Discriminant analysis of the standard 12-lead ECG for diagnosing non-Q wave myocardial infarction

Intra-host Trypanosoma cruzi strain dynamics shape disease progression: the missing link in Chagas disease pathogenesis

Chronic Chagasic cardiomyopathy develops years after infection in 20-40% of patients, but disease progression is poorly understood. Here, we assessed Trypanosoma cruzi parasite dynamics and pathogenesis over a 2.5-year period in naturally infected rhesus macaques. Individuals with better control of parasitemia were infected with a greater diversity of parasite strains compared to those with increasing parasitemia over time. Also, the in vivo parasite multiplication rate decreased with increasing parasite diversity, suggesting competition among strains or a stronger immune response in multiple infections. Significant differences in electrocardiographic (ECG) profiles were observed in Chagasic macaques compared to uninfected controls, suggesting early conduction defects, and changes in ECG patterns over time were observed only in macaques with increasing parasitemia and lower parasite diversity. Disease progression was also associated with plasma fibronectin degradation, which may serve as a biomarker. These data provide a novel framework for the understanding of Chagas disease pathogenesis, with parasite diversity shaping disease progression.IMPORTANCEChagas disease progression remains poorly understood, and patients at increased risk of developing severe cardiac disease cannot be distinguished from those who may remain asymptomatic. Monitoring of Trypanosoma cruzi strain dynamics and pathogenesis over 2-3 years in naturally infected macaques shows that increasing parasite diversity in hosts is detrimental to parasite multiplication and Chagasic cardiomyopathy disease progression. This provides a novel framework for the understanding of Chagas disease pathogenesis.

Importance of accounting for the variability of electrocardiographic data among diagnostically similar patients with inferior wall healed myocardial infarction

The authors describe a method to account for patient-to-patient variability in electrocardiographic data. The method yielded criteria for healed inferior myocardial infarction with diagnostic performances better than those of traditional electrocardiographic parameters.

ECG myocardial infarct size: a gender-, age-, race-insensitive 12-segment multiple regression model. I: Retrospective learning set of 100 pathoanatomic infarcts and 229 normal control subjects

In this early study of ongoing work with multiple regression modeling for mapping myocardial infarct (MI) into 12 left ventricular (LV) segments, promising results have been presented using electrocardiographic (ECG) QRS variables that are gender, age, and race insensitive (GARI), the GARI-QRS 12-segment multiple regression model. These include Q, R, and S duration, expressed as percentage total QRS duration, and R/Q duration, R/Q amplitude, R/S duration, and R/S amplitude variables. For version I, building 12 regression models using 68 single and 32 multiple MIs, the GARI-QRS variables correlated with pathoanatomic MI in each of 12 segments with r values ranging from .67 to .88. In version II of the model, using all MIs and 229 normal subjects, r = .73-.91. Version II predictions of MI in 12 LV segments for each subject were used to calculate the predicted total percentage LV infarct, which correlated well with that found at autopsy. The r values found were .81 for all single MIs, .73 for multiple MIs, and .80 for all MIs taken together. With refinements of the input ECG variables to include (1) improvement in the GARI-QRS variables, (2) adding a significant number of subjects with hypertrophies and conduction defects with and without MI to an expanded learning set, and (3) applying the enhanced 12-LV-segment regression models to a similar test set, it is to be expected that these regression models can be improved even further in such a way as to be applicable to general clinical populations using routine computerized ECG analysis programs.