37 research outputs found

    Pharmacological and non-pharmacological interventions to influence adipose tissue function

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    Obesity is associated with metabolic derangements such as insulin resistance, inflammation and hypercoagulobility which can all be understood as consequences of adipose tissue dysfunction. The potential role for adipose tissue derived cytokines and adipokines in the development of vascular disease and diabetes may produce a clinical need to influence adipose tissue function. Various pharmacological and non-pharmacological interventions affect plasma cytokine and adipokine levels. The effects of these interventions depend on weight loss per se, changes in fat distribution without weight loss and/or direct effects on adipose tissue inflammation

    Insulin resistance increases the occurrence of new cardiovascular events in patients with manifest arterial disease without known diabetes. The SMART study

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    <p>Abstract</p> <p>Background</p> <p>Insulin resistance is accompanied by a cluster of metabolic changes, often referred to as metabolic syndrome. Metabolic syndrome is associated with an increased cardiovascular risk in patients with manifest arterial disease. We investigated whether insulin resistance is associated with an increased risk for cardiovascular events in patients with manifest arterial disease without known diabetes and whether this can be explained by the components of the metabolic syndrome or by inflammation.</p> <p>Methods</p> <p>Prospective cohort study in 2611 patients with manifest arterial disease without known diabetes. Homeostasis model of insulin resistance (HOMA-IR) was used to quantify insulin resistance. The relation of HOMA-IR with cardiovascular events (vascular death, myocardial infarction or stroke) and all cause mortality was assessed with Cox regression analysis. In additional models adjustments were performed for the single components constituting the metabolic syndrome and for inflammation.</p> <p>Results</p> <p>HOMA-IR increases with the number of metabolic syndrome components (mean HOMA-IR ± SD in groups with 0, 1, 2, 3, 4 and 5 metabolic syndrome components: 1.4 ± 0.7; 1.8 ± 1.2; 2.4 ± 1.5; 3.1 ± 1.8; 4.0 ± 2.6; and 5.6 ± 3.6 respectively). High HOMA-IR was independently associated with an increased risk of cardiovascular events (tertile 2 vs. 1 HR 1.92; 95%CI 1.20-3.08) (tertile 3 vs.1 HR 1.78; 95%CI 1.10-2.89) and with all cause mortality (tertile 2 vs. 1 HR 1.80; 95%CI 1.04-3.10) (tertile 3 vs.1 HR 1.56; 95%CI 0.88-2.75). These relations were not influenced by the individual components of metabolic syndrome or by inflammation.</p> <p>Conclusions</p> <p>In patients with manifest arterial disease without known diabetes, insulin resistance increases with the number of metabolic syndrome components, and elevated insulin resistance increases the risk of new cardiovascular events.</p

    Lifestyle changes and kidney function: A 10-year follow-up study in patients with manifest cardiovascular disease

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    BACKGROUND: Patients with cardiovascular disease (CVD) are at higher risk of kidney function decline. The current study aimed to examine the association of lifestyle changes with kidney function decline in patients with manifest CVD. METHODS: A total of 2260 patients from the Utrecht Cardiovascular Cohort-Second Manifestations of ARTerial disease cohort with manifest CVD who returned for a follow-up visit after a median of 9.9 years were included. The relation between change in lifestyle factors (smoking, alcohol consumption, physical activity and obesity) and change in kidney function (eGFR and uACR) was assessed using linear regression models. RESULTS: An increase in body mass index (β -2.81; 95% CI -3.98; -1.63 per 5 kg/m2 ) and for men also an increase in waist circumference (β -0.87; 95% CI -1.28; -0.47 per 5 cm) were significantly associated with a steeper decline in eGFR over 10 years. Continuing smoking (β -2.44, 95% CI -4.43; -0.45) and recent smoking cessation during follow-up (β -3.27; 95% CI -5.20; -1.34) were both associated with a steeper eGFR decline compared to patients who remained as non- or previous smokers from baseline. No significant association was observed between physical exercise or alcohol consumption and kidney function decline. No significant relation between any lifestyle factor and change in uACR was observed. CONCLUSIONS: In patients with CVD, continuing smoking, recent smoking cessation and an increase in obesity markers were related to a steeper kidney function decline. Although no definite conclusions from this study can be drawn, the results support the importance of encouraging weight loss and smoking cessation in high-risk patients as a means of slowing down kidney function decline

    Prediction of individualized lifetime benefit from cholesterol lowering, blood pressure lowering, antithrombotic therapy, and smoking cessation in apparently healthy people.

