64 research outputs found

    The relation between VLDL-cholesterol and risk of cardiovascular events in patients with manifest cardiovascular disease

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    INTRODUCTION: Apolipoprotein B containing lipoproteins are atherogenic. There is evidence that with low plasma low density lipoprotein cholesterol (LDL-C) levels residual vascular risk might be caused by triglyceride rich lipoproteins such as very-low density lipoproteins (VLDL), chylomicrons and their remnants. We investigated the relationship between VLDL-cholesterol (VLDL-C) and recurrent major adverse cardiovascular events (MACE), major adverse limb events (MALE) and all-cause mortality in a cohort of patients with cardiovascular disease. METHODS: Prospective cohort study in 8057 patients with cardiovascular disease from the UCC-SMART study. The relation between calculated VLDL-C levels and the occurrence of MACE, MALE and all-cause mortality was analyzed with Cox regression models. RESULTS: Patients mean age was 60 ± 10 years, 74% were male, 4894 (61%) had coronary artery disease, 2445 (30%) stroke, 1425 (18%) peripheral arterial disease and 684 (8%) patients had an abdominal aorta aneurysm at baseline. A total of 1535 MACE, 571 MALE and 1792 deaths were observed during a median follow up of 8.2 years (interquartile range 4.512.2). VLDL-C was not associated with risk of MACE or all-cause mortality. In the highest quartile of VLDL-C the risk was higher for major adverse limb events (MALE) (HR 1.49; 95%CI 1.16-1.93) compared to the lowest quartile, after adjustment for confounders including LDL-C and lipid lowering medication. CONCLUSION: In patients with clinically manifest cardiovascular disease plasma VLDL-C confers an increased risk for MALE, but not for MACE and all-cause mortality, independent of established risk factors including LDL-C and lipid-lowering medication

    Relationship between classic vascular risk factors and cumulative recurrent cardiovascular event burden in patients with clinically manifest vascular disease: Results from the UCC-SMART prospective cohort study

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    Objective The aim of the current study was to assess the relationship between classic cardiovascular risk factors and risk of not only the first recurrent atherosclerotic cardiovascular event, but also the total number of non-fatal and fatal cardiovascular events in patients with recently clinically manifest cardiovascular disease (CVD). Design Prospective cohort study. Setting Tertiary care centre. Participants 7239 patients with a recent first manifestation of CVD from the prospective UCC-SMART (Utrecht Cardiovascular Cohort-Second Manifestations of ARTerial disease) cohort study. Outcome measures Total cardiovascular events, including myocardial infarction, stroke, vascular interventions, major limb events and cardiovascular mortality. Results During a median follow-up of 8.9 years, 1412 patients had one recurrent cardiovascular event, while 1290 patients had two or more recurrent events, with a total of 5457 cardiovascular events during follow-up. The HRs for the first recurrent event and cumulative event burden using Prentice-Williams-Peterson models, respectively, were 1.36 (95% CI 1.25 to 1.48) and 1.26 (95% CI 1.17 to 1.35) for smoking, 1.14 (95% CI 1.11 to 1.18) and 1.09 (95% CI 1.06 to 1.12) for non-high-density lipoprotein (HDL) cholesterol, and 1.05 (95% CI 1.03 to 1.07) and 1.04 (95% CI 1.03 to 1.06) for systolic blood pressure per 10 mm Hg. Conclusions In a cohort of patients with established CVD, systolic blood pressure, non-HDL cholesterol and current smoking are important risk factors for not only the first, but also subsequent recurrent events during follow-up. Recurrent event analysis captures the full cumulative burden of CVD in patients

    Is the SMART risk prediction model ready for real-world implementation? A validation study in a routine care setting of approximately 380 000 individuals

