Background Little is known about the incidence of and risk factors for sick sinus syndrome (SSS), a common indication for pacemaker implantation. Objectives To describe the epidemiology of SSS. Methods This analysis included 20,572 participants (mean baseline age 59 years, 43% male) in the Atherosclerosis Risk in Communities (ARIC) study and the Cardiovascular Health Study (CHS), who at baseline were free of prevalent atrial fibrillation and pacemaker therapy, had a heart rate of ≥50 bpm unless using beta blockers, and were identified as white or black race. Incident SSS cases were identified by hospital discharge ICD-9-CM code 427.81 and validated by medical record review. Results During an average 17 years of follow-up, 291 incident SSS cases were identified (unadjusted rate 0.8 per 1,000 person-years). Incidence increased with age (HR 1.73, 95% CI: 1.47–2.05 per 5-year increment), and blacks had a 41% lower risk of SSS than whites (HR: 0.59, 95% CI: 0.37–0.98). Incident SSS was associated with greater baseline body mass index, height, NT-proBNP, and cystatin C, with longer QRS interval, with lower heart rate, and with prevalent hypertension, right bundle branch block, and cardiovascular disease. We project that the annual number of new SSS cases in the United States will increase from 78,000 in 2012 to 172,000 in 2060. Conclusions Blacks have a lower risk of SSS than whites, and several cardiovascular risk factors were associated with incident SSS. With the aging of the population, the number of Americans with SSS will increase dramatically over the next 50 years.

Background and Aims Understanding contributions of lean and fat tissue to cardiovascular and non-cardiovascular mortality may help clarify areas of prevention in older adults. We aimed to define distributions of lean and fat tissue in older adults and their contributions to cause-specific mortality. Methods and Results A total of 1335 participants of the Cardiovascular Health Study (CHS) who underwent dual-energy x-ray absorptiometry (DEXA) scans were included. We used principal components analysis (PCA) to define two independent sources of variation in DEXA-derived body composition, corresponding to principal components composed of lean (“lean PC”) and fat (“fat PC”) tissue. We used Cox proportional hazards regression using these PCs to investigate the relationship between body composition with cardiovascular and non-cardiovascular mortality. Mean age was 76.2±4.8 years (56% women) with mean body mass index 27.1±4.4 kg/m2. A greater lean PC was associated with lower all-cause (HR=0.91, 95% CI 0.84-0.98, P=0.01) and cardiovascular mortality (HR=0.84, 95% CI 0.74-0.95, P=0.005). The lowest quartile of the fat PC (least adiposity) was associated with a greater hazard of all-cause mortality (HR = 1.24, 95% CI 1.04-1.48, P=0.02) relative to fat PCs between the 25th-75th percentile, but the highest quartile did not have a significantly greater hazard (P=0.70). Conclusion Greater lean tissue mass is associated with improved cardiovascular and overall mortality in the elderly. The lowest levels of fat tissue mass are linked with adverse prognosis, but the highest levels show no significant mortality protection. Prevention efforts in the elderly frail may be best targeted toward improvements in lean muscle mass.

Cardiovascular disease is the leading cause of death in patients with chronic kidney disease (CKD). We examined the cross-sectional association between novel risk factors and coronary artery calcium (CAC) measured by electron-beam computed tomography or multidetector computed tomography among 2,018 patients with CKD. Based on total Agatston scores, participants were classified as no (0), moderate (>0–100) or high (>100) CAC. After adjustment for age, sex, race, study sites, cigarette smoking, prior cardiovascular disease, hypertension, and diabetes, use of lipid-lowering drugs, body-mass index, waist circumference, and cystatin C, several novel risk factors were significantly associated with high CAC. For example, odds ratios (95% confidence interval) of high CAC associated with one standard deviation higher levels of risk factors were 1.20 (1.04, 1.38) for serum calcium, 1.21 (1.04, 1.41) for serum phosphate, 0.83 (0.71, 0.97) for log (total parathyroid hormone), 1.21 (1.03, 1.43) for log (HOMA-insulin resistance), and 1.23 (1.04, 1.45) for hemoglobin A1c. Additionally, the multivariable-adjusted odds ratio for one standard deviation higher level of cystatin C was 1.31 (1.14, 1.50). Serum high-sensitive C-reactive protein, interleukin-6, tumor necrosis factor-α, and homocysteine were not statistically significantly associated with high CAC. In conclusion, these data indicate that abnormal calcium and phosphate metabolism, insulin resistance, and declined kidney function were associated with the prevalence of high CAC independent of traditional risk factors in patients with CKD. Further studies are warranted to examine the causal effect of these risk factors on CAC in CKD patients.

