Treatment variation in stent choice in patients with stable or unstable coronary artery disease

Aim: Variations in treatment are the result of differences in demographic and clinical factors (e.g. anatomy), but physician and hospital factors may also contribute to treatment variation. The choice of treatment is considered important since it could lead to differences in long-term outcomes. This study explores the associations with stent choice: i.e. drug-eluting stent (DES) versus bare-metal stents (BMS) for Dutch patients diagnosed with stable or unstable coronary artery disease (CAD). Methods & results: Associations with treatment decisions were based on a prospective cohort of 692 patients with stable or unstable CAD. Of those patients, 442 patients were treated with BMS or DES. Multiple logistic regression analyses were performed to identify variables associated with stent choice. Bivariate analyses showed that NYHA class, number of diseased vessels, previous percutaneous coronary intervention, smoking, diabetes, and the treating hospital were associated with stent type. After correcting for other associations the treating hospital remained significantly associated with stent type in the stable CAD population. Conclusions: This study showed that several factors were associated with stent choice. While patients generally appear to receive the most optimal stent given their clinical characteristics, stent choice seems partially determined by the treating hospital, which may lead to differences in longterm outcome

A cluster of blood-based protein biomarkers associated with decreased cerebral blood flow relates to future cardiovascular events in patients with cardiovascular disease

Biological processes underlying decreased cerebral blood flow (CBF) in patients with cardiovascular disease (CVD) are largely unknown. We hypothesized that identification of protein clusters associated with lower CBF in patients with CVD may explain underlying processes. In 428 participants (74% cardiovascular diseases; 26% reference participants) from the Heart-Brain Connection Study, we assessed the relationship between 92 plasma proteins from the Olink® cardiovascular III panel and normal-appearing grey matter CBF, using affinity propagation and hierarchical clustering algorithms, and generated a Biomarker Compound Score (BCS). The BCS was related to cardiovascular risk and observed cardiovascular events within 2-year follow-up using Spearman correlation and logistic regression. Thirteen proteins were associated with CBF (ρSpearman range: −0.10 to −0.19, pFDR-corrected &lt;0.05), and formed one cluster. The cluster primarily reflected extracellular matrix organization processes. The BCS was higher in patients with CVD compared to reference participants (pFDR-corrected &lt;0.05) and was associated with cardiovascular risk (ρSpearman 0.42, p &lt; 0.001) and cardiovascular events (OR 2.05, p &lt; 0.01). In conclusion, we identified a cluster of plasma proteins related to CBF, reflecting extracellular matrix organization processes, that is also related to future cardiovascular events in patients with CVD, representing potential targets to preserve CBF and mitigate cardiovascular risk in patients with CVD.</p

Evolution of renal function and predictive value of serial renal assessments among patients with acute coronary syndrome:BIOMArCS study

Background: Impaired renal function predicts mortality in acute coronary syndrome (ACS), but its evolution immediately following index ACS and preceding next ACS has not been described in detail. We aimed to describe this evolution using serial measurements of creatinine, glomerular filtration rate [eGFRCr] and cystatin C [CysC]. Methods: From 844 ACS patients included in the BIOMArCS study, we analysed patient-specific longitudinal marker trajectories from the case-cohort of 187 patients to determine the risk of the endpoint (cardiovascular death or hospitalization for recurrent non-fatal ACS) during 1-year follow-up. Study included only patients with eGFRCr ≥ 30 ml/min/1.73 m2. Survival analyses were adjusted for GRACE risk score and based on data >30 days after the index ACS (mean of 8 sample per patient). Results: Mean age was 63 years, 79% were men, 43% had STEMI, and 67% were in eGFR stages 2–3. During hospitalization for index ACS (median [IQR] duration: 5 (3–7) days), CysC levels indicated deterioration of renal function earlier than creatinine did (CysC peaked on day 3, versus day 6 for creatinine), and both stabilized after two weeks. Higher CysC levels, but not creatinine, predicted the endpoint independently of the GRACE score within the first year after index ACS (adjusted HR [95% CI] per 1SD increase: 1.68 [1.03–2.74]). Conclusion: Immediately following index ACS, plasma CysC levels deteriorate earlier than creatinine-based indices do, but neither marker stabilizes during hospitalization but on average two weeks after ACS. Serially measured CysC levels predict mortality or recurrence of ACS during 1-year follow-up independently of patients' GRACE risk score

Biomechanical factors in atherosclerosis: mechanisms and clinical implications†

Blood vessels are exposed to multiple mechanical forces that are exerted on the vessel wall (radial, circumferential and longitudinal forces) or on the endothelial surface (shear stress). The stresses and strains experienced by arteries influence the initiation of atherosclerotic lesions, which develop at regions of arteries that are exposed to complex blood flow. In addition, plaque progression and eventually plaque rupture is influenced by a complex interaction between biological and mechanical factors—mechanical forces regulate the cellular and molecular composition of plaques and, conversely, the composition of plaques determines their ability to withstand mechanical load. A deeper understanding of these interactions is essential for designing new therapeutic strategies to prevent lesion development and promote plaque stabilization. Moreover, integrating clinical imaging techniques with finite element modelling techniques allows for detailed examination of local morphological and biomechanical characteristics of atherosclerotic lesions that may be of help in prediction of future events. In this ESC Position Paper on biomechanical factors in atherosclerosis, we summarize the current ‘state of the art' on the interface between mechanical forces and atherosclerotic plaque biology and identify potential clinical applications and key questions for future researc

