971Ethnicity and Cardiovascular Disease in the Australian Population

Focus of Presentation Cardiovascular disease (CVD) risk prediction is recommended for Australians over 45 and Indigenous Australians over 35 years of age. UK evidence for the QRISK tool suggests that including ethnic background as a moderator, improves risk prediction. Australian risk-charts do not account for ethnicity, despite the diversity of the population. Our aim was to compare CVD prevalence among Australian ethnic groups, defined by country of birth and summarized in the following regions: 1.Oceania and Antarctica, 2.North-West-, 3.Southern and Eastern Europe, 4.North Africa and Middle East, 5.South-East-, 6.North-East-, 7.Southern and Central Asia, 8.America and 9.Sub-Saharan Africa. Findings Aggregated data from the Australian Health Survey Core Content–Risk Factors and Health Conditions 2011-12 TableBuilder of Australian Bureau of Statistics were representative of approximately 21.5M Australians according to weights’ analysis; however, age standardisation was impossible. Ischemic CVD prevalence for Australians born in Oceania and Antarctica was approximately 2.6%, North-West Europe 5.1%, Southern and Eastern Europe 6.7%, North Africa and Middle East 4.3%, South-East Asia 1.3%, north-East Asia 0.3%, South and Central Asia 1.2%, America 2.3% and Sub-Saharan Africa 1.2%. In all ethnic sub-groups, males represented 51-83% of individuals with CVD. Conclusions/Implications Country of birth may be used as a proxy of ethnic background for investigating potential socio-cultural CVD risk factors and if accounted for, might increase risk-charts’ performance. Key messages Australians’ ethnic background is associated with CVD prevalence. Including ethnicity in risk-tools might increase accuracy in CVD risk prediction.

Absolute and relative risk prediction in cardiovascular primary prevention with a modified SCORE chart incorporating ceramide-phospholipid risk score and diabetes mellitus

Aims A risk score, CERT2, based on distinct ceramide and phosphatidylcholine species has shown robust performance in predicting cardiovascular risk in secondary prevention. Here, our aim was to investigate the predictive value of CERT2 in primary prevention compared to classical lipid biomarkers and its compatibility with clinical characteristics used in the SCORE risk chart. Methods and Results Four ceramides [Cer(d18:1/16:0), Cer(d18:1/18:0), Cer(d18:1/24:0), Cer(d18:1/24:1))] and three phosphatidylcholines [PC(14:0/22:6), PC(16:0/22:5), PC(16:0/16:0)] were analysed by targeted tandem liquid chromatography-mass spectrometry method in FINRISK 2002, which is a population-based risk factor survey investigating men and women aged 25-74 years. Primary prevention subjects (N = 7,324) were followed up for 10 years for the following outcomes: incident coronary heart disease (CHD), cardiovascular disease (CVD), major adverse cardiovascular event (MACE), stroke and heart failure (HF). Hazard ratios per standard deviation obtained from adjusted Cox proportional hazard models were significant for all these endpoints, and the highest for fatal ones, i.e. fatal CHD [1.45 (95% confidence interval 1.07-1.97)], CVD [1.39 (1.06-1.83)] and MACE [1.39 (1.07-1.80)]. The categorical net reclassification improvement was 0.051 for 10-year risk of incident CVD. Incidence of fatal events was over 10-fold more frequent in the highest CERT2 category compared to the lowest risk category and modified SCORE risk charts, utilizing CERT2 and diabetes mellitus, increased granularity of risk assessment compared to a chart utilizing total cholesterol. Conclusion CERT2 is a significant predictor of incident cardiovascular outcomes and risk charts utilizing this score provide an easy tool to estimate relative and absolute risk for incident CVD.

Validation of the World Health Organization/ International Society of Hypertension (WHO/ISH) cardiovascular risk predictions in Sri Lankans based on findings from a prospective cohort study

Introduction and objectives There are no cardiovascular (CV) risk prediction models for Sri Lankans. Different risk prediction models not validated for Sri Lankans are being used to predict CV risk of Sri Lankans. We validated the WHO/ISH (SEAR-B) risk prediction charts prospectively in a population-based cohort of Sri Lankans. Method We selected 40–64 year-old participants from the Ragama Medical Officer of Health (MOH) area in 2007 by stratified random sampling and followed them up for 10 years. Ten-year risk predictions of a fatal/non-fatal cardiovascular event (CVE) in 2007 were calculated using WHO/ISH (SEAR-B) charts with and without cholesterol. The CVEs that occurred from 2007–2017 were ascertained. Risk predictions in 2007 were validated against observed CVEs in 2017. Results Of 2517 participants, the mean age was 53.7 year (SD: 6.7) and 1132 (45%) were males. Using WHO/ISH chart with cholesterol, the percentages of subjects with a 10-year CV risk <10%, 10–19%, 20%-29%, 30–39%, ≥40% were 80.7%, 9.9%, 3.8%, 2.5% and 3.1%, respectively. 142 non-fatal and 73 fatal CVEs were observed during follow-up. Among the cohort, 9.4% were predicted of having a CV risk ≥20% and 8.6% CVEs were observed in the risk category. CVEs were within the predictions of WHO/ISH charts with and without cholesterol in both high (≥20%) and low(<20%) risk males, but only in low(<20%) risk females. The predictions of WHO/ISH charts, with-and without-cholesterol were in agreement in 81% of subjects (ĸ = 0.429; p<0.001). Conclusions WHO/ISH (SEAR B) risk prediction charts with-and without-cholesterol may be used in Sri Lanka. Risk charts are more predictive in males than in females and for lower-risk categories. The predictions when stratifying into 2 categories, low risk (<20%) and high risk (≥20%), are more appropriate in clinical practice.

