Geographic disparity of pathophysiological coronary artery disease characteristics: Insights from ASET trials

The geographical disparity in the pathophysiological pattern of coronary artery disease (CAD) among patients undergoing percutaneous coronary intervention (PCI) is unknown. To elucidate the geographical variance in the pathophysiological characteristics of CAD. Physiological indices derived from angiography-based fractional flow reserve pullbacks from patients with chronic coronary syndrome enrolled in the ASET Japan (n = 206) and ASET Brazil (n = 201) studies, which shared the same eligibility criteria, were analysed. The pathophysiological patterns of CAD were characterised using Murray law-based quantitative flow ratio (μQFR)-derived indices acquired from pre-PCI angiograms. The diffuseness of CAD was defined by the μQFR pullback pressure gradient index. Significant functional stenoses pre-PCI (μQFR ≤0.80) were more frequent in ASET Japan compared to ASET Brazil (89.9% vs. 67.5%, p < 0.001), as were rates of a post-PCI μQFR <0.91 (22.1% vs. 12.9%, p = 0.013). In the multivariable analysis, pre-procedural μQFR and diffuse disease were independent factors for predicting a post-PCI μQFR <0.91, which contributed to the different rates of post-PCI μQFR ≥0.91 between the studies. Among vessels with a post-PCI μQFR <0.91, a consistent diffuse pattern of CAD pre- and post-PCI occurred in 78.3% and 76.7% of patients in ASET Japan and Brazil, respectively; only 6.3% (Japan) and 10.0% (Brazil) of vessels had a major residual gradient. Independent risk factors for diffuse disease were diabetes mellitus in ASET Japan, and age and male gender in Brazil. There was geographic disparity in pre-procedural angiography-based pathophysiological characteristics. The combined pre-procedural physiological assessment of vessel μQFR and diffuseness of CAD may potentially identify patients who will benefit most from PCI. [Abstract copyright: Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.

World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions

BACKGROUND: To help adapt cardiovascular disease risk prediction approaches to low-income and middle-income countries, WHO has convened an effort to develop, evaluate, and illustrate revised risk models. Here, we report the derivation, validation, and illustration of the revised WHO cardiovascular disease risk prediction charts that have been adapted to the circumstances of 21 global regions. METHODS: In this model revision initiative, we derived 10-year risk prediction models for fatal and non-fatal cardiovascular disease (ie, myocardial infarction and stroke) using individual participant data from the Emerging Risk Factors Collaboration. Models included information on age, smoking status, systolic blood pressure, history of diabetes, and total cholesterol. For derivation, we included participants aged 40-80 years without a known baseline history of cardiovascular disease, who were followed up until the first myocardial infarction, fatal coronary heart disease, or stroke event. We recalibrated models using age-specific and sex-specific incidences and risk factor values available from 21 global regions. For external validation, we analysed individual participant data from studies distinct from those used in model derivation. We illustrated models by analysing data on a further 123 743 individuals from surveys in 79 countries collected with the WHO STEPwise Approach to Surveillance. FINDINGS: Our risk model derivation involved 376 177 individuals from 85 cohorts, and 19 333 incident cardiovascular events recorded during 10 years of follow-up. The derived risk prediction models discriminated well in external validation cohorts (19 cohorts, 1 096 061 individuals, 25 950 cardiovascular disease events), with Harrell's C indices ranging from 0·685 (95% CI 0·629-0·741) to 0·833 (0·783-0·882). For a given risk factor profile, we found substantial variation across global regions in the estimated 10-year predicted risk. For example, estimated cardiovascular disease risk for a 60-year-old male smoker without diabetes and with systolic blood pressure of 140 mm Hg and total cholesterol of 5 mmol/L ranged from 11% in Andean Latin America to 30% in central Asia. When applied to data from 79 countries (mostly low-income and middle-income countries), the proportion of individuals aged 40-64 years estimated to be at greater than 20% risk ranged from less than 1% in Uganda to more than 16% in Egypt. INTERPRETATION: We have derived, calibrated, and validated new WHO risk prediction models to estimate cardiovascular disease risk in 21 Global Burden of Disease regions. The widespread use of these models could enhance the accuracy, practicability, and sustainability of efforts to reduce the burden of cardiovascular disease worldwide. FUNDING: World Health Organization, British Heart Foundation (BHF), BHF Cambridge Centre for Research Excellence, UK Medical Research Council, and National Institute for Health Research

Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies

Aims: There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after ‘recalibration’, a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied. Methods & Results: Using individual-participant data on 360737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at ‘high’ 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE overpredicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29–39% of individuals aged \u3e_40years as high risk. By contrast, recalibration reduced this proportion to 22–24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44–51 such individuals using original algorithms, in contrast to 37–39 individuals with recalibrated algorithms. Conclusions: Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need

Changes in the Charged Metabolite and Sugar Profiles of Pasteurized and Unpasteurized Japanese Sake with Storage

Japanese sake (rice wine) is commonly heat treated (pasteurized) to maintain its quality. In this study, temporal changes in the metabolite profiles of pasteurized and unpasteurized sake were investigated during storage. Metabolomic analyses were conducted for eight sets of pasteurized and unpasteurized sake obtained from single process batches stored at 8 or 20 °C for 0, 1, 2, or 4 months. Capillary electrophoresis time-of-flight mass spectrometry and liquid chromatography tandem mass spectrometry were used to obtain charged metabolite and sugar profiles, respectively. The total amino acid concentration decreased with storage, and the decrease was faster in pasteurized sake than in unpasteurized. The organic acid concentrations were relatively constant in both types of sake. Peptide and glucose concentrations increased and polysaccharide concentrations decreased in unpasteurized sake, while they were relatively constant in pasteurized sake. Rather than stabilizing the sake metabolite profile during storage, pasteurization results in characteristic changes compared to unpasteurized sake

Preprocedural physiological assessment of coronary disease patterns to predict haemodynamic outcomes post-PCI

Even with intracoronary imaging-guided stent optimisation, suboptimal haemodynamic outcomes post-percutaneous coronary intervention (PCI) can be related to residual lesions in non-stented segments. Preprocedural assessment of pathophysiological coronary artery disease (CAD) patterns could help predict the physiological response to PCI. The aim of this study was to assess the relationship between preprocedural pathophysiological haemodynamic patterns and intracoronary imaging findings, as well as their association with physiological outcomes immediately post-PCI. Data from 206 patients with chronic coronary syndrome enrolled in the ASET-JAPAN study were analysed. Pathophysiological CAD patterns were characterised using Murray law-based quantitative flow ratio (μQFR)-derived indices acquired from pre-PCI angiograms. The diffuseness of CAD was defined by the pullback pressure gradient (PPG) index. Intracoronary imaging in stented segments after stent optimisation was also analysed. In the multivariable analysis, diffuse disease - defined by the pre-PCI μQFR-PPG index - was an independent factor for predicting a post-PCI μQFR <0.91 (per 0.1 decrease of PPG index, odds ratio 1.57, 95% confidence interval: 1.07-2.34; p=0.022), whereas the stent expansion index (EI) was not associated with a suboptimal post-PCI μQFR. Among vessels with an EI ≥80% and post-PCI μQFR <0.91, 84.0% of those vessels had a diffuse pattern preprocedure. There was no significant difference in EI between vessels with diffuse disease and those with focal disease. The average plaque burden in the stented segment was significantly larger in vessels with a preprocedural diffuse CAD pattern. A physiological diffuse pattern preprocedure was an independent factor in predicting unfavourable immediate haemodynamic outcomes post-PCI, even after stent optimisation using intracoronary imaging. Preprocedural assessment of CAD patterns could identify patients who are likely to exhibit superior immediate haemodynamic outcomes following PCI