Prevalence and factors associated with impaired left ventricular global longitudinal strain in patients with Chagas disease: SaMi-Trop cohort study.

Cardiomyopathy is a major cause of death in Chagas disease and early detection of cardiac involvement is essential. Myocardial strain is a reliable technique for assessment of subtle left ventricular (LV) contractility alterations. This study assessed LV global longitudinal strain (GLS) in a large Chagas disease population living in remote areas. Between 2015 and 2016, Chagas disease patients were selected in the northern of the Minas Gerais state. All patients underwent T. cruzi antibodies tests and those who had positive tests were included. A resting 12-lead ECG was recorded and classified using the Minnesota Code criteria. Echocardiography was performed at public health primary care units and speckle-tracking strain was analyzed offline. LV dysfunction was defined as ejection fraction (LVEF < 50%) and reduced GLS was defined as < 16% (absolute value). A total of 1387 patients were included, mean age of 60.0 ± 12.5 years, 68% were women, and 14% had LV dysfunction. Among patients with normal LVEF, 59% had impaired LV GLS. Overall, patients with impaired GLS were older, had more comorbidities and ECG abnormalities than those with normal GLS. The independent factors associated with reduced GLS were ST-T abnormalities (OR 1.954; 95% CI 1.027-3.718), QRS duration (OR 1.009; 95% CI 1.002-1.016), LVEF (OR 0.947; 95% CI 0.923-0.972), and E/e' ratio (OR 1.059; 95% CI 1.009-1.112). In a cohort of Chagas disease from endemic areas, impaired LV GLS was detected in a significant proportion of patients, despite normal ECG and preserved LVEF. The main determinants of reduced LV GLS were ST-T abnormalities, QRS duration, LVEF and E/e' ratio, adjusting for demographical and clinical data.

A evolução do eletrocardiograma na doença de Chagas: usos no diagnóstico, prognóstico e no seguimento de idosos / The evolution of the electrocardiogram in Chagas disease: uses in the diagnosis, in the prognosis and in the follow-up of the elderly

Introdução: A história natural da doença de Chagas (DCh) na população idosa é desconhecida, e a progressão da doença nessa faixa etária é controversa. Quando ela evolui para a forma cardíaca, a insuficiência cardíaca é uma das principais causas de morte. Um algoritmo de inteligência artificial (IA) mostrou excelente acurácia para detectar disfunção sistólica do ventrículo esquerdo (DSVE) através da análise do eletrocardiograma (ECG), mas seu uso não foi avaliado na DCh. Objetivo 1: Investigar a evolução das alterações de ECG em idosos com DCh crônica comparados a idosos não infectados (NDCh) e como ela afeta a sobrevida da população da coorte de idosos de Bambuí em um seguimento de 14 anos. Métodos 1: Um ECG de 12 derivações de cada indivíduo foi obtido em 1997, 2002 e 2008, e as anormalidades foram classificadas pelo Código de Minnesota. A influência da doença de Chagas na evolução do ECG foi avaliada por meio de riscos semicompetitivos. Uma análise de sobrevivência foi realizada a partir de um Landmark de 5,5 anos; os indivíduos dos grupos DCh e NDCh foram comparados separadamente pelo desenvolvimento de anormalidades maiores no ECG entre 1997 e 2002. Objetivo 2: Avaliar a capacidade de um algoritmo de IA (IA-ECG) em reconhecer DSVE (fração de ejeção do ventrículo esquerdo determinada pelo Ecocardiograma ≤ 40%) em pacientes com DCh da coorte SaMi-Trop. Métodos 2: Trata-se de estudo transversal dos ECG de pacientes com DCh. Os ECG foram submetidos à análise de algoritmo de IA treinado para detectar DSVE; o ecocardiograma foi padrão-ouro. O modelo foi enriquecido com níveis plasmáticos de NT-proBNP, sexo masculino e QRS ≥ 120ms. Resultados 1: Entre os 1.462 participantes da Coorte de idosos de Bambuí, 557 tinham DCh (idade mediana: 68 anos para DCh e 67 anos para NDCh). A DCh aumenta o risco de desenvolver uma nova anormalidade no ECG quando comparada à NDCh [HR: 2,89 (IC 95% 2,28 ­ 3,67)]. Desenvolver uma nova anormalidade no ECG na DCh aumenta o risco de morte em comparação com aqueles que mantêm um ECG normal [HR: 1,93 (IC 95% 1,02 ­ 3,65)]. Resultados 2: Entre os 1.304 participantes do estudo SaMi-Trop, 7,1% dos indivíduos têm DSVE e 59,5% têm anormalidades maiores no ECG. O IA-ECG identificou DSVE com OR= 63,3 (95% CI 32,3-128,9), sensibilidade de 73%, especificidade de 83%, acurácia de 83% e um valor preditivo negativo de 97%; a AUC foi de 0,839. O modelo ajustado para o sexo masculino e QRS ≥ 120ms aumentou a AUC para 0,859; o ajustado para o sexo masculino e NT-proBNP elevado apresentou acurácia de 0,89 e AUC de 0,874. Conclusões: A DCh está associada a um maior risco de progressão para cardiomiopatia em idosos. A ocorrência de uma nova anormalidade no ECG aumenta o risco de morte. O AI- ECG de pacientes com DCh pode se tornar uma poderosa ferramenta para o reconhecimento da DSVE, contribuindo assim para o tratamento com medicamentos de baixo custo que podem melhorar seus sintomas e reduzir a mortalidade.