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    AIMS: The benefit an individual can expect from preventive therapy varies based on risk-factor burden, competing risks, and treatment duration. We developed and validated the LIFEtime-perspective CardioVascular Disease (LIFE-CVD) model for the estimation of individual-level 10 years and lifetime treatment-effects of cholesterol lowering, blood pressure lowering, antithrombotic therapy, and smoking cessation in apparently healthy people. METHODS AND RESULTS: Model development was conducted in the Multi-Ethnic Study of Atherosclerosis (n = 6715) using clinical predictors. The model consists of two complementary Fine and Gray competing-risk adjusted left-truncated subdistribution hazard functions: one for hard cardiovascular disease (CVD)-events, and one for non-CVD mortality. Therapy-effects were estimated by combining the functions with hazard ratios from preventive therapy trials. External validation was performed in the Atherosclerosis Risk in Communities (n = 9250), Heinz Nixdorf Recall (n = 4177), and the European Prospective Investigation into Cancer and Nutrition-Netherlands (n = 25 833), and Norfolk (n = 23 548) studies. Calibration of the LIFE-CVD model was good and c-statistics were 0.67-0.76. The output enables the comparison of short-term vs. long-term therapy-benefit. In two people aged 45 and 70 with otherwise identical risk-factors, the older patient has a greater 10-year absolute risk reduction (11.3% vs. 1.0%) but a smaller gain in life-years free of CVD (3.4 vs. 4.5 years) from the same therapy. The model was developed into an interactive online calculator available via www.U-Prevent.com. CONCLUSION: The model can accurately estimate individual-level prognosis and treatment-effects in terms of improved 10-year risk, lifetime risk, and life-expectancy free of CVD. The model is easily accessible and can be used to facilitate personalized-medicine and doctor-patient communication

    Improving 10-year cardiovascular risk prediction in apparently healthy people : flexible addition of risk modifiers on top of SCORE2

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    AIMS: In clinical practice, factors associated with cardiovascular disease (CVD) like albuminuria, education level, or coronary artery calcium (CAC) are often known, but not incorporated in cardiovascular risk prediction models. The aims of the current study were to evaluate a methodology for the flexible addition of risk modifying characteristics on top of SCORE2 and to quantify the added value of several clinically relevant risk modifying characteristics. METHODS AND RESULTS: Individuals without previous CVD or DM were included from the UK Biobank; Atherosclerosis Risk in Communities (ARIC); Multi-Ethnic Study of Atherosclerosis (MESA); European Prospective Investigation into Cancer, The Netherlands (EPIC-NL); and Heinz Nixdorf Recall (HNR) studies (n = 409 757) in whom 16 166 CVD events and 19 149 non-cardiovascular deaths were observed over exactly 10.0 years of follow-up. The effect of each possible risk modifying characteristic was derived using competing risk-adjusted Fine and Gray models. The risk modifying characteristics were applied to individual predictions with a flexible method using the population prevalence and the subdistribution hazard ratio (SHR) of the relevant predictor. Risk modifying characteristics that increased discrimination most were CAC percentile with 0.0198 [95% confidence interval (CI) 0.0115; 0.0281] and hs-Troponin-T with 0.0100 (95% CI 0.0063; 0.0137). External validation was performed in the Clinical Practice Research Datalink (CPRD) cohort (UK, n = 518 015, 12 675 CVD events). Adjustment of SCORE2-predicted risks with both single and multiple risk modifiers did not negatively affect calibration and led to a modest increase in discrimination [0.740 (95% CI 0.736-0.745) vs. unimproved SCORE2 risk C-index 0.737 (95% CI 0.732-0.741)]. CONCLUSION: The current paper presents a method on how to integrate possible risk modifying characteristics that are not included in existing CVD risk models for the prediction of CVD event risk in apparently healthy people. This flexible methodology improves the accuracy of predicted risks and increases applicability of prediction models for individuals with additional risk known modifiers

    Intima-media thickness at the near or far wall of the common carotid artery in cardiovascular risk assessment

