Evaluation of Mortality in Atrial Fibrillation: Clinical Outcomes in Digital Electrocardiography (CODE) Study.

Aims: Atrial fibrillation (AF) is a public health problem and its prevalence is increasing worldwide. Electronic cohorts, with large electrocardiogram (ECG) databases linked to mortality data, can be useful in determining prognostic value of ECG abnormalities. Our aim is to evaluate the risk of mortality in patients with AF from Brazil. Methods: This observational retrospective study of primary care patients was developed with the digital ECG database from the Telehealth Network of Minas Gerais, Brazil. ECGs performed from 2010 to 2017 were interpreted by cardiologists and the University of Glasgow automated analysis software. An electronic cohort was obtained linking data from ECG exams and those from a national mortality information system, using standard probabilistic linkage methods. We considered only the first ECG of each patient. Patients under 16 years were excluded. Hazard ratios (HR) for mortality were adjusted for demographic and self-reported clinical factors and estimated with Cox regression. Results: From a dataset of 1,773,689 patients, 1,558,421 were included, mean age 51.6 years; 40.2% male. There were 3.34% deaths from all causes in 3.68 years of median follow up. The prevalence of AF was 1.33%. AF was an independent risk factor for all-cause mortality (HR 2.10, 95%CI 2.03-2.17) and cardiovascular mortality (HR 2.06, 95%CI 1.86-2.29). Females with AF had a higher risk of overall and cardiovascular mortality compared with males (p < 0.001). Conclusions: AF was a strong predictor of cardiovascular and all-cause mortality in a primary care population, with increased risk in women. Condensed abstract: To assess risk of mortality in AF patients, an electronic cohort was obtained linking data from ECG exams of Brazilian primary care patients and a national mortality information system. From 1,558,421 patients, AF (prevalence 1.33%) carried a higher risk of overall and cardiovascular mortality, with increased risk in women. What's New: This is the first study with a large Brazilian electronic cohort to evaluate the risk of mortality linked to AF in primary care patients.AF patients from a Brazilian primary care population had a higher risk of death for all causes (HR 2.10, 95%CI 2.03-2.17) and cardiovascular mortality (HR 2.06, 95%CI 1.86-2.29).Female patients with AF had an increased risk of overall and cardiovascular mortality compared with male patients (p < 0.001).

Author Correction: Automatic diagnosis of the 12-lead ECG using a deep neural network.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Automatic diagnosis of the 12-lead ECG using a deep neural network.

The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has recently achieved striking success in a variety of task and there are great expectations on how it might improve clinical practice. Here we present a DNN model trained in a dataset with more than 2 million labeled exams analyzed by the Telehealth Network of Minas Gerais and collected under the scope of the CODE (Clinical Outcomes in Digital Electrocardiology) study. The DNN outperform cardiology resident medical doctors in recognizing 6 types of abnormalities in 12-lead ECG recordings, with F1 scores above 80% and specificity over 99%. These results indicate ECG analysis based on DNNs, previously studied in a single-lead setup, generalizes well to 12-lead exams, taking the technology closer to the standard clinical practice.

Tele-electrocardiography and bigdata: The CODE (Clinical Outcomes in Digital Electrocardiography) study.

Digital electrocardiographs are now widely available and a large number of digital electrocardiograms (ECGs) have been recorded and stored. The present study describes the development and clinical applications of a large database of such digital ECGs, namely the CODE (Clinical Outcomes in Digital Electrocardiology) study. ECGs obtained by the Telehealth Network of Minas Gerais, Brazil, from 2010 to 17, were organized in a structured database. A hierarchical free-text machine learning algorithm recognized specific ECG diagnoses from cardiologist reports. The Glasgow ECG Analysis Program provided Minnesota Codes and automatic diagnostic statements. The presence of a specific ECG abnormality was considered when both automatic and medical diagnosis were concordant; cases of discordance were decided using heuristisc rules and manual review. The ECG database was linked to the national mortality information system using probabilistic linkage methods. From 2,470,424 ECGs, 1,773,689 patients were identified. After excluding the ECGs with technical problems and patients <16 years-old, 1,558,415 patients were studied. High performance measures were obtained using an end-to-end deep neural network trained to detect 6 types of ECG abnormalities, with F1 scores >80% and specificity >99% in an independent test dataset. We also evaluated the risk of mortality associated with the presence of atrial fibrillation (AF), which showed that AF was a strong predictor of cardiovascular mortality and mortality for all causes, with increased risk in women. In conclusion, a large database that comprises all ECGs performed by a large telehealth network can be useful for further developments in the field of digital electrocardiography, clinical cardiology and cardiovascular epidemiology.

Normal limits of the electrocardiogram derived from a large database of Brazilian primary care patients.

BACKGROUND: Knowledge of the normal limits of the electrocardiogram (ECG) is mandatory for establishing which patients have abnormal ECGs. No studies have assessed the reference standards for a Latin American population. Our aim was to establish the normal ranges of the ECG for pediatric and adult Brazilian primary care patients. METHODS: This retrospective observational study assessed all the consecutive 12-lead digital electrocardiograms of primary care patients at least 1 year old in Minas Gerais state, Brazil, recorded between 2010 and 2015. ECGs were excluded if there were technical problems, selected abnormalities were present or patients with selected self-declared comorbidities or on drug therapy. Only the first ECG from patients with multiple ECGs was accepted. The University of Glasgow ECG analysis program was used to automatically interpret the ECGs. For each variable, the 1st, 2nd, 50th, 98th and 99th percentiles were determined and results were compared to selected studies. RESULTS: A total of 1,493,905 ECGs were recorded. 1,007,891 were excluded and 486.014 were analyzed. This large study provided normal values for heart rate, P, QRS and T frontal axis, P and QRS overall duration, PR and QT overall intervals and QTc corrected by Hodges, Bazett, Fridericia and Framingham formulae. Overall, the results were similar to those from other studies performed in different populations but there were differences in extreme ages and specific measurements. CONCLUSIONS: This study has provided reference values for Latinos of both sexes older than 1 year. Our results are comparable to studies performed in different populations.

Major Electrocardiographic Abnormalities According to the Minnesota Coding System Among Brazilian Adults (from the ELSA-Brasil Cohort Study).

The electrocardiogram is a simple and useful clinical tool; nevertheless, few studies have evaluated the prevalence of electrocardiographic abnormalities in the Latin American population. This study aims to evaluate the major electrocardiographic abnormalities according to the Minnesota coding system in Brazilian adults, stratified by gender, age, race, and cardiovascular risk factors. Data from 14,424 adults (45.8% men, age 35 to 74 years) were obtained at baseline of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), according to standardized protocol. The electrocardiogram were obtained with the Burdick Atria 6100 machine, stored on Pyramis System, automatically coded according to the Minnesota coding system by the Glasgow University software and then manually revised. Major abnormalities were more prevalent in men than women (11.3% and 7.9%, p <0.001). These differences were consistent through the different age groups, race, and number of cardiovascular risk factors. Electrocardiographic major abnormalities were more prevalent in black participants for both men (black: 15.1%, mixed: 10.4%, white: 11.1%, p = 0.001) and women (black: 10%, mixed: 7.6%, white: 7.2%, p = 0.004). In conclusion, in this large sample of Brazilian adults, the prevalence of major electrocardiographic abnormalities was higher among men, the elderly, black, and among people with more cardiovascular risk factors.