Antonio Luiz Pinho Ribeiro

• MD, PhD
• Head of Department at Federal University of Minas Gerais

Background Individuals in the indeterminate phase of Chagas disease are considered to have mortality rates similar to those of the overall population. This study compares mortality rates among blood donors seropositive for Chagas disease and negative controls in the city of São Paulo, Brazil. Methodology/principal findings This is a retrospective...

The electrocardiogram (ECG) 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 sex, ag...

Background Microvascular dysfunction is a marker of early vascular disease that predicts cardiovascular events. Whether metabolically healthy obese individuals have impaired microvascular function remains unclear. The aim of this study was to evaluate the relation of obesity phenotypes stratified by metabolic status to microvascular function. Meth...

In patients with cardiovascular diseases, comprehensive risk factor control and lifestyle modification reduce the risk of recurrent events and the need for revascularisation procedures, and improve survival and quality of life.1 Despite this convincing evidence, in the real world, there are several barriers that hamper the application of such measu...

Brazil is a large country, with an evolving economy, but marked social inequalities. The population is formed by an admixture of native Brazilians, Europeans, and Africans; is predominantly urban; and faces rapid aging. Time trends related to health behaviors show a substantial reduction in smoking rates, but a rising prevalence of overweight and o...

Background and Aims AI-enhanced 12-lead ECG can detect a range of structural heart diseases (SHDs) but has a limited role in community-based screening. We developed and externally validated a noise-resilient single-lead AI-ECG algorithm that can detect SHD and predict the risk of their development using wearable/portable devices. Methods Using 266...

Background Telemedicine interventions (TMIs) for heart failure (HF) can reduce hospitalizations and deaths. It is unclear if low literacy and limited access to technology in low‐ and middle‐income countries affect these benefits. We evaluated whether TMIs added to usual care could reduce HF‐related rehospitalizations in patients discharged from hos...

Background Heart failure (HF) has a major impact on public health. HF staging helps capture preclinical disease and its progression to advanced stages. There are scarce data on HF staging from longitudinal studies in Latin America. This study aimed to determine the prevalence and mortality of HF stages in a Brazilian adult cohort of participants 60...

Graphical Abstract

Resumo Fundamento A fibrilação atrial (FA) é uma arritmia que causa sintomas significativos e aumenta o risco de complicações. Objetivos Avaliar a associação de parâmetros clínicos, eletrocardiográficos e ecocardiográficos com fibrilação ou flutter atrial (FFA) prevalente e avaliar o perfil de risco para FFA incidente utilizando os escores de pre...

Background and Aims Current heart failure (HF) risk stratification strategies require comprehensive clinical evaluation. In this study, artificial intelligence (AI) applied to electrocardiogram (ECG) images was examined as a strategy to predict HF risk. Methods Across multinational cohorts in the Yale New Haven Health System (YNHHS), UK Biobank (U...

Background/Objectives: Lowering low-density lipoprotein cholesterol (LDL-C) to <70 mg/dL is recommended for most patients with diabetes. However, clinical trials investigating subjects with diabetes who are not at high cardiovascular risk are inconclusive regarding the all-cause mortality benefit of the current target, and real-world studies sugges...

Background In our previous study of blood donors in the Argentinian Chaco Province, we documented bimodal distributions of anti-Trypanosoma cruzi antibody (Ab) levels, suggesting potential self-cure in donors with low-reactive samples. This study aimed to correlate “high” and “low” Ab level groups, defined by a mathematical model, with parasitemia...

Cardiac trabeculae form a network of muscular strands that line the inner surfaces of the heart. Their development depends on multiscale morphogenetic processes and, while highly conserved across vertebrate evolution, their role in the pathophysiology of the mature heart is not fully understood. Here we report variant associations across the allele...

Background Most artificial intelligence-enhanced ECG (AI-ECG) models used to predict adverse events including death require that the ECGs be stored digitally. However, the majority of clinical facilities worldwide store ECGs as images. Methods 1,163,401 ECGs (189,539 patients) from a secondary care dataset were available as both natively digital t...

BACKGROUND Subtle, prognostically important ECG features may not be apparent to physicians. In the course of supervised machine learning, thousands of ECG features are identified. These are not limited to conventional ECG parameters and morphology. We aimed to investigate whether neural network–derived ECG features could be used to predict future c...

Background: Portable devices capable of recording single-lead electrocardiograms (ECGs) can enable large-scale community-based cardiovascular risk assessment. We developed a noise-adapted ensemble deep learning algorithm for lead I ECGs as the sole input and predicted the risk of major adverse cardiovascular events (MACE) and development of new-ons...

