3%-7.1%), depolarization abnormalities (0%), and repolarization abnormalities (0%-65%). The reported risk factors of ECG abnormalities (two studies) are male sex, anthracyclines, RT involving the heart region, and hypertension, although results were not univocal between studies and abnormalities.

CONCLUSIONS

Multiple ECG abnormalities have been described in CCS ≥2 years from diagnosis, some of which can have important implications. Future research is needed to evaluate the exact long-term incidence and risk factors, and to investigate their clinical relevance and relation with cardiac dysfunction or future cardiac events. This could improve cardiac surveillance for CCS.

A large-scale multi-label 12-lead electrocardiogram database with standardized diagnostic statements

Deep learning approaches have exhibited a great ability on automatic interpretation of the electrocardiogram (ECG). However, large-scale public 12-lead ECG data are still limited, and the diagnostic labels are not uniform, which increases the semantic gap between clinical practice. In this study, we present a large-scale multi-label 12-lead ECG database with standardized diagnostic statements. The dataset contains 25770 ECG records from 24666 patients, which were acquired from Shandong Provincial Hospital (SPH) between 2019/08 and 2020/08. The record length is between 10 and 60 seconds. The diagnostic statements of all ECG records are in full compliance with the AHA/ACC/HRS recommendations, which aims for the standardization and interpretation of the electrocardiogram, and consist of 44 primary statements and 15 modifiers as per the standard. 46.04% records in the dataset contain ECG abnormalities, and 14.45% records have multiple diagnostic statements. The dataset also contains additional patient demographics.

Measurement(s)	12-lead electrocardiogram
Technology Type(s)	EKG or ECG Monitor Device

Remote and Wearable ECG Devices with Diagnostic Abilities in Adults: A State-of-the-Science Scoping Review

The electrocardiogram (ECG) records the electrical activity in the heart in real-time, providing an important opportunity to detecting various cardiac pathologies. The 12-lead ECG currently serves as the "standard" ECG acquisition technique for diagnostic purposes for many cardiac pathologies other than arrhythmias. However, the technical aspects of acquiring a 12-lead ECG are not easy and its usage is currently restricted to trained medical personnel, limiting the scope of its usefulness. Remote and wearable ECG devices have attempted to bridge this gap by enabling patients to take their own ECG using a simplified method at the expense of a reduced number of leads, usually a single-lead ECG. In this review article, we summarize the studies which investigate the use of remote ECG devices and their clinical utility in diagnosing cardiac pathologies. Eligible studies discussed FDA-cleared, commercially available devices that were validated on an adult population. We summarize technical logistics of signal quality and device reliability, dimensional and functional features, and diagnostic value. In summary, our synthesis shows that reduced-set ECG wearables have huge potential for long-term monitoring, particularly if paired with real-time notification techniques. Such capabilities make them primarily useful for abnormal rhythm detection and there is sufficient evidence that a remote ECG device can be more superior to traditional 12-lead ECG in diagnosing specific arrhythmias such as atrial fibrillation. However, this review identifies important challenges faced by this technology, highlighting the limited availability of clinical research examining their usefulness.

Electrocardiographic diagnosis of atrial cardiomyopathy to predict atrial contractile dysfunction, thrombogenesis and adverse cardiovascular outcomes

Thromboembolism and stroke are dreaded complications in atrial fibrillation (AF). Established risk stratification models identify susceptible patients, but their discriminative properties are poor. Atrial cardiomyopathy (ACM) is associated to thromboembolism and stroke in smaller studies, but the modalities used for ACM-diagnosis (MRI and endocardial mapping) are unsuitable for widespread population screening. We aimed to investigate an ECG-based diagnosis of ACM using amplified p-wave analysis (APWA) for stratification of thromboembolic risk and cardiovascular outcome. In this case–control study, ACM-staging was performed using APWA on digital 12-lead sinus rhythm-ECGs in patients with LAA-thrombus and a propensity-score-matched control-cohort. Left atrial contractile function and thrombi were evaluated by transesophageal echocardiography (TEE). Outcome for MACCE including death was assessed using official registries and structured phone interviews. Left-atrial appendage [LAA]-thrombi and appropriate sinus rhythm-ECGs for ACM-staging were found in 109 of 4086 patients that were matched 1:1 to control patients without thrombus (218 patients in total). Both cohorts were comparable regarding cardiovascular risk factors, anticoagulants and CHA2DS2-VASC-score. ACM-stages 1 to 3 (equivalent to no, moderate and extensive ACM) were found in 63 (57.8%), 36 (33.0%) and 10 (9.2%) of patients without and 3 (2.8%), 23 (21.1%) and 83 (76.1%) of patients with LAA-thrombi. Atrial contractile function decreased from ACM-stages 1 to 3 (LAA-flow velocities 38 ± 16 cm/s, 31 ± 15 cm/s and 21 ± 12 cm/s; p < 0.0001), while the likelihood for LAA-thrombus increased (2.8%, 21.1% and 76.1%, p < 0.001). Multivariable analysis confirmed an independent odds ratio for LAA-thrombus of 24.6 (p < 0.001) per ACM-stage. Two-year survival free of stroke/TIA, hospitalization for heart failure, myocardial infarction or all-cause death was strongly reduced in ACM-stage 3 (53.8%) compared to no or moderate ACM (82.8% and 84.7%, respectively; p < 0.0001). Electrocardiographic diagnosis of ACM identifies patients with atrial contractile dysfunction and atrial thrombi at risk for adverse cardiovascular outcomes and death.

