On Merging Feature Engineering and Deep Learning for Diagnosis, Risk-Prediction and Age Estimation Based on the 12-Lead ECG

Objective: Machine learning techniques have been used extensively for 12-lead electrocardiogram (ECG) analysis. For physiological time series, deep learning (DL) superiority to feature engineering (FE) approaches based on domain knowledge is still an open question. Moreover, it remains unclear whether combining DL with FE may improve performance. Methods: We considered three tasks intending to address these research gaps: cardiac arrhythmia diagnosis (multiclass-multilabel classification), atrial fibrillation risk prediction (binary classification), and age estimation (regression). We used an overall dataset of 2.3M 12-lead ECG recordings to train the following models for each task: i) a random forest taking the FE as input was trained as a classical machine learning approach; ii) an end-to-end DL model; and iii) a merged model of FE+DL. Results: FE yielded comparable results to DL while necessitating significantly less data for the two classification tasks and it was outperformed by DL for the regression task. For all tasks, merging FE with DL did not improve performance over DL alone. Conclusion: We found that for traditional 12-lead ECG based diagnosis tasks DL did not yield a meaningful improvement over FE, while it improved significantly the nontraditional regression task. We also found that combining FE with DL did not improve over DL alone which suggests that the FE were redundant with the features learned by DL. Significance: Our findings provides important recommendations on what machine learning strategy and data regime to chose with respect to the task at hand for the development of new machine learning models based on the 12-lead ECG

Cost-Effectiveness of Routine Screening for Cardiac Toxicity in Patients Treated with Imatinib in Brazil

AbstractWe performed a cost-effectiveness study of different strategies of screening for cardiotoxicity in patients receiving imatinib, the first strategy based on yearly echocardiograms in all patients and the second strategy based on yearly B-type natriuretic peptide level measurement, reserving echocardiograms for patients with an abnormal test result. Results are presented in terms of additional cost per diagnosis as compared with not performing any screening. From the Brazilian private sector’s perspective, strategies 1 and 2 resulted in additional costs of US $30,951.53 and US$19,925.64 per diagnosis of cardiotoxicity, respectively. From the perspective of the Brazilian public health system, the same strategies generated additional costs of US $7,668.00 and US$20,232.87 per diagnosis, respectively. In our study, systematic screening for cardiotoxicity in patients using imatinib has a high cost per diagnosis. If screening is to be adopted, a strategy based on B-type natriuretic peptide level measurement, reserving echocardiography for patients with abnormal results, results in lower costs per diagnosis in the private sector. From the public health system’s perspective, costs per diagnosis will greatly depend on the reimbursement values adopted for B-type natriuretic peptide level measurement

Longitudinal study of patients with chronic Chagas cardiomyopathy in Brazil (SaMi-Trop project): a cohort profile.

PurposeWe have established a prospective cohort of 1959 patients with chronic Chagas cardiomyopathy to evaluate if a clinical prediction rule based on ECG, brain natriuretic peptide (BNP) levels, and other biomarkers can be useful in clinical practice. This paper outlines the study and baseline characteristics of the participants.ParticipantsThe study is being conducted in 21 municipalities of the northern part of Minas Gerais State in Brazil, and includes a follow-up of 2 years. The baseline evaluation included collection of sociodemographic information, social determinants of health, health-related behaviours, comorbidities, medicines in use, history of previous treatment for Chagas disease, functional class, quality of life, blood sample collection, and ECG. Patients were mostly female, aged 50-74 years, with low family income and educational level, with known Chagas disease for >10 years; 46% presented with functional class >II. Previous use of benznidazole was reported by 25.2% and permanent use of pacemaker by 6.2%. Almost half of the patients presented with high blood cholesterol and hypertension, and one-third of them had diabetes mellitus. N-terminal of the prohormone BNP (NT-ProBNP) level was >300 pg/mL in 30% of the sample.Findings to dateClinical and laboratory markers predictive of severe and progressive Chagas disease were identified as high NT-ProBNP levels, as well as symptoms of advanced heart failure. These results confirm the important residual morbidity of Chagas disease in the remote areas, thus supporting political decisions that should prioritise in addition to epidemiological surveillance the medical treatment of chronic Chagas cardiomyopathy in the coming years. The São Paulo-Minas Gerais Tropical Medicine Research Center (SaMi-Trop) represents a major challenge for focused research in neglected diseases, with knowledge that can be applied in primary healthcare.Future plansWe will continue following this patients' cohort to provide relevant information about the development and progression of Chagas disease in remotes areas, with social and economic inequalities.Trial registration numberNCT02646943; Pre-results