Background: Despite the availability of effective pharmacological and procedural interventions, risk stratification strategies for structural heart disorders (SHDs) remain elusive. We developed an ensemble deep learning model for ECG images that predicts the development of future SHD and the risk of major adverse cardiovascular events (MACE). Metho...

Background: Screening for structural heart disorders (SHDs) requires cardiac imaging, which has limited accessibility and requires clinical expertise. We report the multinational validation of PRESENT-SHD, an artificial intelligence-based approach for detecting multiple SHDs from a single image of a 12-lead electrocardiogram (ECG) across clinical s...

Background Atrial fibrillation (AF) is an arrhythmia that can lead to limiting symptoms and increases the risk of stroke and heart failure (HF). Purpose To evaluate the association of clinical, electrocardiographic, and echocardiographic parameters with prevalent AF or flutter (AFF), and the risk profile for future AFF according to Charge-AF and E...

Aims Heart failure (HF) has a major impact on public health, affecting up to 2% of adult population. HF staging is helpful in capturing pre-clinical disease and its progression to advanced stages. We aimed to determine the prevalence and mortality of HF stages in the participants of a Brazilian adult cohort. Methods The ELSA-Brasil cohort comprise...

Background and Aims: AI-enhanced 12-lead ECG can detect a range of structural heart diseases (SHDs) but has a limited role in community-based screening. We developed and externally validated a noise-resilient single-lead AI-ECG algorithm that can detect SHD and predict the risk of their development using wearable/portable devices. Methods: Using 26...

Background: Identifying structural heart diseases (SHDs) early can change the course of the disease, but their diagnosis requires cardiac imaging, which is limited in accessibility. Objective: To leverage 12-lead ECG images for automated detection and prediction of multiple SHDs using a novel deep learning model. Methods: We developed a series of c...

Introduction: The expansion of telehealth during the COVID-19 pandemic may widen digital divides. It is essential to better understand the use of telehealth by the elderly population for the development of equitable telehealth tools. Objectives: This study aimed to describe the socioeconomic, clinical, and functional characteristics of elderly pati...

Trypanosomiases are diseases caused by various species of protozoan parasite in the genus Trypanosoma, each presenting with distinct clinical manifestations and prognoses. Infections can affect multiple organs, with Trypanosoma cruzi predominantly affecting the heart and digestive system, leading to American trypanosomiasis or Chagas disease, and T...

The electrocardiogram (ECG) can capture obesity-related cardiac changes. Artificial intelligence-enhanced ECG (AI-ECG) can identify subclinical disease. We trained an AI-ECG model to predict body mass index (BMI) from the ECG alone. Developed from 512,950 12-lead ECGs from the Beth Israel Deaconess Medical Center (BIDMC), a secondary care cohort, a...

Background: Heart failure (HF) contributes to a high burden of hospitalization, and its form of presentation is associated with disease prognosis. Objectives: To describe the association of hemodynamic profile of acute HF patients at hospital admission, based on congestion (wet/dry) and perfusion (cold/warm), with mortality, hospital length of stay...

Aims Despite notable population differences in high-income and low- and middle-income countries (LMICs), national guidelines in LMICs often recommend using US-based cardiovascular disease (CVD) risk scores for treatment decisions. We examined the performance of widely used international CVD risk scores within the largest Brazilian community-based c...

Background Hypertension underpins significant global morbidity and mortality. Hypertension-mediated organ damage is an early indicator of serious cardiovascular sequelae, with multinational guidelines advocating aggressive treatment where detected. Artificial intelligence-enabled electrocardiogram (AI-ECG) offers novel strategies to facilitate pers...

Importance Despite the availability of disease-modifying therapies, scalable strategies for heart failure (HF) risk stratification remain elusive. Portable devices capable of recording single-lead electrocardiograms (ECGs) can enable large-scale community-based risk assessment. Objective To evaluate an artificial intelligence (AI) algorithm to pre...

Background: Current risk stratification strategies for heart failure (HF) risk require either specific blood-based biomarkers or comprehensive clinical evaluation. In this study, we evaluated the use of artificial intelligence (AI) applied to images of electrocardiograms (ECGs) to predict HF risk. Methods: Across multinational longitudinal cohorts...

Aims Electrocardiogram (ECG) is widely considered the primary test for evaluating cardiovascular diseases. However, the use of artificial intelligence (AI) to advance these medical practices and learn new clinical insights from ECGs remains largely unexplored. We hypothesize that AI models with a specific design can provide fine-grained interpretat...

