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OBJECTIVE: It has been shown that asthma is significantly associated with the risk of cardiovascular disease (CVD). Under this background, this study aimed to systematically classify and summarize the epidemiological evidence of a...
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OBJECTIVE: It has been shown that asthma is significantly associated with the risk of cardiovascular disease (CVD). Under this background, this study aimed to systematically classify and summarize the epidemiological evidence of asthma and the risk of 4 specific cardiovascular diseases (CVDs) and cardiovascular mortality (CVM). MATERIALS AND METHODS: PubMed and Embase databases were searched from inception to December 1st, 2021 in order to identify relevant studies. The random-model was used to assess the pooled results. All pooled results were expressed as risk ratios (RRs) and corresponding 95% confidence intervals (CIs). RESULTS: Finally, a total of 18 studies were included in the present meta-analysis. Compared with non-asthmatic group, patients with asthma had significantly increased risks of subsequent cardiovascular heart disease (CHD, RR 1.33; 1.19-1.50, I2=80.3%; p<0.001), and CVM (RR 1.35; 1.15-1.59, I2=0%; p<0.001). Similarly, the risks of heart failure (HF, RR 2.10; 1.98-2.22, I2=17.4%; p<0.001) and myocardial infraction (MI, RR 1.39; 1.16-1.66, I2=59.3%; p<0.001) were higher in the asthmatic population. However, the higher risk of atrial fibrillation (RR 1.70; 1.45-2.00, I2=0%; p<0.001) was observed only in the active asthmatic population. CONCLUSIONS: In general, asthma is associated with subsequent increased risks of CHD, MI, AF, HF, and CVM. In addition, among patients with asthma, females have a higher risk of CHD than males, while active asthmatic patients have a higher risk of CVM than non-active asthmatic patients.
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Previous research demonstrates an inverse association between age and cardiovascular disease (CVD) biomarkers with cognitive function; however, little is known about the combined associations of CVD risk factors and cognitive func...
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Previous research demonstrates an inverse association between age and cardiovascular disease (CVD) biomarkers with cognitive function; however, little is known about the combined associations of CVD risk factors and cognitive function with all-cause mortality in an older adult population, which was the purpose of this study. Data from the 1999-2002 NHANES were used (N = 2,097; 60+ yrs), with mortality follow-up through 2011. Evaluated individual biomarkers included mean arterial pressure (MAP), high-sensitivity C-reactive protein (CRP), HDL-C, total cholesterol (TC), A1C, and measured body mass index (BMI). Cognitive function was assessed using the Digit Symbol Substitution Test (DSST). Further, 4 groups were created based on CVD risk and cognitive function. Group 1: high cognitive function and low CVD risk; Group 2: high cognitive function and high CVD risk; Group 3: low cognitive function and low CVD risk; Group 4: low cognitive function and high CVD risk. An inverse relationship was observed where those with more CVD risk factors had a lower (worse) cognitive function score. Compared to those in Group 1, only those in Group 3 and 4 had an increase mortality risk. (C) 2016 Elsevier Inc. All rights reserved.
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This JAMA Patient Page summarizes the US Preventive Services Task Force’s recent recommendations on using statins for primary prevention of cardiovascular disease in adults.
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BackgroundNonlaboratory-based (non-LB) algorithms have been developed to facilitate absolute cardiovascular risk assessment in resource-constrained settings. The non-LB Framingham algorithm, which substitute BMI for lipids in labo...