Echocardiographic study of cardiac structure and function in people with bipolar disorder after midlife

BACKGROUND

Heart failure is the leading cause of mortality in older people with bipolar disorder (BD). Studies examining cardiac structure and function in middle-aged patients with BD by using echocardiography and cardiac strain imaging are scant.

METHODS

We recruited 48 patients with bipolar I disorder (BD-I) older than 45 years to undergo conventional and tissue speckle tracking echocardiography. Data of 31 mentally healthy adults older than 45 years were randomly retrieved from the echocardiographic dataset and compared with the data of BD patients.

RESULTS

Patients with BD-I had significantly higher mean values of interventricular septal thickness (Cohen's d = 0.83, p = 0.001) and left ventricular internal diameter (Cohen's d = 0.90, p = 0.001) at end-diastole relative to controls. Additionally, BD-I patients exhibited significantly lower mean values of mitral valve E/A ratio (Cohen's d = 0.67, p = 0.007) and a more reduced global longitudinal strain (Cohen's d = 0.72, p = 0.029) than controls. Multiple linear regression revealed that body mass index was negatively correlated with the mitral valve E/A ratio (adjustment R² = 0.363, p = 0.043) in patients with BD-I.

LIMITATIONS

A relatively small sample size may limit generalization.

CONCLUSIONS

After midlife, BD patients exhibit cardiac diastolic (low mitral valve E/A ratio) and systolic (reduced global longitudinal strain) dysfunction. High body mass index may play a role in the unfavorable cardiac function in aging patients with BD.

Prognostic value of initial electrocardiography in predicting long-term all-cause mortality in COVID-19

BACKGROUND

The electrocardiography (ECG) has short-term prognostic value in coronavirus disease 2019 (COVID-19), yet its ability to predict long-term mortality is unknown. This study aimed to elucidate the predictive role of initial ECG on long-term all-cause mortality in patients diagnosed with COVID-19.

METHODS

In this prospective cohort study, adults with COVID-19 who underwent ECG testing within a 17-hospital health system in Northeast Ohio and Florida between 03/2020-06/2020 were identified. An expert ECG reader analyzed all studies blinded to patient status. The associations of ECG characteristics with long-term all-cause mortality and intensive care unit (ICU) admission were assessed using Cox proportional hazards regression model and multivariable logistic regression models, respectively. Status of long-term mortality was adjudicated on 01/07/2022.

RESULTS

Of 837 patients (median age 65 years, 51% female, 44% Black), 683 (81.6%) were hospitalized, 281 (33.6%) required ICU admission, 67 (8.0%) died in-hospital, and 206 (24.6%) died at final follow-up after a median (IQR) of 21 (9-103) days after ECG. Overall, 179 (20.7%) patients presented with sinus tachycardia, 12 (1.4%) with atrial flutter, and 45 (5.4%) with atrial fibrillation (AF). After multivariable adjustment, sinus tachycardia (E-value for HR=3.09, lower CI=2.2) and AF (E-value for HR=3.13, lower CI=2.03) each independently predicted all-cause mortality. At final follow-up, patients with AF had 64.5% probability of death compared with 20.5% for those with normal sinus rhythm (P<.0001).

CONCLUSIONS

Sinus tachycardia and AF on initial ECG strongly predict long-term all-cause mortality in COVID-19. The ECG can serve as a powerful long-term prognostic tool in COVID-19.

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.

