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.

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, electrocardiogram, and echocardiogram at enrollment (2008 to 2010) and at follow-up (2018 to 2019). The primary outcomes were all-cause mortality and development of cardiomyopathy, defined as the presence of a left ventricular ejection fraction <50% and/or QRS complex duration ≥ 120 ms. 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/1000py (17/114, 15%) in T. cruzi -seropositives with cardiomyopathy at baseline. Among T. cruzi -seropositive donors without cardiomyopathy at baseline mortality was 3.7 events/1000py (15/385, 4%), which was no different from T. cruzi -seronegative donors with 3.6 deaths/1000py (17/488, 3%). The incidence of cardiomyopathy in T. cruzi -seropositive donors was 13.8 (95% CI 9.5-19.6) events/1000py (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/1000py. T. cruzi antibody level at baseline was associated with development of cardiomyopathy (adjusted OR of 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.

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 1,959 Chagas disease patients in 21 municipalities within a limited region in the northern part of the State of Minas Gerais (Brazil), 1,084 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.

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.

No abstract