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BackgroundNonlaboratory-based (non-LB) algorithms have been developed to facilitate absolute cardiovascular risk assessment in resource-constrained settings. The non-LB Framingham algorithm, which substitute BMI for lipids in laboratory-based Framingham, exhibits best performance among non-LB algorithms. However, its external validity has not been evaluated.AimTo examine the validity of non-LB Framingham algorithm in Atherosclerosis Risk in Communities dataset, and contrast performance with the laboratory-based Framingham algorithm.MethodsWe developed Cox regression models including non-LB and laboratory-based Framingham covariates in Atherosclerosis Risk in Communities dataset. Discrimination was assessed via C-statistic, calibration via goodness-of-fit, and marginal discrimination value of BMI vis-a-vis lipids vis-a-vis waist-hip ratio via net reclassification improvement (NRI). Both models were compared via area under receiver operating characteristic.ResultsAmong 11601 participants (mean age 54 years, 55% women, 23% black), non-LB vs. laboratory-based Framingham performed as follows: C-statistic 0.75 vs. 0.76 among women and 0.67 vs. 0.68 among men; goodness-of-fit 14.2 vs. 10.5 among women and 25.8 vs. 21.8 among men. Overall area under receiver operating characteristic was 0.706 vs. 0.710, respectively, with no racial differences in discrimination or calibration. BMI and total cholesterol had no impact on NRI. Incremental predictive value of HDL was comparable with waist-hip ratio (category-less NRI=0.34 vs. 0.31; categorical NRI7.5=0.06 vs. 0.05, P<0.01).ConclusionThese results demonstrate the validity and limitations of the non-LB Framingham algorithm in a biracial cohort. Substituting BMI with a central adiposity metric such as waist-hip ratio or waist circumference could make the algorithm better or at par with the laboratory-based Framingham algorithm.
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Aim Centenarians represent a biological model of successful aging because they escaped/postponed most invalidating age-related diseases, such as cardiovascular diseases. The aim of the present study was to clarify whether a favora...
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Aim Centenarians represent a biological model of successful aging because they escaped/postponed most invalidating age-related diseases, such as cardiovascular diseases. The aim of the present study was to clarify whether a favorable cardiovascular risk profile increases the survival chances in long-lived people. Methods A total of 355 community-dwelling nonagenarians and centenarians living in Southern Italy were recruited in the study. Patients were classified as at low and high cardiovascular risk on the basis of serum cholesterol, diabetes, hypertension and smoking status. The relationship between cardiovascular risk factors and 10-year mortality was investigated by Cox regression analysis. Splines-based hazard ratio curves were also estimated for total cholesterol, low-density lipoprotein cholesterol, and systolic and diastolic blood pressure. Results Low levels of selected cardiovascular risk factors usually associated with lower mortality in adults do not increase survival chances among oldest-old individuals. In particular, after adjusting for age, sex, and cognitive, functional and nutritional status, serum cholesterol >200 mg/dL increased the survival chances during the follow-up period (hazard ratio 0.742, 95% CI 0.572-0.963). Conclusions The present results showed that in nonagenarians and centenarians, the clinical and prognostic meaning associated with traditional cardiovascular risk factors is very different from younger populations. Consequently, considering the increase of this population segment, further studies are required to confirm these results and to translate them into clinical practice/primary care. Geriatr Gerontol Int 2019; 19: 165-170.
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Aim Centenarians represent a biological model of successful aging because they escaped/postponed most invalidating age-related diseases, such as cardiovascular diseases. The aim of the present study was to clarify whether a favora...
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Aim Centenarians represent a biological model of successful aging because they escaped/postponed most invalidating age-related diseases, such as cardiovascular diseases. The aim of the present study was to clarify whether a favorable cardiovascular risk profile increases the survival chances in long-lived people. Methods A total of 355 community-dwelling nonagenarians and centenarians living in Southern Italy were recruited in the study. Patients were classified as at low and high cardiovascular risk on the basis of serum cholesterol, diabetes, hypertension and smoking status. The relationship between cardiovascular risk factors and 10-year mortality was investigated by Cox regression analysis. Splines-based hazard ratio curves were also estimated for total cholesterol, low-density lipoprotein cholesterol, and systolic and diastolic blood pressure. Results Low levels of selected cardiovascular risk factors usually associated with lower mortality in adults do not increase survival chances among oldest-old individuals. In particular, after adjusting for age, sex, and cognitive, functional and nutritional status, serum cholesterol >200 mg/dL increased the survival chances during the follow-up period (hazard ratio 0.742, 95% CI 0.572-0.963). Conclusions The present results showed that in nonagenarians and centenarians, the clinical and prognostic meaning associated with traditional cardiovascular risk factors is very different from younger populations. Consequently, considering the increase of this population segment, further studies are required to confirm these results and to translate them into clinical practice/primary care. Geriatr Gerontol Int 2019; 19: 165-170.
