Atrial fibrillation in patients with inherited cardiomyopathies

To describe the effect of atrial fibrillation on long-term morbidity and mortality. The Renfrew/Paisley Study surveyed 7052 men and 8354 women aged 45-64 years between 1972 and 1976. All hospitalizations and deaths occurring during the subsequent 20 years were analyzed by the presence or absence of atrial fibrillation at baseline. Lone atrial fibrillation was defined in the absence of other cardiovascular signs or symptoms. Cox proportional hazards models were used to adjust for age and cardiovascular conditions. After 20 years, 42 (89%) of the 47 women with atrial fibrillation had a cardiovascular event (death or hospitalization), compared with 2276 (27%) of the 8307 women without this arrhythmia. Among men, 35 (66%) of 53 with atrial fibrillation had an event, compared with 3151 (45%) of 6999 without atrial fibrillation. In women, atrial fibrillation was an independent predictor of cardiovascular events (rate ratio [RR] = 3.0; 95% confidence interval [CI]: 2.1-4.2), fatal or nonfatal strokes (RR = 3.2; 95% CI: 1.0-5.0), and heart failure (RR = 3.4; 95% CI: 1.9-6.2). The rate ratios among men were 1.8 (95% CI: 1.3-2.5) for cardiovascular events, 2.5 (95% CI: 1.3-4.8) for strokes, and 3.4 (95% CI: 1.7-6.8) for heart failure. Atrial fibrillation was an independent predictor of all-cause mortality in women (RR = 2.2; 95% CI: 1.5-3.2) and men (RR = 1.5; 95% CI: 1.2-2.2). However, lone atrial fibrillation (which occurred in 15 subjects) was not associated with a statistically significant increase in either cardiovascular events (RR = 1.5; 95% CI: 0.6-3.6) or mortality (RR = 1.8; 95% CI: 0.9-3.8). Atrial fibrillation is associated with an increased long-term risk of stroke, heart failure, and all-cause mortality, especially in women.

Estimates and projections of diagnosed incidence and prevalence of atrial fibrillation (AF) in the United States have been highly inconsistent across published studies. Although it is generally acknowledged that AF incidence and prevalence are increasing due to growing numbers of older people in the U.S. population, estimates of the rate of expected growth have varied widely. Reasons for these variations include differences in study design, covered time period, birth cohort, and temporal effects, as well as improvements in AF diagnosis due to increased use of diagnostic tools and health care awareness. The objective of this study was to estimate and project the incidence and prevalence of diagnosed AF in the United States out to 2030. A large health insurance claims database for the years 2001 to 2008, representing a geographically diverse 5% of the U.S. population, was used in this study. The trend and growth rate in AF incidence and prevalence was projected by a dynamic age-period cohort simulation progression model that included all diagnosed AF cases in future prevalence projections regardless of follow-up treatment, as well as those cases expected to be chronic in nature. Results from the model showed that AF incidence will double, from 1.2 million cases in 2010 to 2.6 million cases in 2030. Given this increase in incidence, AF prevalence is projected to increase from 5.2 million in 2010 to 12.1 million cases in 2030. The effect of uncertainty in model parameters was explored in deterministic and probabilistic sensitivity analyses. Variability in future trends in AF incidence and recurrence rates has the greatest impact on the projected estimates of chronic AF prevalence. It can be concluded that both incidence and prevalence of AF are likely to rise from 2010 to 2030, but there exists a wide range of uncertainty around the magnitude of future trends.

Hypertrophic cardiomyopathy is an autosomal-dominant disorder in which 10 genes and numerous mutations have been reported. The aim of the present study was to perform a systematic screening of these genes in a large population, to evaluate the distribution of the disease genes, and to determine the best molecular strategy in clinical practice. The entire coding sequences of 9 genes (MYH7, MYBPC3, TNNI3, TNNT2, MYL2, MYL3, TPM1, ACTC, andTNNC1) were analyzed in 197 unrelated index cases with familial or sporadic hypertrophic cardiomyopathy. Disease-causing mutations were identified in 124 index patients ( approximately 63%), and 97 different mutations, including 60 novel ones, were identified. The cardiac myosin-binding protein C (MYBPC3) and beta-myosin heavy chain (MYH7) genes accounted for 82% of families with identified mutations (42% and 40%, respectively). Distribution of the genes varied according to the prognosis (P=0.036). Moreover, a mutation was found in 15 of 25 index cases with "sporadic" hypertrophic cardiomyopathy (60%). Finally, 6 families had patients with more than one mutation, and phenotype analyses suggested a gene dose effect in these compound-heterozygous, double-heterozygous, or homozygous patients. These results might have implications for genetic diagnosis strategy and, subsequently, for genetic counseling. First, on the basis of this experience, the screening of already known mutations is not helpful. The analysis should start by testing MYBPC3 and MYH7 and then focus on TNNI3, TNNT2, and MYL2. Second, in particularly severe phenotypes, several mutations should be searched. Finally, sporadic cases can be successfully screened.