Introduction: The natural history of Chagas disease (ChD) in the elderly population is unknown, and it is controversial whether the disease continues to progress in old age. When it progresses to the cardiac form, the heart failure is one of the leading causes of death. An artificial intelligence (AI) algorithm has shown excellent accuracy for detecting left ventricular systolic dysfunction (LVSD) using the electrocardiogram (ECG), but it has not been evaluated in ChD. Objective 1: To investigate the evolution of ECG changes in elderly people with chronic ChD compared to non-infected elderly (NChD) and how this affects the survival of the population of the elderly cohort of Bambuí in a 14-year follow-up. Methods 1: A 12-lead ECG of each subject was obtained in 1997, 2002, and 2008, and abnormalities were classified by the Minnesota Code. The influence of ChD on the ECG evolution was evaluated through semi-competitive risks. A survival analysis was performed from a 5.5-year Landmark; individuals of the ChD and NChD groups were compared separately for the development of major ECG abnormalities between 1997 and 2002. Objective 2: To analyze the AI-ECG's ability to recognize LVSD in patients with ChD from the SaMi-Trop cohort, defined as left ventricular ejection fraction determined by Echocardiogram ≤ 40%. Methods 2: Cross-sectional study of ECG obtained from the cohort of patients with ChD named SaMi-Trop. The digital ECGs of the participants were submitted to the analysis of the trained machine to detect LVSD. The diagnostic performance of the AI- ECG to detect LVSD was evaluated, and the echocardiogram was the gold standard. The model was enriched with NT-proBNP plasma levels, male sex, and QRS ≥ 120ms. Results 1: Among the 1,462 participants in the Bambuí Elderly Cohort, 557 had CDh (median age: 68 years for ChD and 67 years for NChD). ChD increases the risk of developing a new ECG abnormality when compared to NChD [HR: 2.89 (95% CI 2.28 ­ 3.67)]. Developing a new ECG abnormality in ChD increases the risk of death compared to those who maintain a normal ECG [HR: 1.93 (95% CI 1.02 ­ 3.65)]. Results 2: Among the 1,304 participants in the SaMi-Trop study, 7.1% of subjects have LVSD and 59.5% have major ECG abnormalities. The AI algorithm identified LVSD with OR= 63.3 (95% CI 32.3-128.9), sensitivity of 73%, specificity of 83%, accuracy of 83% and a negative predictive value of 97%; the AUC was 0.839. The model adjusted for the male sex and QRS ≥ 120ms improved the AUC to 0.859. The model adjusted for the male sex and elevated NT-proBNP had a higher accuracy of 0.89 and an AUC of 0.874. Conclusions: ChD is associated with a higher risk of progression to cardiomyopathy in the elderly. The occurrence of a new abnormality on the ECG increases the risk of death. AI - ECG of patients with ChD can be turned into a powerful tool for the recognition of LVSD, thus, contributing to the treatment with low-cost drugs that can improve symptoms and reduce mortality.