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The primary objective of this study was to identify improvement in practice patterns in the clinical management of coronary heart disease (CHD) following the initiation of a cardiovascular disease management program. Retrospective...
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The primary objective of this study was to identify improvement in practice patterns in the clinical management of coronary heart disease (CHD) following the initiation of a cardiovascular disease management program. Retrospective and prospective administrative claims database analysis and Health Plan Employer Data and Information Set (HEDIS) quality indicators analysis were applied. The CHD management program included educating physicians and patients on the management of CHD. Outcomes included percent of CHD members obtaining annual lipid profiles; percent of CHD members with a physician follow up within 14 days of hospital discharge following an acute coronary event; percent of CHD members receiving annual flu vaccine; percent of CHD members with an annual visit to a primary care provider; and percent of CHD members filling a prescription for < greater-than-or-equal-to >1 HMG-CoA reductase inhibitor. Other outcomes included HEDIS quality indicators including < beta >-blocker treatment after heart attack and cholesterol management after acute cardiovascular event. Significant improvement was seen in 3 of the 7 outcome measures 2 years following initiation of the program. The percent of members receiving at least one lipid test during the 12-month measurement period significantly increased from 56% at baseline to 68%, at year 1 (P<.0001) and to 72% at year 2 (P<.0001). Members receiving < greater-than-or-equal-to >1 prescription for an HMG-CoA reductase inhibitor significantly increased from 49% at baseline to 55% at year 1 (P=.0009) and 61.5% at year 2 (P<.0001). The HEDIS measure of the percent of CHD members receiving cholesterol screening after an acute cardiac event significantly increased from 49% to 70% at year 1 using 1999 HEDIS measures (P=.0001). Evaluation of administrative claims database and HEDIS quality indicators at PARTNERS demonstrated that targeting providers and at risk CHD populations with a comprehensive disease management program significantly improved management of the CHD patient.
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The Sixth Joint Task Force of the European Society of Cardiology (ESC) and Other Societies on Cardiovascular Disease Prevention in Clinical Practice Guidelines have been published in 2016: greater emphasis has been placed on a pop...
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The Sixth Joint Task Force of the European Society of Cardiology (ESC) and Other Societies on Cardiovascular Disease Prevention in Clinical Practice Guidelines have been published in 2016: greater emphasis has been placed on a population-based approach, on disease-specific interventions and on female-specific conditions, younger individuals and ethnic minorities. The ESC guidelines underscore that a lifetime approach to cardiovascular risk is important as both risk and prevention are dynamic and continuous. The guidelines can assist healthcare professionals, patients, and are valuable for the healthcare system but implementation of secondary cardiovascular disease prevention is far from optimal. Although there is no single way to ensure the use of guidelines in practice, multifaceted interventions based on known barriers are most appropriate. Essential components for implementation are: (a) taking action; (b) strengthening capacity; (c) evaluating impact; (d) advancing policy; and (e) engaging in regional and global partnerships. The strategy depends on a balanced investment in all available intervention approaches, from policy and environmental changes designed to prevent risk factors to assurance of quality care for individuals with cardiovascular disease. Our greatest challenges represent our greatest opportunities.
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It is widely believed that the US health care system needs to transition from a culture of reactive treatment of disease to one of proactive prevention. As a tool for understanding the appropriate allocation of spending to prevent...
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It is widely believed that the US health care system needs to transition from a culture of reactive treatment of disease to one of proactive prevention. As a tool for understanding the appropriate allocation of spending to prevention versus treatment (including research into improved prevention and treatment), a simple Markov model is used to represent the flow of individuals among states of health, where the transition rates are governed by the magnitude of appropriately-lagged expenditures in each of these categories. The model estimates the discounted cost and discounted effectiveness (measured in quality adjusted life years or QALYs) associated with a given spending mix, and it allows computing the marginal cost-effectiveness associated with additional spending in a category. We apply the model to explore interactions of alternative investments in cardiovascular disease (CVD) and to identify an optimal spending mix. Under the assumptions of our model structure, we find that the marginal cost-effectiveness of prevention of CVD varies with changes in spending on treatment (and vice versa), and that the optimal mix of CVD spending (i. e., the spending mix that maximizes the overall QALYs achieved) would, indeed, shift spending from treatment to prevention.
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