Cardiac monitoring for patients with palpitations

Palpitations are one of the most common reasons for medical consultation. They tend to worry patients and can affect their quality of life. They are often a symptom associated with cardiac rhythm disorders, although there are other etiologies. For diagnosis, it is essential to be able to reliably correlate the symptoms with an electrocardiographic record allowing the identification or ruling out of a possible rhythm disorder. However, reaching a diagnosis is not always simple, given that they tend to be transitory symptoms and the patient is frequently asymptomatic at the time of assessment. In recent years, electrocardiographic monitoring systems have incorporated many technical improvements that solve several of the 24-h Holter monitor limitations. The objective of this review is to provide an update on the different monitoring methods currently available, remarking their indications and limitations, to help healthcare professionals to appropriately select and use them in the work-up of patients with palpitations.

Critical thinking and diagnostic reasoning of the heart and cardiovascular system

This is the second of two articles exploring assessment and clinical reasoning of conditions relating to the heart and cardiovascular system in the context of emergency care. In the last article, the structure and function of the heart was reviewed, and reference made to many of the conditions that may affect the heart. In addition, the common presenting complaints of cardiac conditions were highlighted, together with important aspects of the history for each symptom. The full cardiac examination was outlined. In this article, some of the common cardiac conditions will be discussed. These will be linked to common findings in the history, examination, and investigations.

Decoding Electrophysiological Signals with Organic Electrochemical Transistors

The organic electrochemical transistor (OECT) has unique characteristics that distinguish it from other transistors and make it a promising electronic transducer of biological events. High transconductance, flexibility, and biocompatibility render OECTs ideal for detecting electrophysiological signals. Device properties such as transconductance, response time, and noise level should, however, be optimized to adapt to the needs of various application environments including in vitro cell culture, human skin, and inside of a living system. This review includes an overview of the origin of electrophysiological signals, the working principles of OECTs, and methods for performance optimization. While covering recent research examples of the use of OECTs in electrophysiology, a perspective is provided for next-generation bioelectric sensors and amplifiers for electrophysiology applications.

Clinically contextualised ECG interpretation: the impact of prior clinical exposure and case vignettes on ECG diagnostic accuracy

BACKGROUND

ECGs are often taught without clinical context. However, in the clinical setting, ECGs are rarely interpreted without knowing the clinical presentation. We aimed to determine whether ECG diagnostic accuracy was influenced by knowledge of the clinical context and/or prior clinical exposure to the ECG diagnosis.

METHODS

Fourth- (junior) and sixth-year (senior) medical students, as well as medical residents were invited to complete two multiple-choice question (MCQ) tests and a survey. Test 1 comprised 25 ECGs without case vignettes. Test 2, completed immediately thereafter, comprised the same 25 ECGs and MCQs, but with case vignettes for each ECG. Subsequently, participants indicated in the survey when last, during prior clinical clerkships, they have seen each of the 25 conditions tested. Eligible participants completed both tests and survey. We estimated that a minimum sample size of 165 participants would provide 80% power to detect a mean difference of 7% in test scores, considering a type 1 error of 5%.

RESULTS

This study comprised 176 participants (67 [38.1%] junior students, 55 [31.3%] senior students, 54 [30.7%] residents). Prior ECG exposure depended on their level of training, i.e., junior students were exposed to 52% of the conditions tested, senior students 63.4% and residents 96.9%. Overall, there was a marginal improvement in ECG diagnostic accuracy when the clinical context was known (Cohen's d = 0.35, p < 0.001). Gains in diagnostic accuracy were more pronounced amongst residents (Cohen's d = 0.59, p < 0.001), than senior (Cohen's d = 0.38, p < 0.001) or junior students (Cohen's d = 0.29, p < 0.001). All participants were more likely to make a correct ECG diagnosis if they reported having seen the condition during prior clinical training, whether they were provided with a case vignette (odds ratio [OR] 1.46, 95% confidence interval [CI] 1.24-1.71) or not (OR 1.58, 95% CI 1.35-1.84).

CONCLUSION

ECG interpretation using clinical vignettes devoid of real patient experiences does not appear to have as great an impact on ECG diagnostic accuracy as prior clinical exposure. However, exposure to ECGs during clinical training is largely opportunistic and haphazard. ECG training should therefore not rely on experiential learning alone, but instead be supplemented by other formal methods of instruction.

