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BACKGROUND: Hypertension is a highly prevalent cardiovascular disease risk factor that may be related to inflammation. Whether adverse levels of specific inflammatory cytokines relate to hypertension is unknown. The present study sought to determine whether higher levels of IL (interleukin)-1β, IL-6, TNF (tumor necrosis factor)-α, IFN (interferon)-γ, IL-17A, and CRP (C-reactive protein) are associated with a greater risk of incident hypertension. METHODS: The REGARDS study (Reasons for Geographic and Racial Difference in Stroke) is a prospective cohort study that recruited 30 239 community-dwelling Black and White adults from the contiguous United States in 2003 to 2007 (visit 1), with follow-up 9 years later in 2013 to 2016 (visit 2). We included participants without prevalent hypertension who attended follow-up 9 years later and had available laboratory measures and covariates of interest. Poisson regression estimated the risk ratio of incident hypertension by level of inflammatory biomarkers. RESULTS: Among 1866 included participants (mean [SD] aged of 62 [8] years, 25% Black participants, 55% women), 36% developed hypertension. In fully adjusted models comparing the third to first tertile of each biomarker, there was a greater risk of incident hypertension for higher IL-1β among White (1.24 [95% CI, 1.01–1.53]) but not Black participants (1.01 [95% CI, 0.83–1.23]) and higher TNF-α (1.20 [95% CI, 1.02–1.41]) and IFN-γ (1.22 [95% CI, 1.04–1.42]) among all participants. There was no increased risk with IL-6, IL-17A, or CRP. CONCLUSIONS: Higher levels of IL-1β, TNF-α, and IFN-γ, representing distinct inflammatory pathways, are elevated in advance of hypertension development. Whether modifying these cytokines will reduce incident hypertension is unknown. [ABSTRACT FROM AUTHOR]

BACKGROUND: Heart failure (HF) affects >6 million US adults, with recent increases in HF hospitalizations. We aimed to investigate the association between neighborhood disadvantage and incident HF events and potential differences by diabetes status. METHODS: We included 23 645 participants from the REGARDS study (Reasons for Geographic and Racial Differences in Stroke), a prospective cohort of Black and White adults aged ≥45 years living in the continental United States (baseline 2005–2007). Neighborhood disadvantage was assessed using a Z score of 6 census tract variables (2000 US Census) and categorized as quartiles. Incident HF hospitalizations or HF-related deaths through 2017 were adjudicated. Multivariable-adjusted Cox regression was used to examine the association between neighborhood disadvantage and incident HF. Heterogeneity by diabetes was assessed using an interaction term. RESULTS: The mean age was 64.4 years, 39.5% were Black adults, 54.9% females, and 18.8% had diabetes. During a median follow-up of 10.7 years, there were 1125 incident HF events with an incidence rate of 3.3 (quartile 1), 4.7 (quartile 2), 5.2 (quartile 3), and 6.0 (quartile 4) per 1000 person-years. Compared to adults living in the most advantaged neighborhoods (quartile 1), those living in neighborhoods in quartiles 2, 3, and 4 (most disadvantaged) had 1.30 (95% CI, 1.06–1.60), 1.36 (95% CI, 1.11–1.66), and 1.45 (95% CI, 1.18–1.79) times greater hazard of incident HF even after accounting for known confounders. This association did not significantly differ by diabetes status (interaction P =0.59). For adults with diabetes, the adjusted incident HF hazards comparing those in quartile 4 versus quartile 1 was 1.34 (95% CI, 0.92–1.96), and it was 1.50 (95% CI, 1.16–1.94) for adults without diabetes. CONCLUSIONS: In this large contemporaneous prospective cohort, neighborhood disadvantage was associated with an increased risk of incident HF events. This increase in HF risk did not differ by diabetes status. Addressing social, economic, and structural factors at the neighborhood level may impact HF prevention. [ABSTRACT FROM AUTHOR]