Objective The associations of some risk factors with cardiovascular disease (CVD) are attenuated in older age; whereas others appear robust. The present study aimed to compare CVD risk factors across older age. Methods Participants (n=4,883) in the Cardiovascular Health Study free of prevalent CVD, were stratified into three age groups: 65–74, 75–84, 85+ years. Traditional risk factors included systolic blood pressure (BP), LDL-cholesterol, HDL-cholesterol, obesity, and diabetes. Novel risk factors included kidney function, C-reactive protein (CRP), and N-terminal pro-B-type natriuretic peptide (NT pro-BNP). Results There were 1,498 composite CVD events (stroke, myocardial infarction, and cardiovascular death) over 5 years. The associations of high systolic BP and diabetes appeared strongest, though both were attenuated with age (p-values for interaction = 0.01 and 0.002, respectively). The demographic-adjusted hazard ratios (HR) for elevated systolic BP were 1.79 (95% confidence interval: 1.49, 2.15), 1.59 (1.37, 1.85) and 1.10 (0.86, 1.41) in participants aged 65–74, 75–84, 85+, and for diabetes, 2.36 (1.89, 2.95), 1.55 (1.27, 1.89), 1.51 (1.10, 2.09). The novel risk factors had consistent associations with the outcome across the age spectrum; low kidney function: 1.69 (1.31, 2.19), 1.61 (1.36, 1.90), and 1.57 (1.16, 2.14) for 65–74, 75–84, and 85+ years, respectively; elevated CRP: 1.54 (1.28, 1.87), 1.33 (1.13, 1.55), and 1.51 (1.15, 1.97); elevated NT pro-BNP: 2.67 (1.96, 3.64), 2.71 (2.25, 3.27), and 2.18 (1.43, 3.45). Conclusions The associations of most traditional risk factors with CVD were minimal in the oldest old, whereas diabetes, eGFR, CRP, and NT pro-BNP were associated with CVD across older age.

Sarcopenia is the loss of muscle strength, mass, and function, which is often exacerbated by chronic comorbidities including cardiovascular diseases, chronic kidney disease, and cancer. Sarcopenia is associated with faster progression of cardiovascular diseases and higher risk of mortality, falls, and reduced quality of life, particularly among older adults. Although the pathophysiologic mechanisms are complex, the broad underlying cause of sarcopenia includes an imbalance between anabolic and catabolic muscle homeostasis with or without neuronal degeneration. The intrinsic molecular mechanisms of aging, chronic illness, malnutrition, and immobility are associated with the development of sarcopenia. Screening and testing for sarcopenia may be particularly important among those with chronic disease states. Early recognition of sarcopenia is important because it can provide an opportunity for interventions to reverse or delay the progression of muscle disorder, which may ultimately impact cardiovascular outcomes. Relying on body mass index is not useful for screening because many patients will have sarcopenic obesity, a particularly important phenotype among older cardiac patients. In this review, we aimed to: (1) provide a definition of sarcopenia within the context of muscle wasting disorders; (2) summarize the associations between sarcopenia and different cardiovascular diseases; (3) highlight an approach for a diagnostic evaluation; (4) discuss management strategies for sarcopenia; and (5) outline key gaps in knowledge with implications for the future of the field.