Pathologies affect the performance of ECG signals compression

The performance of ECG signals compression is influenced by many things. However, there is not a single study primarily focused on the possible effects of ECG pathologies on the performance of compression algorithms. This study evaluates whether the pathologies present in ECG signals affect the efficiency and quality of compression. Single-cycle fractal-based compression algorithm and compression algorithm based on combination of wavelet transform and set partitioning in hierarchical trees are used to compress 125 15-leads ECG signals from CSE database. Rhythm and morphology of these signals are newly annotated as physiological or pathological. The compression performance results are statistically evaluated. Using both compression algorithms, physiological signals are compressed with better quality than pathological signals according to 8 and 9 out of 12 quality metrics, respectively. Moreover, it was statistically proven that pathological signals were compressed with lower efficiency than physiological signals. Signals with physiological rhythm and physiological morphology were compressed with the best quality. The worst results reported the group of signals with pathological rhythm and pathological morphology. This study is the first one which deals with effects of ECG pathologies on the performance of compression algorithms. Signal-by-signal rhythm and morphology annotations (physiological/pathological) for the CSE database are newly published.

Accuracy of Physicians' Electrocardiogram Interpretations: A Systematic Review and Meta-analysis

IMPORTANCE

The electrocardiogram (ECG) is the most common cardiovascular diagnostic test. Physicians' skill in ECG interpretation is incompletely understood.

OBJECTIVES

To identify and summarize published research on the accuracy of physicians' ECG interpretations.

DATA SOURCES

A search of PubMed/MEDLINE, Embase, Cochrane CENTRAL (Central Register of Controlled Trials), PsycINFO, CINAHL (Cumulative Index to Nursing and Allied Health), ERIC (Education Resources Information Center), and Web of Science was conducted for articles published from database inception to February 21, 2020.

STUDY SELECTION

Of 1138 articles initially identified, 78 studies that assessed the accuracy of physicians' or medical students' ECG interpretations in a test setting were selected.

DATA EXTRACTION AND SYNTHESIS

Data on study purpose, participants, assessment features, and outcomes were abstracted, and methodological quality was appraised with the Medical Education Research Study Quality Instrument. Results were pooled using random-effects meta-analysis.

MAIN OUTCOMES AND MEASURES

Accuracy of ECG interpretation.

RESULTS

Of 1138 studies initially identified, 78 assessed the accuracy of ECG interpretation. Across all training levels, the median accuracy was 54% (interquartile range [IQR], 40%-66%; n = 62 studies) on pretraining assessments and 67% (IQR, 55%-77%; n = 47 studies) on posttraining assessments. Accuracy varied widely across studies. The pooled accuracy for pretraining assessments was 42.0% (95% CI, 34.3%-49.6%; n = 24 studies; I2 = 99%) for medical students, 55.8% (95% CI, 48.1%-63.6%; n = 37 studies; I2 = 96%) for residents, 68.5% (95% CI, 57.6%-79.5%; n = 10 studies; I2 = 86%) for practicing physicians, and 74.9% (95% CI, 63.2%-86.7%; n = 8 studies; I2 = 22%) for cardiologists.

CONCLUSIONS AND RELEVANCE

Physicians at all training levels had deficiencies in ECG interpretation, even after educational interventions. Improved education across the practice continuum appears warranted. Wide variation in outcomes could reflect real differences in training or skill or differences in assessment design.

Modelling of the electrocardiographic signal during an angioplasty procedure in the right coronary artery

Dynamical models are useful tools to generate sets of varied morphological signals by synthesizing human electrocardiograms (ECGs). These signals are used for testing and improving algorithms of ECG delineation, patient monitoring and heart disease detection. This work presents a procedure based on the ECGSYN model to synthesize ECG morphological changes induced by a percutaneous transluminal coronary angioplasty (PTCA) procedure in the right coronary artery. We provide a set of parameters to be used in ECGSYN and generate heartbeats with altered ST-T complexes. These characteristic model parameters were obtained through a non-linear fitting algorithm applied to every available heartbeat. To extend these parameters, normal distributions were generated with their means and standard deviations obtained from the STAFF III database. Parameters were presented for P, QRS and T-waves at leads II, III and aVF. The synthesis procedure shows an average correlation and positive predictive value of 92.2% and 88.2%, respectively. In conclusion, we provide a technique capable of synthesizing electrocardiographic ischemic morphology with physiological plausibility. Then, the generation of data sets for algorithm testing can benefit from this system of ECG signal synthesis.

Predicting sustained ventricular arrhythmias in dilated cardiomyopathy: a meta-analysis and systematic review

AIMS

Patients with non-ischaemic dilated cardiomyopathy (DCM) are at increased risk of sudden cardiac death. Identification of patients that may benefit from implantable cardioverter-defibrillator implantation remains challenging. In this study, we aimed to determine predictors of sustained ventricular arrhythmias in patients with DCM.

