Cardiovascular Disease Risk Research Articles

LE8 score in relation to cardiovascular disease and mortality in individuals with diabetes

Abstract Background Evidence regarding the potential health effects of Life’s Essential 8 (LE8) score among individuals with type 2 diabetes (T2D) is limited. Purpose We aimed to examine the associations of LE8 score with risk of cardiovascular disease (CVD) and mortality, among individuals with T2D. Methods We prospectively followed 19,915 Chinese participants with T2D at baseline or diagnosed during follow-up (Kailuan Study: 2006-2020), who were free of CVD at diagnosis of diabetes. Diet, lifestyle, and health conditions were repeatedly assessed every 2 years. The LE8 score (range, 0-100), was calculated based on 8 components: diet quality, physical activity, smoking status, sleep health, BMI, blood lipids, blood glucose, and blood pressure. We used time-varying cox models to model the associations. Results During a median follow-up of 11.5 years in participants with T2D, there were 3,295 incident CVD cases and 3,123 deaths. Higher LE8 score was associated with lower risk of CVD incidence and total mortality among participants with diabetes. The multivariate-adjusted hazard ratios and 95%CIs for the highest quintile of LE8 score compared with the lowest quintile were 0.56 (0.53, 0.59) for CVD incidence, 0.57 (0.53, 0.62) for heart disease incidence, 0.53 (0.49, 0.57) for stroke incidence, and 0.73 (0.69, 0.78) for total mortality (all p trend<0.001). Furthermore, compared with participants with stable or decreased LE8 score after diabetes diagnosis, those with increased LE8 score had 17%-42% lower risk of CVD incidence, heart disease incidence, stroke incidence, and total mortality. These associations persisted in subgroup analysis stratified by age, sex, BMI, smoking status, alcohol intake, family history of diabetes and CVD, and follow-up time. Conclusions Higher LE8 score was associated with a substantially lower risk of CVD incidence and total mortality among adults with T2D. These findings further support the tremendous benefit of adhering to a high CVH, defined as the LE8 in reducing the subsequent burden of cardiovascular complications and improving overall health in individuals with T2D.Main TableMain Figure

Utility of the triglycerides/HDL cholesterol ratio in older adult patients in Colombia

Abstract Introduction Alterations in lipid metabolism are responsible for atherogenesis and an increased risk of atherosclerotic cardiovascular disease. The triglycerides to high-density lipoprotein cholesterol ratio (TG/HDL-C) is used to assess the risk of cardiovascular diseases; however, it has not been evaluated in older adults. The aim of the present study is to evaluate the TG/HDL-C ratio in elderly patients and analyze its correlation and discriminatory capacity with cardiovascular risk factors according to data from the SABE Colombia survey. Purpose Describe the sociodemographic characteristics, cardiovascular history, lifestyle, and cardiovascular risk score in the older adult population included in the SABE Colombia Study.Describes the distribution of triglyceride levels, cholesterol, and the TAG-HDL ratio in the older adult population included in the SABE Colombia Study. Evaluate the relationship between the TAG/HDL Cholesterol Index and cardiovascular risk factors such as hypertension, prediabetes, type 2 diabetes mellitus, cardiovascular disease, cerebrovascular disease Determine if there is a correlation and the degree of correlation between the TAG/HDL Cholesterol ratio and variables related to higher cardiovascular risk and stablish cutoff points of the triglyceride to HDL cholesterol ratio as indicators of the onset of risk factors Materials and Methods Cross-sectional study in adults aged 60 years and older included in the national SABE Colombia survey (National Survey of Health, Well-being, and Ageing conducted in Colombia in 2015), which included 244 municipalities from all departments of the country. A correlation test was performed to assess the presence and degree of correlation between the TAG/HDL index and cardiovascular risk factors, and ROC curve analysis was conducted to evaluate the performance of the TAG/HDL index in identifying risk factors. Results A total of 23,694 patients with the necessary information for the study were included. The median age was 69 years, 57.3% were women, and 34.3% were of white race. 23.5% had hypertension, and 16.4% had diabetes mellitus. 13.4% had a history of cardiovascular disease, and 2.5% had cerebrovascular disease. While the specific correlation between the index and different cardiovascular risk factors is generally low to moderate, good discriminatory capacity was found for diabetes and metabolic syndrome with the following values: diabetes, with an area under the curve (AUC) of 0.871 and a cut-off point of 9.17; and for metabolic syndrome, the AUC was 0.840, with a cut-off point of 8.81. Conclusions Our findings show that the TG/HDL ratio has intermediate correlation for different cardiovascular risk factors; however, it has excellent predictive ability for the presence of diabetes and metabolic syndrome. These findings are very useful in the clinical evaluation, screening, and detection of cardiovascular risk factors in the population aged 60 years and older in Colombia.Scatter plots of TAG/HDL ratio comparedROC curves for diabetes and metabolic s