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    AIMS: Reliably quantifying event rates in secondary prevention could aid clinical decision-making, including quantifying potential risk reductions of novel, and sometimes expensive, add-on therapies. We aimed to assess whether the SMART risk prediction model performs well in a real-world setting. METHODS AND RESULTS: We conducted a historical open cohort study using UK primary care data from the Clinical Practice Research Datalink (2000-2017) diagnosed with coronary, cerebrovascular, peripheral, and/or aortic atherosclerotic cardiovascular disease (ASCVD). Analyses were undertaken separately for cohorts with established (≥6 months) vs. newly diagnosed ASCVD. The outcome was first post-cohort entry occurrence of myocardial infarction, stroke, or cardiovascular death. Among the cohort with established ASCVD [n = 244 578, 62.1% male, median age 67.3 years, interquartile range (IQR) 59.2-74.0], the calibration and discrimination achieved by the SMART model was not dissimilar to performance at internal validation [Harrell's c-statistic = 0.639, 95% confidence interval (CI) 0.636-0.642, compared with 0.675, 0.642-0.708]. Decision curve analysis indicated that the model outperformed treat all and treat none strategies in the clinically relevant 20-60% predicted risk range. Consistent findings were observed in sensitivity analyses, including complete case analysis (n = 182 482; c = 0.624, 95% CI 0.620-0.627). Among the cohort with newly diagnosed ASCVD (n = 136 445; 61.0% male; median age 66.0 years, IQR 57.7-73.2), model performance was weaker with more exaggerated risk under-prediction and a c-statistic of 0.559, 95% CI 0.556-0.562. CONCLUSIONS: The performance of the SMART model in this validation cohort demonstrates its potential utility in routine healthcare settings in guiding both population and individual-level decision-making for secondary prevention patients

    The effect of computerized decision support systems on cardiovascular risk factors: A systematic review and meta-analysis

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    Background: Cardiovascular risk management (CVRM) is notoriously difficult because of multi-morbidity and the different phenotypes and severities of cardiovascular disease. Computerized decision support systems (CDSS) enable the clinician to integrate the latest scientific evidence and patient information into tailored strategies. The effect on cardiovascular risk factor management is yet to be confirmed. Methods: We performed a systematic review and meta-analysis evaluating the effects of CDSS on CVRM, defined as the change in absolute values and attainment of treatment goals of systolic blood pressure (SBP), low density lipoprotein cholesterol (LDL-c) and HbA1c. Also, CDSS characteristics related to more effective CVRM were identified. Eligible articles were methodologically appraised using the Cochrane risk of bias tool. We calculated mean differences, relative risks, and if appropriate (I2 < 70%), pooled the results using a random-effects model. Results: Of the 14,335 studies identified, 22 were included. Four studies reported on SBP, 3 on LDL-c, 10 on CVRM in patients with type II diabetes and 5 on guideline adherence. The CDSSs varied considerably in technical performance and content. Heterogeneity of results was such that quantitative pooling was often not appropriate. Among CVRM patients, the results tended towards a beneficial effect of CDSS, but only LDL-c target attainment in diabetes patients reached statistical significance. Prompting, integration into the electronical health record, patient empowerment, and medication support were related to more effective CVRM. Conclusion: We did not find a clear clinical benefit from CDSS in cardiovascular risk factor levels and target attainment. Some features of CDSS seem more promising than others. However, the variability in CDSS characteristics and heterogeneity of the results – emphasizing the immaturity of this research area - limit stronger conclusions. Clinical relevance of CDSS in CVRM might additionally be sought in the improvement of shared decision making and patient empowerment

    Estimated individual lifetime benefit from PCSK9 inhibition in statin-treated patients with coronary artery disease

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    OBJECTIVE: In statin-treated patients with stable coronary artery disease (CAD), residual risk of cardiovascular events is partly explained by plasma levels of low-density lipoprotein cholesterol (LDL-C). This study aimed to estimate individual benefit of proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibition in CAD patients already treated with high-dose statin. METHODS: Individual lifetime benefit was estimated in months gain free of stroke or myocardial infarction (MI) until age 80 years. Predictions were based on two competing risk models developed in data from 4853 patients with CAD originating from the atorvastatin 80 mg arm of the Treating to New Targets (TNT) trial. The relative effect of PCSK9 inhibition was added to the models and was assumed based on average estimates from large clinical trials. We accounted for individual LDL-C levels, assuming 50% LDL-C reduction by PCSK9 inhibition and 21% cardiovascular risk reduction per mmol/L (39 mg/dL) LDL-C lowering. RESULTS: Estimated individual gain was 1.8 mmol/L (>70 mg/dL). Estimated benefit was lowest (≤5 months) in older patients (≥70 years), in particular if LDL-C and other risk factors levels were low. CONCLUSION: The individual estimated lifetime benefit from PCSK9 inhibition in patients with stable CAD on high-dose statin varied from <6 to ≥12 months free of stroke or MI. Highest benefit is expected in younger patients (age 40-60 years) with high risk factor burden and relatively high LDL-C levels. TRIAL REGISTRATION NUMBER: NCT00327691; Post-results

    Prediction of Lifetime and 10-Year Risk of Cancer in Individual Patients With Established Cardiovascular Disease