METHODS AND RESULTS

We searched MEDLINE/Embase for studies describing predictors of sustained ventricular arrhythmias in patients with DCM. Quality and bias were assessed using the Quality in Prognostic Studies tool, articles with high risk of bias in ≥2 areas were excluded. Unadjusted hazard ratios (HRs) of uniformly defined predictors were pooled, while all other predictors were evaluated in a systematic review. We included 55 studies (11 451 patients and 3.7 ± 2.3 years follow-up). Crude annual event rate was 4.5%. Younger age [HR 0.82; 95% CI (0.74-1.00)], hypertension [HR 1.95; 95% CI (1.26-3.00)], prior sustained ventricular arrhythmia [HR 4.15; 95% CI (1.32-13.02)], left ventricular ejection fraction on ultrasound [HR 1.45; 95% CI (1.19-1.78)], left ventricular dilatation (HR 1.10), and presence of late gadolinium enhancement [HR 5.55; 95% CI (4.02-7.67)] were associated with arrhythmic outcome in pooled analyses. Prior non-sustained ventricular arrhythmia and several genotypes [mutations in Phospholamban (PLN), Lamin A/C (LMNA), and Filamin-C (FLNC)] were associated with arrhythmic outcome in non-pooled analyses. Quality of evidence was moderate, and heterogeneity among studies was moderate to high.

CONCLUSIONS

In patients with DCM, the annual event rate of sustained ventricular arrhythmias is approximately 4.5%. This risk is considerably higher in younger patients with hypertension, prior (non-)sustained ventricular arrhythmia, decreased left ventricular ejection fraction, left ventricular dilatation, late gadolinium enhancement, and genetic mutations (PLN, LMNA, and FLNC). These results may help determine appropriate candidates for implantable cardioverter-defibrillator implantation.

Automatic Triage of 12-Lead ECGs Using Deep Convolutional Neural Networks

BACKGROUND

The correct interpretation of the ECG is pivotal for the accurate diagnosis of many cardiac abnormalities, and conventional computerized interpretation has not been able to reach physician‐level accuracy in detecting (acute) cardiac abnormalities. This study aims to develop and validate a deep neural network for comprehensive automated ECG triage in daily practice.

METHODS AND RESULTS

We developed a 37‐layer convolutional residual deep neural network on a data set of free‐text physician‐annotated 12‐lead ECGs. The deep neural network was trained on a data set with 336.835 recordings from 142.040 patients and validated on an independent validation data set (n=984), annotated by a panel of 5 cardiologists electrophysiologists. The 12‐lead ECGs were acquired in all noncardiology departments of the University Medical Center Utrecht. The algorithm learned to classify these ECGs into the following 4 triage categories: normal, abnormal not acute, subacute, and acute. Discriminative performance is presented with overall and category‐specific concordance statistics, polytomous discrimination indexes, sensitivities, specificities, and positive and negative predictive values. The patients in the validation data set had a mean age of 60.4 years and 54.3% were men. The deep neural network showed excellent overall discrimination with an overall concordance statistic of 0.93 (95% CI, 0.92–0.95) and a polytomous discriminatory index of 0.83 (95% CI, 0.79–0.87).

CONCLUSIONS

This study demonstrates that an end‐to‐end deep neural network can be accurately trained on unstructured free‐text physician annotations and used to consistently triage 12‐lead ECGs. When further fine‐tuned with other clinical outcomes and externally validated in clinical practice, the demonstrated deep learning–based ECG interpretation can potentially improve time to treatment and decrease healthcare burden.

Electrical Remodeling of Ventricular Repolarization Abnormality after Treatment in Pheochromocytoma: U Wave Finding in a Retrospective Analysis

Background

Pheochromocytoma is a rare neuroendocrine tumor, clinically characterized by high blood pressure, palpitations, and headache. It is often associated with abnormalities of the ventricular repolarization phase; the dispersion of ventricular repolarization is the basis for ventricular arrhythmias (torsion de point, ventricular tachycardia or ventricular fibrillation).

Objectives

Analysis of abnormal ventricular repolarization focused on the presence and amount of U wave in patients affected by pheochromocytoma and its modification after surgery.

Materials and Methods

We reviewed pathology records of 722 patients admitted for adrenal nodule or suspected chromaffin-cell tumor and identified 39 patients affected by pheochromocytoma. Metanephrine, normetanephrine, and 3-methoxytyramine have been assessed by determining concentrations in 24-hour urine collection. Standard 12-lead electrocardiogram records have been reviewed with analysis of heart rate, P wave, PR interval, QRS duration, QTc, and U wave. Then we selected and compared 22 patients of 39 affected by pheochromocytoma, with both clinical and electrocardiographic data before and after surgery.