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    Aims: Current guidelines recommend measuring carotid intima-media thickness (IMT) at the far wall of the common carotid artery (CCA). We aimed to precisely quantify associations of near vs. far wall CCA-IMT with the risk for atherosclerotic cardiovascular disease (CVD, defined as coronary heart disease or stroke) and their added predictive values. Methods and results: We analysed individual records of 41 941 participants from 16 prospective studies in the Proof-ATHERO consortium {mean age 61 years [standard deviation (SD) = 11]; 53% female; 16% prior CVD}. Mean baseline values of near and far wall CCA-IMT were 0.83 (SD = 0.28) and 0.82 (SD = 0.27) mm, differed by a mean of 0.02 mm (95% limits of agreement: −0.40 to 0.43), and were moderately correlated [r = 0.44; 95% confidence interval (CI): 0.39–0.49). Over a median follow-up of 9.3 years, we recorded 10 423 CVD events. We pooled study-specific hazard ratios for CVD using random-effects meta-analysis. Near and far wall CCA-IMT values were approximately linearly associated with CVD risk. The respective hazard ratios per SD higher value were 1.18 (95% CI: 1.14–1.22; I² = 30.7%) and 1.20 (1.18–1.23; I² = 5.3%) when adjusted for age, sex, and prior CVD and 1.09 (1.07–1.12; I² = 8.4%) and 1.14 (1.12–1.16; I²=1.3%) upon multivariable adjustment (all P < 0.001). Assessing CCA-IMT at both walls provided a greater C-index improvement than assessing CCA-IMT at one wall only [+0.0046 vs. +0.0023 for near (P < 0.001), +0.0037 for far wall (P = 0.006)]. Conclusions: The associations of near and far wall CCA-IMT with incident CVD were positive, approximately linear, and similarly strong. Improvement in risk discrimination was highest when CCA-IMT was measured at both walls

    Estimated Glomerular Filtration Rate, Albuminuria, and Adverse Outcomes. An Individual-Participant Data Meta-Analysis

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    IMPORTANCE: Chronic kidney disease (low estimated glomerular filtration rate [eGFR] or albuminuria) affects approximately 14% of adults in the US. OBJECTIVE: To evaluate associations of lower eGFR based on creatinine alone, lower eGFR based on creatinine combined with cystatin C, and more severe albuminuria with adverse kidney outcomes, cardiovascular outcomes, and other health outcomes. DESIGN, SETTING, AND PARTICIPANTS: Individual-participant data meta-analysis of 27 503 140 individuals from 114 global cohorts (eGFR based on creatinine alone) and 720 736 individuals from 20 cohorts (eGFR based on creatinine and cystatin C) and 9 067 753 individuals from 114 cohorts (albuminuria) from 1980 to 2021. EXPOSURES: The Chronic Kidney Disease Epidemiology Collaboration 2021 equations for eGFR based on creatinine alone and eGFR based on creatinine and cystatin C; and albuminuria estimated as urine albumin to creatinine ratio (UACR). MAIN OUTCOMES AND MEASURES: The risk of kidney failure requiring replacement therapy, all-cause mortality, cardiovascular mortality, acute kidney injury, any hospitalization, coronary heart disease, stroke, heart failure, atrial fibrillation, and peripheral artery disease. The analyses were performed within each cohort and summarized with random-effects meta-analyses. RESULTS: Within the population using eGFR based on creatinine alone (mean age, 54 years [SD, 17 years]; 51% were women; mean follow-up time, 4.8 years [SD, 3.3 years]), the mean eGFR was 90 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 11 mg/g (IQR, 8-16 mg/g). Within the population using eGFR based on creatinine and cystatin C (mean age, 59 years [SD, 12 years]; 53% were women; mean follow-up time, 10.8 years [SD, 4.1 years]), the mean eGFR was 88 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 9 mg/g (IQR, 6-18 mg/g). Lower eGFR (whether based on creatinine alone or based on creatinine and cystatin C) and higher UACR were each significantly associated with higher risk for each of the 10 adverse outcomes, including those in the mildest categories of chronic kidney disease. For example, among people with a UACR less than 10 mg/g, an eGFR of 45 to 59 mL/min/1.73 m2 based on creatinine alone was associated with significantly higher hospitalization rates compared with an eGFR of 90 to 104 mL/min/1.73 m2 (adjusted hazard ratio, 1.3 [95% CI, 1.2-1.3]; 161 vs 79 events per 1000 person-years; excess absolute risk, 22 events per 1000 person-years [95% CI, 19-25 events per 1000 person-years]). CONCLUSIONS AND RELEVANCE: In this retrospective analysis of 114 cohorts, lower eGFR based on creatinine alone, lower eGFR based on creatinine and cystatin C, and more severe UACR were each associated with increased rates of 10 adverse outcomes, including adverse kidney outcomes, cardiovascular diseases, and hospitalizations
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