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Medline ® Abstract for Reference 12

of 'Chagas heart disease: Treatment and prognosis'

Electrocardiographic abnormalities in elderly Chagas disease patients: 10-year follow-up of the Bambui Cohort Study of Aging.
Ribeiro AL, Marcolino MS, Prineas RJ, Lima-Costa MF
J Am Heart Assoc. 2014;3(1):e000632. Epub 2014 Feb 7.
BACKGROUND: Electrocardiography has been considered an important tool in the management of Chagas disease (ChD) patients, although its value in elderly infected patients is unknown. This study was designed to investigate the prevalence and prognostic value of electrocardiographic abnormalities in Trypanosoma cruzi infected and noninfected older adults.
METHODS AND RESULTS: We studied 1462 participants in BambuíCity, Brazil, with electrocardiogram (ECG) records classified by the Minnesota Code. Follow-up time was 10 years; the endpoint was mortality. Adjustment for potential confounding variables included age, gender, conventional risk factors, and B-type natriuretic peptide (BNP). The mean age was 69 years (60.9% women). The prevalence of ChD was 38.1% (n=557). ECG abnormalities were more frequent in ChD patients (87.6% versus 77.7%, P<0.001). Right bundle branch block (RBBB) with left anterior hemiblock (LAH) was strongly related to ChD (OR: 11.99 [5.60 to 25.69]). During the mean follow-up time of 8.7 years, 556 participants died (253 with ChD), and only 89 were lost to follow-up. ECG variables of independent prognostic value for death in ChD included absence of sinus rhythm, frequent ventricular and supraventricular premature beats, atrial fibrillation, RBBB, old and possible old myocardial infarction, and left ventricular hypertrophy. The presence of any major ECG abnormalities doubled the risk of death in ChD patients (HR: 2.18 [1.35 to 3.53]), but it also increased the risk in non-ChD subjects (HR: 1.50 [1.07 to 2.10]); the risk of death increased with the number of major abnormalities in the same patient.
CONCLUSION: ECG abnormalities are more common among elderly Chagas disease patients and strongly predict adverse outcomes.
Department of Internal Medicine, Medical School, Universidade Federal de Minas Gerais, Brazil.