Results

In our cohort of 39 patients affected by pheochromocytoma, we found U wave in ECG, before treatment, in 82.8 percent of patients, while only 37.0 percent after treatment (p<0.001) and we observed a statistically significant correlation between this wave and the urinary metanephrine. After surgery, in the selected 22 patients, we observed a clear significant reduction in systemic blood pressure, fasting glucose, metanephrine, normetanephrine, and 3-methoxytyramine. We found a significant reduction of U wave presence and leads involved in these patients after surgery (90.9% versus 9%). We observed a linear correlation between the amount of U waves in 12-lead electrocardiogram and metanephrine (r²=0.333, p=0.015), 3-methoxytyramine levels (r²=0.458, p=0.006), and tumor size (r²=0.429, p=0.003).

Conclusions

In our retrospective analysis, patients affected by pheochromocytoma presented U wave in electrocardiogram. The presence and amount of U wave were associated with the metanephrine levels and the tumor size with significant reduction after surgical removal.

Early differentiation of long-standing persistent atrial fibrillation using the characteristics of fibrillatory waves in surface ECG multi-leads

We characterized the f-waves in atrial fibrillation (AF) in the surface ECG by quantifying the amplitude, irregularity, and dominant rate of the f-waves in leads II, aVL, and V₁, and investigated whether those parameters of the f-waves could discriminate long-standing persistent AF (LPeAF) from non-LPeAF. A total of 224 AF patients were enrolled: 112 with PAF (87 males), 48 with PeAF (38 males), and 64 with LPeAF (47 males). The f-waves in surface ECG leads V₁, aVL, and II, which reflect well electrical activity in the right atrium (RA), the left atrium (LA), and both atria, respectively, were analyzed. The f-waves for LPeAF had lower amplitudes in II and aVL, increased irregularity and a higher dominant rate in II and V₁ compared to PAF and PeAF (all p < 0.02). In a multivariate analysis, a low amplitude in lead II (<34.6 uV) and high dominant rate in lead V₁ (≧390/min) (p < 0.00₁) independently discriminated LPeAF from the other AF types. The f-waves combined with both a low amplitude in lead II and high dominant rate in lead V₁ were significantly associated with LPeAF (OR 6.27, p < 0.001). Characteristics of the f-waves on the surface ECG could discriminate LPeAF from other types of AF.

QRS duration and dispersion for predicting ventricular arrhythmias in early stage of acute myocardial infraction

OBJECTIVE

To determine the relationship between QRS duration and dispersion and the occurrence of ventricular arrhythmias in early stages of acute myocardial infarction (AMI).

DESIGN

A retrospective, longitudinal descriptive study was carried out.

SETTING

Hospital General Universitario "Camilo Cienfuegos", Sancti Spíritus, Cuba. Secondary health care.

PATIENTS OR PARTICIPANTS

A total of 209 patients diagnosed with ST-segment elevation AMI from January 2012 to June 2014.

MAIN VARIABLES OF INTEREST

The duration and dispersion of the QT interval, corrected QT interval, and QRS complex were measured in the first electrocardiogram performed at the hospital. The presence of ventricular tachycardia/fibrillation was assessed during follow-up (length of hospital stay).

RESULTS

Arrhythmias were found in 46 patients (22%); in 25 of them (15.9%), arrhythmias originated in ventricles, and were more common in those subjects with extensive anterior wall AMI, which was responsible for 81.8% of the ventricular fibrillations and more than half (57.1%) of the ventricular tachycardias. The widest QRS complexes (77.3±13.3 vs. 71.5±6.4ms; P=.029) and their greatest dispersion (24.1±16.2 vs. 16.5±4.8ms; P=.019) were found on those leads that explore the regions affected by ischemia. The highest values of all measurements were found in extensive anterior wall AMI, with significant differences: QRS 92.3±18.8ms, QRS dispersion 37.9±23.9ms, corrected QT 518.5±72.2ms, and corrected QT interval dispersion 94.9±26.8ms. Patients with higher QRS dispersion values were more likely to have ventricular arrhythmias, with cutoff points at 23.5ms and 24.5ms for tachycardia and ventricular fibrillation, respectively.

CONCLUSIONS

Increased QRS duration and dispersion implied a greater likelihood of ventricular arrhythmias in early stages of AMI than increased duration and dispersion of the corrected QT interval.