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

Lack of evidence of seronegative infection in an endemic area of Chagas disease

The diagnosis of Chagas disease is based on the detection of Trypanosoma cruzi (T. cruzi)-specific antibodies. Nonetheless, there is concern about the sensitivity of current serological assays due to reports of T. cruzi PCR positivity among seronegative individuals. The aim of this study was to evaluate if T. cruzi seronegative infections occur in endemic areas. We recruited 2,157 individuals that were identified as having Chagas disease in a public health system database of an endemic region in Brazil. All participants were interviewed and 2,091 had a sample collected for serological and PCR testing. From these, 149 (7.1%) had negative serological results. PCR was positive in 610 samples (31.4%) of the 1,942 seropositive samples but in none of the 149 samples from seronegative participants. True T. cruzi seronegative infections seem to be rare (95% CI 0-3.7) and should not be a concern for blood supply, which relies on antibody screening

Multidrug resistance 1 gene polymorphisms may determine Crohn's disease behavior in patients from Rio de Janeiro

OBJECTIVES: Conflicting data from studies on the potential role of multidrug resistance 1 gene polymorphisms in inflammatory bowel disease may result from the analysis of genetically and geographically distinct populations. Here, we investigated whether multidrug resistance 1 gene polymorphisms are associated with inflammatory bowel diseases in patients from Rio de Janeiro. METHODS: We analyzed 123 Crohn's disease patients and 83 ulcerative colitis patients to determine the presence of the multidrug resistance 1 gene polymorphisms C1236T, G2677T and C3435T. In particular, the genotype frequencies of Crohn's disease and ulcerative colitis patients were analyzed. Genotype-phenotype associations with major clinical characteristics were established, and estimated risks were calculated for the mutations. RESULTS: No significant difference was observed in the genotype frequencies of the multidrug resistance 1 G2677T/A and C3435T polymorphisms between Crohn's disease and ulcerative colitis patients. In contrast, the C1236T polymorphism was significantly more common in Crohn's disease than in ulcerative colitis (p = 0.047). A significant association was also found between the multidrug resistance 1 C3435T polymorphism and the stricturing form of Crohn's disease (OR: 4.13; p = 0.009), whereas no association was found with penetrating behavior (OR: 0.33; p = 0.094). In Crohn's disease, a positive association was also found between the C3435T polymorphism and corticosteroid resistance/refractoriness (OR: 4.14; p = 0.010). However, no significant association was found between multidrug resistance 1 gene polymorphisms and UC subphenotypic categories. CONCLUSION: The multidrug resistance 1 gene polymorphism C3435T is associated with the stricturing phenotype and an inappropriate response to therapy in Crohn's disease. This association with Crohn's disease may support additional pathogenic roles for the multidrug resistance 1 gene in regulating gut-microbiota interactions and in mediating fibrosis. Understanding the effects of several drugs associated with multidrug resistance 1 gene variants may aid in the selection of customized therapeutic regimens

Electrocardiographic findings and prognostic values in patients hospitalised with COVID-19 in the World Heart Federation Global Study

BACKGROUND COVID-19 affects the cardiovascular system and ECG abnormalities may be associated with worse prognosis. We evaluated the prognostic value of ECG abnormalities in individuals with COVID-19. METHODS Multicentre cohort study with adults hospitalised with COVID-19 from 40 hospitals across 23 countries. Patients were followed-up from admission until 30 days. ECG were obtained at each participating site and coded according to the Minnesota coding criteria. The primary outcome was defined as death from any cause. Secondary outcomes were admission to the intensive care unit (ICU) and major adverse cardiovascular events (MACE). Multiple logistic regression was used to evaluate the association of ECG abnormalities with the outcomes. RESULTS Among 5313 participants, 2451 had at least one ECG and were included in this analysis. The mean age (SD) was 58.0 (16.1) years, 60.7% were male and 61.1% from lower-income to middle-income countries. The prevalence of major ECG abnormalities was 21.3% (n=521), 447 (18.2%) patients died, 196 (8.0%) had MACE and 1115 (45.5%) were admitted to an ICU. After adjustment, the presence of any major ECG abnormality was associated with a higher risk of death (OR 1.39; 95% CI 1.09 to 1.78) and cardiovascular events (OR 1.81; 95% CI 1.30 to 2.51). Sinus tachycardia (>120 bpm) with an increased risk of death (OR 3.86; 95% CI 1.97 to 7.48), MACE (OR 2.68; 95% CI 1.10 to 5.85) and ICU admission OR 1.99; 95% CI 1.03 to 4.00). Atrial fibrillation, bundle branch block, ischaemic abnormalities and prolonged QT interval did not relate to the outcomes. CONCLUSION Major ECG abnormalities and a heart rate >120 bpm were prognostic markers in adults hospitalised with COVID-19

Cartografia e diplomacia: usos geopolíticos da informação toponímica (1750-1850)

O artigo explora dimensões geopolíticas da toponímia, registradas em documentos cartográficos, desde as reformas empreendidas pelo consulado pombalino em meados do século XVIII, até às primeiras décadas do século XIX, em meio ao processo de afirmação do Estado imperial pós-colonial.This paper explores the geopolitical dimensions of toponymy as registered in cartographic documents dating from the reforms pushed through by the consulate of Marquis of Pombal in the mid 18th century to the early decades of the 19th century, as the post-colonial imperial State established itself