Introduction: Handheld echocardiography (echo) is the tool of choice for rheumatic heart disease (RHD) screening. We aimed to assess the agreement between screening and standard echo for latent RHD diagnosis in schoolchildren from an endemic setting. Methods: Over 14 months, 3 nonphysicians used handheld machines and the 2012 WHF Criteria to determ...

Introduction Despite advancements in implantable cardioverter‐defibrillator (ICD) technology, sudden cardiac death (SCD) remains a persistent public health concern. Chagas disease (ChD), prevalent in Brazil, is associated with increased ventricular tachycardia (VT) and ventricular fibrillation (VF) events and SCD compared to other cardiomyopathies....

Parasitemia and inflammatory markers are cross-sectionally associated with chronic Chagas cardiomyopathy (CCC) among patients with Trypanosoma cruzi. However, the prospective association of the parasite load and host immune response-related characteristics with CCC (that is, progressors) among T. cruzi seropositive individuals has only been partial...

The aims of this study were to estimate the prevalence of gastrointestinal manifestations among individuals with positive serology for Chagas disease (ChD) and to describe the clinical gastrointestinal manifestations of the disease. A systematic review with meta-analysis was conducted based on the criteria and recommendations of the Preferred Repor...

Introduction: Telemedicine interventions (TMI) for heart failure (HF) can reduce hospitalizations and deaths. It is unknown if lower literacy and access to technology in low- and middle-income countries could hamper these positive results. We evaluated if a TMI could reduce HF-related rehospitalizations in HF patients discharged from public hospita...

Introduction: Tele-cardiology tools are valuable strategies to improve risk stratification, especially in low-resourced settings. We aimed to evaluate the accuracy of tele-electrocardiography (ECG) in remote sites to predict abnormalities in screening echocardiography (echo) in primary care (PC). Methods: In 17 months, 6 healthcare workers at 16 PC...

Introduction: Chagas disease (CD) is a neglected disease caused by Trypanosoma cruzi ( T. cruzi ), and benznidazole (BZN) is the most prescribed trypanocidal drug in Brazil in function of its best tolerability profile. While treatment with this drug is effective in acute disease, there is no consensus on its effectiveness in adults with chronic inf...

Introduction: The COVID-19 pandemic led to a reduction in cardiovascular (CVD) hospital admissions in many countries. We aimed to assess the effect of the COVID-19 pandemic on CVD hospitalizations, management, and mortality in Brazil. Methods: Hospitalization data for the years 2020 and 2021 for Brazil and regions were analyzed using the Datasus ho...

Background: Handheld echocardiography (echo) is the tool of choice for Rheumatic Heart Disease (RHD) screening, based on the 2012 World Heart Federation (WHF) Criteria. We aimed to assess the agreement between screening and standard echo for diagnosis of latent RHD in schoolchildren from an endemic setting. Methods: Over 14 months, 3 non-physicians...

Background: Direct oral anticoagulants (DOACs) have progressively replaced vitamin K antagonists (VKAs). However, in certain conditions, especially antiphospholipid syndrome, mechanical heart valves and rheumatic mitral stenosis, VKAs remain the only drugs with established safety and efficacy. In low-income contexts, they are frequently the preferr...

Atherosclerosis burden can be evaluated in asymptomatic patients by measuring coronary artery calcification (CAC), whereas the global longitudinal strain (GLS) and diastolic function parameters (mitral E/e' ratio, septal e', and lateral e') are used to evaluate subclinical left ventricular (LV) dysfunction. We investigated whether subjects with CAC...

Background Deep neural network artificial intelligence (DNN-AI)-based Heart Age estimations have been presented and used to show that the difference between an ECG-estimated Heart Age and chronological age is associated with prognosis. An accurate ECG Heart Age, without DNNs, has been developed using explainable advanced ECG (A-ECG) methods. We aim...

Introduction: Even with the increased use of telehealth from the COVID-19 pandemic onward, there needs to be more knowledge about its usability for patients with non-communicable diseases from the point of view of the health professional, which is the main objective of this study. The secondary objectives will be to describe the user’s profile, dis...

Background Worldwide, it is estimated that over 6 million people are infected with Chagas disease (ChD). It is a neglected disease that can lead to severe heart conditions in its chronic phase. While early treatment can avoid complications, the early-stage detection rate is low. We explore the use of deep neural networks to detect ChD from electroc...

Background: Deep neural networks have been used to estimate age from ECGs, the electrocardiographic age (ECG-age), which predicts adverse outcomes. However, this prediction ability has been restricted to clinical settings or relatively short periods. We hypothesized that ECG-age is associated with death and cardiovascular outcomes in the long-stan...