CSE database: extended annotations and new recommendations for ECG software testing

Nowadays, cardiovascular diseases represent the most common cause of death in western countries. Among various examination techniques, electrocardiography (ECG) is still a highly valuable tool used for the diagnosis of many cardiovascular disorders. In order to diagnose a person based on ECG, cardiologists can use automatic diagnostic algorithms. Research in this area is still necessary. In order to compare various algorithms correctly, it is necessary to test them on standard annotated databases, such as the Common Standards for Quantitative Electrocardiography (CSE) database. According to Scopus, the CSE database is the second most cited standard database. There were two main objectives in this work. First, new diagnoses were added to the CSE database, which extended its original annotations. Second, new recommendations for diagnostic software quality estimation were established. The ECG recordings were diagnosed by five new cardiologists independently, and in total, 59 different diagnoses were found. Such a large number of diagnoses is unique, even in terms of standard databases. Based on the cardiologists' diagnoses, a four-round consensus (4R consensus) was established. Such a 4R consensus means a correct final diagnosis, which should ideally be the output of any tested classification software. The accuracy of the cardiologists' diagnoses compared with the 4R consensus was the basis for the establishment of accuracy recommendations. The accuracy was determined in terms of sensitivity = 79.20-86.81%, positive predictive value = 79.10-87.11%, and the Jaccard coefficient = 72.21-81.14%, respectively. Within these ranges, the accuracy of the software is comparable with the accuracy of cardiologists. The accuracy quantification of the correct classification is unique. Diagnostic software developers can objectively evaluate the success of their algorithm and promote its further development. The annotations and recommendations proposed in this work will allow for faster development and testing of classification software. As a result, this might facilitate cardiologists' work and lead to faster diagnoses and earlier treatment.

The LIFE-Adult-Study: objectives and design of a population-based cohort study with 10,000 deeply phenotyped adults in Germany

Background

The LIFE-Adult-Study is a population-based cohort study, which has recently completed the baseline examination of 10,000 randomly selected participants from Leipzig, a major city with 550,000 inhabitants in the east of Germany. It is the first study of this kind and size in an urban population in the eastern part of Germany. The study is conducted by the Leipzig Research Centre for Civilization Diseases (LIFE). Our objective is to investigate prevalences, early onset markers, genetic predispositions, and the role of lifestyle factors of major civilization diseases, with primary focus on metabolic and vascular diseases, heart function, cognitive impairment, brain function, depression, sleep disorders and vigilance dysregulation, retinal and optic nerve degeneration, and allergies.

Methods/design

The study covers a main age range from 40-79 years with particular deep phenotyping in elderly participants above the age of 60. The baseline examination was conducted from August 2011 to November 2014. All participants underwent an extensive core assessment programme (5-6 h) including structured interviews, questionnaires, physical examinations, and biospecimen collection. Participants over 60 underwent two additional assessment programmes (3-4 h each) on two separate visits including deeper cognitive testing, brain magnetic resonance imaging, diagnostic interviews for depression, and electroencephalography.

Discussion

The participation rate was 33 %. The assessment programme was accepted well and completely passed by almost all participants. Biomarker analyses have already been performed in all participants. Genotype, transcriptome and metabolome analyses have been conducted in subgroups. The first follow-up examination will commence in 2016.

Cardiac abnormalities after aneurysmal subarachnoid hemorrhage: effects of β-blockers and angiotensin-converting enzyme inhibitors

BACKGROUND

Cardiac abnormalities attributed to adrenergic surge are common after aneurysmal subarachnoid hemorrhage. Prescribed medications that block adrenergic stimulation may suppress the onset of cardiopulmonary compromise in patients after aneurysmal subarachnoid hemorrhage.

OBJECTIVES

To compare the incidence of early cardiac complications between patients who reported prescribed use of β-blockers and/or angiotensin-converting enzyme inhibitors before aneurysmal subarachnoid hemorrhage and patients who did not.

METHODS

A retrospective review of 254 adult patients after acute aneurysmal subarachnoid hemorrhage who were enrolled in an existing R01 study. Demographic data and history were obtained from patients'/proxies' reports and charts. Cardiac enzyme levels, 12-lead electrocardiograms, and chest radiographs were obtained on admission. Holter monitoring and echocardiograms were completed as a part of the R01 study.