Left ventricular systolic dysfunction predicted by artificial intelligence using the electrocardiogram in Chagas disease patients-The SaMi-Trop cohort.

BACKGROUND: Left ventricular systolic dysfunction (LVSD) in Chagas disease (ChD) is relatively common and its treatment using low-cost drugs can improve symptoms and reduce mortality. Recently, an artificial intelligence (AI)-enabled ECG algorithm showed excellent accuracy to detect LVSD in a general population, but its accuracy in ChD has not been tested. OBJECTIVE: To analyze the ability of AI to recognize LVSD in patients with ChD, defined as a left ventricular ejection fraction determined by the Echocardiogram ≤ 40%. METHODOLOGY/PRINCIPAL FINDINGS: This is a cross-sectional study of ECG obtained from a large cohort of patients with ChD named São Paulo-Minas Gerais Tropical Medicine Research Center (SaMi-Trop) Study. The digital ECGs of the participants were submitted to the analysis of the trained machine to detect LVSD. The diagnostic performance of the AI-enabled ECG to detect LVSD was tested using an echocardiogram as the gold standard to detect LVSD, defined as an ejection fraction <40%. The model was enriched with NT-proBNP plasma levels, male sex, and QRS ≥ 120ms. Among the 1,304 participants of this study, 67% were women, median age of 60; there were 93 (7.1%) individuals with LVSD. Most patients had major ECG abnormalities (59.5%). The AI algorithm identified LVSD among ChD patients with an odds ratio of 63.3 (95% CI 32.3-128.9), a sensitivity of 73%, a specificity of 83%, an overall accuracy of 83%, and a negative predictive value of 97%; the AUC was 0.839. The model adjusted for the male sex and QRS ≥ 120ms improved the AUC to 0.859. The model adjusted for the male sex and elevated NT-proBNP had a higher accuracy of 0.89 and an AUC of 0.874. CONCLUSION: The AI analysis of the ECG of Chagas disease patients can be transformed into a powerful tool for the recognition of LVSD.

Incidence and Predictors of Progression to Chagas Cardiomyopathy: Long-Term Follow-Up of Trypanosoma cruzi-Seropositive Individuals.

BACKGROUND: There are few contemporary cohorts of Trypanosoma cruzi-seropositive individuals, and the basic clinical epidemiology of Chagas disease is poorly understood. Herein, we report the incidence of cardiomyopathy and death associated with T. cruzi seropositivity. METHODS: Participants were selected in blood banks at 2 Brazilian centers. Cases were defined as T. cruzi-seropositive blood donors. T. cruzi-seronegative controls were matched for age, sex, and period of donation. Patients with established Chagas cardiomyopathy were recruited from a tertiary outpatient service. Participants underwent medical examination, blood collection, ECG, and echocardiogram at enrollment (2008-2010) and at follow-up (2018-2019). The primary outcomes were all-cause mortality and development of cardiomyopathy, defined as the presence of a left ventricular ejection fraction <50% or QRS complex duration ≥120 ms, or both. To handle loss to follow-up, a sensitivity analysis was performed using inverse probability weights for selection. RESULTS: We enrolled 499 T. cruzi-seropositive donors (age 48±10 years, 52% male), 488 T. cruzi-seronegative donors (age 49±10 years, 49% male), and 101 patients with established Chagas cardiomyopathy (age 48±8 years, 59% male). The mortality in patients with established cardiomyopathy was 80.9 deaths/1000 person-years (py) (54/101, 53%) and 15.1 deaths/1000 py (17/114, 15%) in T. cruzi-seropositive donors with cardiomyopathy at baseline. Among T. cruzi-seropositive donors without cardiomyopathy at baseline, mortality was 3.7 events/1000 py (15/385, 4%), which was no different from T. cruzi-seronegative donors with 3.6 deaths/1000 py (17/488, 3%). The incidence of cardiomyopathy in T. cruzi-seropositive donors was 13.8 (95% CI, 9.5-19.6) events/1000 py (32/262, 12%) compared with 4.6 (95% CI, 2.3-8.3) events/1000 py (11/277, 4%) in seronegative controls, with an absolute incidence difference associated with T. cruzi seropositivity of 9.2 (95% CI, 3.6-15.0) events/1000 py. T. cruzi antibody level at baseline was associated with development of cardiomyopathy (adjusted odds ratio, 1.4 [95% CI, 1.1-1.8]). CONCLUSIONS: We present a comprehensive description of the natural history of T. cruzi seropositivity in a contemporary patient population. The results highlight the central importance of anti-T. cruzi antibody titer as a marker of Chagas disease activity and risk of progression.