Combined use of QRISK3 and SCORE as predictors of carotid plaques in patients with rheumatoid arthritis

Objective Because carotid plaques predict the development of cardiovascular events in RA, we aimed to assess if the combined use of the systematic coronary risk evaluation (SCORE) and the QRISK3 algorithms allows for the identification of RA patients with carotid plaques in a defined population-based RA inception cohort. Methods A set of consecutive RA patients without a history of diabetes, chronic kidney disease or cardiovascular events were studied by carotid US between 2012 and 2019. Modified SCORE (mSCORE) for RA based on the 2015/2016 updated EULAR recommendations and QRISK3 algorithms were retrospectively tested using baseline data obtained at the time of the carotid US assessment. Results A total of 466 (54%) of 865 patients had carotid plaques. Using dichotomized QRISK3 and EULAR mSCORE, 73.2% (95% CI: 68.4.8, 77.6) of patients with QRISK ≥ 10% and EULAR mSCORE &lt; 5% had plaque. In this group, the diagnostic odds ratio was 5.79 (95% CI: 4.14, 8.10). However, if both algorithms were above their thresholds of high cardiovascular risk (QRISK ≥ 10% and EULAR mSCORE ≥ 5%), the sensitivity increased up to 83.3% (95% CI: 72.1, 91.4) and the diagnostic odds ratio up to 10.6 (95% CI: 5.13, 22.0). When the risk charts scales were used as continuous variables, both QRISK3 and EULAR mSCORE were found positively associated with plaque. For each 1% QRISK3 or EULAR mSCORE increase, the probability of having plaques multiplied by 1.14 and 1.22, respectively. However, the effects of both algorithms did not multiply by each other. Conclusions . The combined use of QRISK3 and EULAR mSCORE allows for the identification of most RA patients at high risk of carotid plaques.

Impact of cardiovascular risk factors and genetics on 10-year absolute risk of dementia: risk charts for targeted prevention

Aims Dementia is a major global challenge for health and social care in aging populations. A third of all dementia may be preventable due to cardiovascular risk factors. Intensive multi-domain intervention trials targeting primarily cardiovascular risk factors show improved cognitive function in people at risk. Such interventions will, however, be expensive to implement in all individuals at risk and will represent unrealistic economic tasks for most societies. Therefore, a risk score identifying high-risk individuals is warranted. Methods and results In 61 664 individuals from two prospective cohorts of the Danish general population, we generated 10-year absolute risk scores for all-cause dementia from cardiovascular risk factors and genetics. In both sexes, 10-year absolute risk of all-cause dementia increased with increasing age, number of apolipoprotein E (APOE) ɛ4 alleles, number of genome-wide association studies (GWAS) risk alleles, and cardiovascular risk factors. The highest 10-year absolute risks of all-cause dementia seen in smoking women with diabetes, low education, APOE ɛ44 genotype, and 22–31 GWAS risk alleles were 6%, 23%, 48%, and 66% in those aged 50–59, 60–69, 70–79, and 80–100, respectively. Corresponding values for men were 5%, 19%, 42%, and 60%, respectively. Conclusion Ten-year absolute risk of all-cause dementia increased with age, APOE ɛ4 alleles, GWAS risk alleles, diabetes, low education, and smoking in both women and men. Ten-year absolute risk charts for dementia will facilitate identification of high-risk individuals, those who likely will benefit the most from an early intervention against cardiovascular risk factors.

Fasting and non-fasting lipid profile for cardiovascular risk assessments using China ASCVD risk estimator and Europe SCORE risk charts in Chinese participants

Background Previous studies have shown that non-fasting lipids have similar values in cardiovascular risk estimation as fasting, but it is not clear whether this could also be applicable to Chinese participants.Methods A total of 127 (76 men, 51 women) participants without atherosclerotic cardiovascular diseases (ASCVD) were enrolled in the study. Serum levels of blood lipids were monitored at 0 h, 2 h and 4 h after a daily breakfast. Ten-year cardiovascular disease (CVD) risk was estimated with China ASCVD risk estimator and Europe SCORE risk charts. Kappa statistic was used to determine agreement among estimators.Results there was substantial agreement between China ASCVD risk estimator based on fasting and non-fasting lipid profiles (Kappa = 0.731 or 0.718, P < 0.001), but poorly agreement between China ASCVD risk estimator and SCORE low- or high-risk chart (Kappa = 0.339 or 0.300, P < 0.001).Conclusions Promoting use of non-fasting blood lipids in diagnosis, evaluation, and prediction of CVD are feasible. Furthermore, non-fasting blood lipids could be used in China ASCVD risk estimator to evaluate assess 10-year risk of ASCVD among Chinese general participants.