Achieving optimal cardiovascular health in rural populations can be challenging for several reasons including decreased access to care with limited availability of imaging modalities, specialist physicians, and other important health care team members. Therefore, innovative solutions are needed to optimize health care and address cardiovascular health disparities in rural areas. Mobile examination units can bring imaging technology to underserved or remote communities with limited access to health care services. Mobile examination units can be equipped with a wide array of assessment tools and multiple imaging modalities such as computed tomography scanning and echocardiography. The detailed structural assessment of cardiovascular and lung pathology, as well as the detection of extracardiac pathology afforded by computed tomography imaging combined with the functional and hemodynamic assessments acquired by echocardiography, yield deep phenotyping of heart and lung disease for populations historically underrepresented in epidemiological studies. Moreover, by bringing the mobile examination unit to local communities, innovative approaches are now possible including engagement with local professionals to perform these imaging assessments, thereby augmenting local expertise and experience. However, several challenges exist before mobile examination unit–based examinations can be effectively integrated into the rural health care setting including standardizing acquisition protocols, maintaining consistent image quality, and addressing ethical and privacy considerations. Herein, we discuss the potential importance of cardiac multimodality imaging to improve cardiovascular health in rural regions, outline the emerging experience in this field, highlight important current challenges, and offer solutions based on our experience in the RURAL (Risk Underlying Rural Areas Longitudinal) cohort study. [ABSTRACT FROM AUTHOR]

Background--PCSK9 loss-of-function (LOF) variants allow for the examination of the effects of lifetime reduced lowdensity lipoprotein cholesterol (LDL-C) on cardiovascular events. We examined the association of PCSK9 LOF variants with LDL-C and incident coronary heart disease and stroke through a meta-analysis of data from 8 observational cohorts and 1 randomized trial of statin therapy. Methods and Results--These 9 studies together included 17 459 blacks with 403 (2.3%) having at least 1 Y142X or C679X variant and 31 306 whites with 955 (3.1%) having at least 1 R46L variant. Unadjusted odds ratios for associations between PCSK9 LOF variants and incident coronary heart disease (851 events in blacks and 2662 events in whites) and stroke (523 events in blacks and 1660 events in whites) were calculated using pooled Mantel-Haenszel estimates with continuity correction factors. Pooling results across studies using fixed-effects inverse-variance-weighted models, PCSK9 LOF variants were associated with 35 mg/dL (95% confidence interval [CI], 32-39) lower LDL-C in blacks and 13 mg/dL (95% CI, 11-16) lower LDL-C in whites. PCSK9 LOF variants were associated with a pooled odds ratio for coronary heart disease of 0.51 (95% CI, 0.28-0.92) in blacks and 0.82 (95% CI, 0.63-1.06) in whites. PCSK9 LOF variants were not associated with incident stroke (odds ratio, 0.84; 95% CI, 0.48-1.47 in blacks and odds ratio, 1.06; 95% CI, 0.80-1.41 in whites). Conclusions--PCSK9 LOF variants were associated with lower LDL-C and coronary heart disease incidence. PCSK9 LOF variants were not associated with stroke risk. [ABSTRACT FROM AUTHOR]

Background: The accuracy of stroke diagnosis in administrative claims for a contemporary population of Medicare enrollees has not been studied. We assessed the validity of diagnostic coding algorithms for identifying stroke in the Medicare population by linking data from the REasons for Geographic And Racial Differences in Stroke (REGARDS) Study to Medicare claims.Methods and Results: The REGARDS Study enrolled 30 239 participants ≥45 years in the United States between 2003 and 2007. Stroke experts adjudicated suspected strokes, using retrieved medical records. We linked data for participants enrolled in fee-for-service Medicare to claims files from 2003 through 2009. Using adjudicated strokes as the gold standard, we calculated accuracy measures for algorithms to identify incident and recurrent strokes. We linked data for 15 089 participants, among whom 422 participants had adjudicated strokes during follow-up. An algorithm using primary discharge diagnosis codes for acute ischemic or hemorrhagic stroke (International Classification of Diseases, Ninth Revision, Clinical Modification codes: 430, 431, 433.x1, 434.x1, 436) had a positive predictive value of 92.6% (95% confidence interval, 88.8%-96.4%), a specificity of 99.8% (99.6%-99.9%), and a sensitivity of 59.5% (53.8%-65.1%). An algorithm using only acute ischemic stroke codes (433.x1, 434.x1, 436) had a positive predictive value of 91.1% (95% confidence interval, 86.6%-95.5%), a specificity of 99.8% (99.7%-99.9%), and a sensitivity of 58.6% (52.4%-64.7%).Conclusions: Claims-based algorithms to identify stroke in a contemporary Medicare cohort had high positive predictive value and specificity, supporting their use as outcomes for etiologic and comparative effectiveness studies in similar populations. These inpatient algorithms are unsuitable for estimating stroke incidence because of low sensitivity. [ABSTRACT FROM AUTHOR]