Association between typical electrocardiographic abnormalities and NT-proBNP elevation in a large cohort of patients with Chagas disease from endemic area.

Chagas cardiomyopathy is the most harmful complication of Chagas disease. The electrocardiogram is a well-studied exam and has been considered an important tool for detection and evaluation of Chagas cardiomyopathy since the first years of its description. Many of its abnormalities have been described as associated with a worse prognosis. Serum BNP levels were described as inversely related to the left ventricular ejection fraction and as an independent predictor of death. It was not reported how electrocardiographic alterations correlate to NT-proBNP and its analog. The present study aims to describe the baseline electrocardiograms of a large cohort of patients with Chagas disease from endemic area and to establish an association between the number of electrocardiogram alterations and high levels of NT-ProBNP in Chagas disease patients. This study selected 1959 Chagas disease patients in 21 municipalities within a limited region in the northern part of the State of Minas Gerais (Brazil), 1084 of them had Chagas cardiomyopathy. NT-proBNP levels were suggestive of heart failure in 11.7% of this population. One or more electrocardiographic alterations have an Odds Ratio of 9.12 (CI 95% 5.62-14.80) to have NT-proBNP elevation. Considering the association between the number of 1, 2, and 3 or more alterations in electrocardiogram and NT-proBNP elevation, the ORs were 7.11 (CI 95% 4.33-11.67); 16.04 (CI 95% 9.27-27.77) and 47.82 (CI 95% 17.98-127.20), respectively. The presence and the number of typical electrocardiographic alterations of Chagas disease are independently associated with the severity of the cardiomyopathy.

Electrocardiogram in Chagas disease.

Since the initial descriptions of Chagas cardiomyopathy (ChCM), the electrocardiography has played a key role in patient evaluations. The diagnostic criterion of chronic ChCM is the presence of characteristic electrocardiographic (ECG) abnormalities in seropositive individuals, regardless of the presence of symptoms. However, these ECG abnormalities are rarely specific to ChCM and, particularly among the elderly, can be caused by other simultaneous cardiomyopathies. ECG abnormalities can predict the occurrence of heart failure, stroke, and even death. Nevertheless, most prognostic studies have included Chagas disease (ChD) populations and, not exclusively, ChCM. Thus, more studies are required to evaluate the efficacy of ECG in predicting reliable prognoses in established chronic ChCM. This review exclusively discusses the role of the 12-lead ECG in the clinical evaluation of chronic ChD.

Electrocardiogram in Chagas disease

Abstract Since the initial descriptions of Chagas cardiomyopathy (ChCM), the electrocardiography has played a key role in patient evaluations. The diagnostic criterion of chronic ChCM is the presence of characteristic electrocardiographic (ECG) abnormalities in seropositive individuals, regardless of the presence of symptoms. However, these ECG abnormalities are rarely specific to ChCM and, particularly among the elderly, can be caused by other simultaneous cardiomyopathies. ECG abnormalities can predict the occurrence of heart failure, stroke, and even death. Nevertheless, most prognostic studies have included Chagas disease (ChD) populations and, not exclusively, ChCM. Thus, more studies are required to evaluate the efficacy of ECG in predicting reliable prognoses in established chronic ChCM. This review exclusively discusses the role of the 12-lead ECG in the clinical evaluation of chronic ChD.