RESULTS

Patients reporting prescribed use of angiotensin-converting enzyme inhibitors or β-blockers before aneurysmal subarachnoid hemorrhage had more ventricular and supraventricular ectopy on a Holter report than did patients who did not (P < .05). When age, race, sex, and injury (Fisher grade) were controlled for, patients reporting use of β-blockers were 8 times more likely than others to have occasional to frequent ventricular ectopy (P = .02).

CONCLUSION

No concrete evidence was found that exposure to adrenergic blockade before aneurysmal subarachnoid hemorrhage provides protection from neurocardiac injury.

Comparison of twelve-lead electrocardiogram using a glove-based recording system with standard methodology

We tested the clinically relevant diagnostic accuracy of a new electrocardiographic (ECG) recording system incorporating all 10 ECG electrodes in a single-size glove worn on the patient's left arm and placed on the chest. The PhysioGlove (PG) was designed to allow fast, reproducible, electrode placement with only minimal training. The American College of Cardiology/American Heart Association ECG recording guidelines and others have repeatedly highlighted the unacceptable progressive deterioration in ECG accuracy mainly resulting from a performer's lack of proficiency and diligence, leading to frequent electrode misplacement. We studied 428 consenting adult patients with a broad spectrum of anthropomorphic characteristics and ECG and cardiovascular pathologic entities. The chest girth was measured to ascertain the single-size PG clinical diagnostic accuracy in ≥90% of this patient population. For each patient, a PG and standard-cable electrocardiogram were consecutively recorded and interpreted by experienced electrocardiographers. The study included 3 phases: phase 1, run-in (n = 120); phase 2, comparative diagnostic accuracy (n = 208); and phase 3, randomized, blinded, diagnostic accuracy (n = 100). Of the entire study population (n = 428), 92% fit the chest girth range of 85 to 118 cm (34 to 47 in.), representing the reference standard clinical diagnostic PG chest girth range. The phase 2 PG diagnostic accuracy was 91.3% for entire chest girth range and 95.7% for the 89.4% of patients with a chest girth within the reference range. The mean PG diagnostic accuracy in phase 3 was 93% (95% confidence interval 89% to 95%). In conclusion, compared with standard-cable electrocardiograms, the PG demonstrated excellent diagnostic accuracy (93% to 95.7%) in ≥90% of a typical western adult patient population. The PG's ease of use and minimal training requirements offer a promising tool to markedly improve ECG clinical diagnostic accuracy in most adult western patients.

Electrocardiographic characteristics in patients with pulmonary sarcoidosis indicating cardiac involvement

INTRODUCTION

Sarcoidosis is a multisystem granulomatous disease that can affect the heart. Early identification of cardiac sarcoidosis (CS) is critical because sudden death can be the initial presentation. We sought to evaluate the potential role of the ECG for identification of cardiac involvement in a cohort of patients with biopsy-proven pulmonary sarcoidosis.

METHODS

Our cohort consisted of referred patients with biopsy-proven pulmonary sarcoidosis who demonstrated symptoms consistent with cardiac involvement. The ECG characteristics collected were PR, QRS duration, QT interval, rate, bundle branch block (BBB), fragmented QRS (fQRS). QRS fragmentation was defined as 2 anatomically contiguous leads demonstrating RSR' patterns in the absence of BBB.

RESULTS

There were 112 subjects included in the cohort. Of the 52 subjects eventually diagnosed with CS, 39 had an ECG demonstrating fQRS while 21 of the 60 of non-CS patients had fQRS (75% vs 33.9%, P < 0.01). A RBBB or LBBB pattern were both more prevalent in the CS population (RBBB: 23.1% vs 6.7%, P = 0.016; LBBB: 3.8% vs 1.7%, P = 0.6). QRS duration remained significantly associated with CS after exclusion of those with BBB (93.5 +/- 10.6 vs 88 +/- 11 ms; P = 0.04). When fQRS and bundle branch block were combined, 90.4% of CS patient's ECGs contained at least one of the features, compared to 36.7% of noncardiac CS (P < 0.01).

CONCLUSIONS

The presence of fQRS or BBB pattern in patients with pulmonary sarcoidosis is associated with cardiac involvement and therefore should prompt further evaluation.

The ECG dilemma: guidelines on improving interpretation

The "ECG Dilemma" was recognized by the American College of Cardiology (ACC) and the American Heart Association more than 10 years ago. Estimates put the number of patients suffering from significant ECG interpretation errors every year in the same range as deaths from diabetes. Missed MI ranks in the top tier of malpractice dollars lost. Guidelines have been put forth to reduce these losses and improve patient safety and quality of care. These guidelines, and suggestions towards implementing them, are discussed.