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    BACKGROUND: Cardiovascular disease (CVD) and cancer share many common risk factors; patients with CVD also may be at risk of developing cancer. OBJECTIVES: The aim of this study was to derive and externally validate prediction models for the estimation of lifetime and 10-year risk for total, colorectal, and lung cancer in patients with established CVD. METHODS: Data from patients with established CVD from the UCC-SMART cohort (N ¼ 7,280) were used for model development, and from the CANTOS trial (N ¼ 9,322) for model validation. Predictors were selected based on previously published cancer risk scores, clinical availability, and presence in the derivation dataset. Fine and Gray competing risk-adjusted lifetime models were developed for the outcomes total, colorectal, and lung cancer. RESULTS: Selected predictors were age, sex, smoking, weight, height, alcohol use, antiplatelet use, diabetes, and C-reactive protein. External calibration for the 4-year risk of lung, colorectal, and total cancer was reasonable in our models, as was discrimination with C-statistics of 0.74, 0.64, and 0.63, respectively. Median predicted lifetime and 10-year risks in CANTOS were 26% (range 1% to 52%) and 13% (range 1% to 31%) for total cancer; 4% (range 0% to 13%) and 2% (range 0% to 6%) for colorectal cancer; and 5% (range 0% to 37%) and 2% (range 0% to 24%) for lung cancer. CONCLUSIONS: Lifetime and 10-year risk of total, colorectal, and lung cancer can be estimated reasonably well in patients with established CVD with readily available clinical predictors. With additional study, these tools could be used in clinical practice to further aid in the emphasis of healthy lifestyle changes and to guide thresholds for targeted diagnostics and screening

    End-stage kidney disease in patients with clinically manifest vascular disease; incidence and risk factors: results from the UCC-SMART cohort study

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    Background: Patients with cardiovascular disease (CVD) are at increased risk of end-stage kidney disease (ESKD). Insights into the incidence and role of modifiable risk factors for end-stage kidney disease may provide means for prevention in patients with cardiovascular disease. Methods: We included 8402 patients with stable cardiovascular disease. Incidence rates (IRs) for end-stage kidney disease were determined stratified according to vascular disease location. Cox proportional hazard models were used to assess the risk of end-stage kidney disease for the different determinants. Results: Sixty-five events were observed with a median follow-up of 8.6 years. The overall incidence rate of end-stage kidney disease was 0.9/1000 person-years. Patients with polyvascular disease had the highest incidence rate (1.8/1000 person-years). Smoking (Hazard ratio (HR) 1.87; 95% CI 1.10–3.19), type 2 diabetes (HR 1.81; 95% CI 1.05–3.14), higher systolic blood pressure (HR 1.37; 95% CI 1.24–1.52/10 mmHg), lower estimated glomerular filtration rate (eGFR) (HR 2.86; 95% CI 2.44–3.23/10 mL/min/1.73 m ) and higher urine albumin/creatinine ratio (uACR) (HR 1.19; 95% CI 1.15–1.23/10 mg/mmol) were independently associated with elevated risk of end-stage kidney disease. Body mass index (BMI), waist circumference, non-HDL-cholesterol and exercise were not independently associated with risk of end-stage kidney disease. Conclusions: Incidence of end-stage kidney disease in patients with cardiovascular disease varies according to vascular disease location. Several modifiable risk factors for end-stage kidney disease were identified in patients with cardiovascular disease. These findings highlight the potential of risk factor management in patients with manifest cardiovascular disease. Graphic abstract: [Figure not available: see fulltext.].

    Comparison of the European and U.S. guidelines for lipid-lowering therapy in primary prevention of cardiovascular disease.

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    Population-wide impacts of new guidelines in the primary prevention of atherosclerotic cardiovascular disease (ASCVD) should be explored in independent cohorts. Assess and compare the lipid-lowering therapy eligibility and predictive classification performance of 2016 and 2021 European Society of Cardiology (ESC), 2019 American Heart Association/American College of Cardiology (AHA/ACC) and 2022U.S. Preventive Services Task Force (USPSTF) guidelines. Participants from the Colaus|PsyCoLaus study, without ASCVD and not taking lipid-lowering therapy at baseline. Derivation of 10-year risk for ASCVD using SCORE1, SCORE2 (including SCORE2-OP) and PCE. Computation of the number of people eligible for lipid-lowering therapy based on each guideline and assessment of discrimination and calibration metrics of the risk models using first incident ASCVD as an outcome. Among 4,092 individuals, 158 (3.9%) experienced an incident ASCVD during a median follow-up of 9 years (IQR, 1.1). Lipid-lowering therapy was recommended or considered in 40.2% (95% CI, 38.2-42.2), 26.4% (24.6-28.2), 28.6% (26.7-30.5) and 22.6% (20.9-24.4) of women and in 62.1% (59.8-64.3), 58.7% (56.4-61.0), 52.6% (50.3-54.9) and 48.4% (46.1-50.7) of men according to 2016 ESC, 2021 ESC, 2019 AHA/ACC and 2022 USPSTF guidelines, respectively. 43.3% and 46.7% of women facing an incident ASCVD were not eligible for lipid-lowering therapy at baseline according to 2021 ESC and 2022 USPSTF, compared to 21.7% and 38.3% using 2016 ESC and 2019 AHA/ACC, respectively. Both 2022 USPSTF and 2021 ESC guidelines particularly reduced lipid-lowering therapy eligibility in women. Nearly half of women who faced an incident ASCVD were not eligible for lipid-lowering therapy