Novel methodologies for biomarker discovery in atherosclerosis

Identification of subjects at increased risk for cardiovascular events plays a central role in the worldwide efforts to improve prevention, prediction, diagnosis, and prognosis of cardiovascular disease and to decrease the related costs. Despite their high predictive value on population level, traditional risk factors fail to fully predict individual risk. This position paper provides a summary of current vascular biomarkers other than the traditional risk factors with a special focus on the emerging −omics technologies. The definition of biomarkers and the identification and use of classical biomarkers are introduced, and we discuss the limitations of current biomarkers such as high sensitivity C-reactive protein (hsCRP) or N-terminal pro-brain natriuretic peptide (NT-proBNP). This is complemented by circulating plasma biomarkers, including high-density lipoprotein (HDL), and the conceptual shift from HDL cholesterol levels to HDL composition/function for cardiovascular risk assessment. Novel sources for plasma-derived markers include microparticles, microvesicles, and exosomes and their use for current omics-based analytics. Measurement of circulating micro-RNAs, short RNA sequences regulating gene expression, has attracted major interest in the search for novel biomarkers. Also, mass spectrometry and nuclear magnetic resonance spectroscopy have become key complementary technologies in the search for new biomarkers, such as proteomic searches or identification and quantification of small metabolites including lipids (metabolomics and lipidomics). In particular, pro-inflammatory lipid metabolites have gained much interest in the cardiovascular field. Our consensus statement concludes on leads and needs in biomarker research for the near future to improve individual cardiovascular risk predictio

Circulating biomarkers of cardiovascular disease are related to aneurysm volume in abdominal aortic aneurysm

Background: Surveillance programs in abdominal aortic aneurysms (AAA) are mainly based on imaging and leave room for improvement to timely identify patients at risk for AAA growth. Many biomarkers are dysregulated in patients with AAA, which fuels interest in biomarkers as indicators of disease progression. We examined associations of 92 cardiovascular disease (CVD)-related circulating biomarkers with AAA and sac volume. Methods: In a cross-sectional analysis, we separately investigated (1) 110 watchful waiting (WW) patients (undergoing periodic surveillance imaging without planned intervention) and (2) 203 patients after endovascular aneurysm repair (EVAR). The Cardiovascular Panel III (Olink Proteomics AB, Sweden) was used to measure 92 CVD-related circulating biomarkers. We used cluster analyses to investigate protein-based subphenotypes, and linear regression to examine associations of biomarkers with AAA and sac volume on CT scans. Results: Cluster analyses revealed two biomarker-based subgroups in both WW and EVAR patients, with higher levels of 76 and 74 proteins, respectively, in one subgroup versus the other. In WW patients, uPA showed a borderline significant association with AAA volume. Adjusting for clinical characteristics, there was a difference of −0.092 (−0.148, −0.036) loge mL in AAA volume per SD uPA. In EVAR patients, after multivariable adjustment, four biomarkers remained significantly associated with sac volume. The mean effects on sac volume per SD difference were: LDLR: −0.128 (−0.212, −0.044), TFPI: 0.139 (0.049, 0.229), TIMP4: 0.110 (0.023, 0.197), IGFBP-2: 0.103 (0.012, 0.194). Conclusion: LDLR, TFPI, TIMP4, and IGFBP-2 were independently associated with sac volume after EVAR. Subgroups of patients with high levels of the majority of CVD-related biomarkers emphasize the intertwined relationship between AAA and CVD. ClinicalTrials.gov Identifier: NCT03703947.</p

Temporal Evolution of Serum Concentrations of High-Sensitivity Cardiac Troponin During 1 Year After Acute Coronary Syndrome Admission

Background Detailed insights in temporal evolution of high-sensitivity cardiac troponin following acute coronary syndrome (ACS) are currently missing. We aimed to describe and compare the post-ACS kinetics of high-sensitivity cardiac troponin I (hs-cTnI) and high-sensitivity cardiac troponin T (hs-cTnT), and to determine their intra- and interindividual variation in clinically stable patients. Methods and Results We determined hs-cTnI (Abbott) and hs-cTnT (Roche) in 1507 repeated blood samples, derived from 191 patients with ACS (median, 8/patient) who remained free from adverse cardiac events during 1-year follow-up. Post-ACS kinetics were studied by linear mixed-effect models. Using the samples collected in the 6- to 12-month post-ACS time frame, patients were then considered to have chronic coronary syndrome. We determined (differences between) the average hs-cTnI and average hs-cTnT concentration, and the intra- and interindividual variation for both biomarkers. Compared with hs-cTnT, hs-cTnI peaked higher (median 3506 ng/L versus 494 ng/L; P<0.001) and was quicker below the biomarker-specific upper reference limit (16 versus 19 days; P<0.001). In the post-6-month samples, hs-cTnI and hs-cTnT showed modest correlation (rspearman

Evolution of renal function and predictive value of serial renal assessments among patients with acute coronary syndrome: BIOMArCS study

Background: Impaired renal function predicts mortality in acute coronary syndrome (ACS), but its evolution immediately following index ACS and preceding next ACS has not been described in detail. We aimed to describe this evolution using serial measurements of creatinine, glomerular filtration rate [eGFRCr] and cystatin C [CysC]. Methods: F