Background Subtle, prognostically-meaningful ECG features may not be apparent to physicians. In the course of supervised machine learning ML training, many thousands of ECG features are identified. These are not limited to conventional ECG parameters and morphology. These novel neural network (NN)-derived ECG features may have clinical, phenotypic,...

The authors, collaborators and coordinators of this document are aware that, in this phase of intensified perception of CD as a neglected disease, it is mandatory to rescue the affected individuals from their miserable conditions and their deplorable medical-social implications. Thus, we should strive to minimize the stigma of CD, beginning by bann...

Background: People age at different rates. Biological age is a risk factor for many chronic diseases independent of chronological age. A good lifestyle is known to improve overall health, but its association with biological age is unclear. Methods: This study included participants from the UK Biobank who had undergone 12-lead resting electrocard...

Background: During the COVID-19 pandemic, telehealth was expanded without the opportunity to evaluate the adopted technology's usability extensively. Objective: To synthesize evidence on health professionals' perceptions regarding the usability of telehealth systems in the primary care of individuals with non-communicable diseases (NCDs) (hypert...

The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and...

Objective. Automatic detection of Electrocardiograms (ECG) quality is fundamental to minimize costs and risks related to delayed diagnosis due to low ECG quality. Most algorithms to assess ECG quality include non-intuitive parameters. Also, they were developed using data non-representative of a real-world scenario, in terms of pathological ECGs and...

Background: Statins are an effective strategy to reduce CVD risk, however, treatment goals are not achieved especially among Blacks and “Pardos” in Brazil. Hypothesis: Socioeconomic differences and lack of statin treatment for primary CVD prevention can explain part of the elevated mortality risk of Blacks and “Pardos”. Methods: Data from the ELSA-...

Aims To evaluate clinical and electrocardiographic outcomes of patients with COVID-19, comparing those using chloroquine compounds (chloroquine) to individuals without specific treatment. Methods Outpatients with suspected COVID-19 in Brazil who had at least one tele-electrocardiography (ECG) recorded in a telehealth system were enrolled in two ar...

Background: The Good Practices in Cardiology Program is an initiative created by the Brazilian Society of Cardiology (SBC) to improve the quality of care of cardiovascular disease patients in Brazilian public hospitals. Objectives: To characterize patients admitted to a tertiary public hospital with diagnosis of acute coronary syndrome (ACS) or...

The COVID-19 pandemic has profoundly influenced the effort to achieve global health equity. This has been particularly the case for HIV/AIDS, tuberculosis, and malaria control initiatives in low- and middle-income countries, with significant outcome setbacks seen for the first time in decades. Lost in the calls for compensatory funding increases fo...

Background. Worldwide it is estimated that more than 6 million people are infected with Chagas disease (ChD). It is considered one of the most important neglected diseases and, when it reaches its chronic phase, the infected person often develops serious heart conditions. While early treatment can avoid complications, the condition is often not det...

Objective: Over the past few years, deep learning (DL) has been used extensively in research for 12-lead electrocardiogram (ECG) analysis. However, it is unclear whether the explicit or implicit claims made on DL superiority to the more classical feature engineering (FE) approaches, based on domain knowledge, hold. In addition, it remains unclear w...

We aimed to evaluate the reasons for disagreement between screening echocardiography (echo), acquired by nonexperts, and standard echo in the Brazilian primary care (PC). Over 20 months, 22 PC workers were trained on simplified handheld (GE VSCAN) echo protocols. Screening groups, consisting of patients aged 17-20, 35-40 and 60-65 years, and patien...

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 admiss...

Introduction: Data addressing the economic aspects of telehealth initiatives are incipient. This study aimed to evaluate the labor costs for running a COVID-19 telehealth system and its potential incremental access to health care service. Methods: From July 2020 to July 2021, data from a Brazilian teleconsultation service were analyzed. Labor costs...

Introduction: The COVID-19 pandemic prompted policies that limited direct human interactions globally. Due to this, healthcare systems worldwide have witnessed unprecedented challenges in providing adequate and continuous healthcare for patients with Non-Communicable Diseases (NCDs), among them hypertension and diabetes. The pandemic promoted the e...

BACKGROUND Telehealth has been established as a strategy to provide health care for patients with hypertension and diabetes from the COVID-19 pandemic onward. However, little is known about its usability from a healthcare professional's perspective. OBJECTIVE To assess evidence on health professionals’ perceptions of the usability of telehealth sy...