    Treatment gaps in the implementation of LDL cholesterol control among high- and very high-risk patients in Europe between 2020–2021: the multinational observational SANTORINI study

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    Background European data pre-2019 suggest statin monotherapy is the most common approach to lipid management for preventing cardiovascular (CV) events, resulting in only one-fifth of high- and very high-risk patients achieving the 2019 ESC/EAS recommended low-density lipoprotein cholesterol (LDL-C) goals. Whether the treatment landscape has evolved, or gaps persist remains of interest. Methods Baseline data are presented from SANTORINI, an observational, prospective study that documents the use of lipid-lowering therapies (LLTs) in patients ≥18 years at high or very high CV risk between 2020 and 2021 across primary and secondary care settings in 14 European countries. Findings Of 9602 enrolled patients, 9044 with complete data were included (mean age: 65.3 ± 10.9 years; 72.6% male). Physicians reported using 2019 ESC/EAS guidelines as a basis for CV risk classification in 52.0% (4706/9044) of patients (overall: high risk 29.2%; very high risk 70.8%). However, centrally re-assessed CV risk based on 2019 ESC/EAS guidelines suggested 6.5% (308/4706) and 91.0% (4284/4706) were high- and very high-risk patients, respectively. Overall, 21.8% of patients had no documented LLTs, 54.2% were receiving monotherapy and 24.0% combination LLT. Median (interquartile range [IQR]) LDL-C was 2.1 (1.6, 3.0) mmol/L (82 [60, 117] mg/dL), with 20.1% of patients achieving risk-based LDL-C goals as per the 2019 ESC/EAS guidelines. Interpretation At the time of study enrolment, 80% of high- and very high-risk patients failed to achieve 2019 ESC/EAS guidelines LDL-C goals. Contributory factors may include CV risk underestimation and underutilization of combination therapies. Further efforts are needed to achieve current guideline-recommended LDL-C goals. Trial registration ClinicalTrials.gov Identifier: NCT04271280. Funding This study is funded by Daiichi Sankyo Europe GmbH, Munich, Germany

    Routinely measured hematological parameters and prediction of recurrent vascular events in patients with clinically manifest vascular disease

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    BACKGROUND AND AIMS: The predictive value of traditional risk factors for vascular events in patients with manifest vascular disease is limited, underscoring the need for novel biomarkers to improve risk stratification. Since hematological parameters are routinely assessed in clinical practice, they are readily available candidates. METHODS: We used data from 3,922 vascular patients, who participated in the Second Manifestations of ARTerial Disease (SMART) study. We first investigated associations between recurrent vascular events and 22 hematological parameters, obtained from the Utrecht Patient Oriented Database (UPOD), and then assessed whether parameters associated with outcome improved risk prediction. RESULTS: After adjustment for all SMART risk score (SRS) variables, lymphocyte %, neutrophil count, neutrophil % and red cell distribution width (RDW) were significantly associated with vascular events. When individually added to the SRS, lymphocyte % improved prediction of recurrent vascular events with a continuous net reclassification improvement (cNRI) of 17.4% [95% CI: 2.1, 32.1%] and an increase in c-statistic of 0.011 [0.000, 0.022]. The combination of lymphocyte % and neutrophil count resulted in a cNRI of 22.2% [3.2, 33.4%] and improved c-statistic by 0.011 [95% CI: 0.000, 0.022]. Lymphocyte % and RDW yielded a cNRI of 18.7% [3.3, 31.9%] and improved c-statistic by 0.016 [0.004, 0.028]. However, the addition of hematological parameters only modestly increased risk estimates for patients with an event during follow-up. CONCLUSIONS: Several hematological parameters were independently associated with recurrent vascular events. Lymphocyte % alone and in combination with other parameters enhanced discrimination and reclassification. However, the incremental value for patients with a recurrent event was limited
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