Hypnotic use and the risk of cardiovascular diseases in insomnia patients

Abstract Background Insomnia, commonly treated with hypnotic agents, is an independent risk factor of cardiovascular diseases. Previous research demonstrated the detrimental effect of hypnotics on the prognosis of cardiovascular patients. Purpose We aimed to examine the association between hypnotic agents and cardiovascular outcomes in general individuals with insomnia. Methods In a propensity score matched cohort of UK Biobank (UKB) participants with insomnia, Cox proportional hazard model was used to estimate the association between regular use of hypnotic agents and predetermined cardiovascular outcomes including incident coronary heart diseases (CHD), heart failure (HF), stroke, and cardiovascular death. Inverse probability of treatment weighting and competing risk models were further performed during sensitivity analysis. Drug-target Mendelian randomization (MR) analyses were employed for further evaluation of hypnotics-related genes and cardiovascular disease association. The genome-wide association data of CHD, HF, and stroke were there large-scale genome-wide association analyses. Tissue-specified expression quantitative trait loci (eQTL) data was derived from BrainSeq phase II. Results During a median follow-up of 14.3 years, the matched cohort documented a total of 1,019 CHD cases, 406 HF cases, 285 stroke cases, and 197 cardiovascular deaths. No significant association was detected between Z-meds and CHD, stroke, and cardiovascular mortality. Benzodiazepine use was significantly associated with the increased risk of CHD, HF, and cardiovascular mortality (Figure 1). The inverse probability of treatment weighting and competing risk models didn’t alter the above associations. Moreover, drug-target MR analyses corroborated the safety of Z-meds in the general population regarding cardiovascular health. However, GABRG1—a drug target for benzodiazepines—was associated with heightened risks for heart failure, and ischemic stroke (Figure 2). Conclusions Our findings suggested the heterogeneous associations between different categories of hypnotics and incident cardiovascular events in individuals with insomnia. Z-meds are safe regarding the risk of cardiovascular outcomes in the UKB population with insomnia.Figure 1Figure 2

Independent and joint associations of urinary potassium excretion with cardiovascular death: a national population-based cohort study

Abstract Background Elevated potassium excretion is associated with lower blood pressure, as well as reduced risks of cardiovascular disease (CVD) death. However, the impact of varied sodium levels on this association remains a topic of debate, and the mediators of this association besides blood pressure remain uncertain. Purpose To examine the joint association of potassium and sodium with CVD mortality risk, and to identify potential mediating factors of this association. Methods Based on the ChinaHEART (China Health Evaluation And risk Reduction through nationwide Teamwork) project, participants aged 35-75 from 239 sites across all 31 provinces in the mainland of China were recruited from November 2014 to December 2022. We collected spot urine samples from participants and estimated 24-hour sodium and potassium excretion using the Kawasaki formula. Death records were captured through data linkage with the National Mortality Surveillance System and Vital Registration. Multiple regressions were used to analyze the association between potassium excretion and CVD death, as well as to examine the addictive interaction of potassium and sodium. Results This study included 270,991 participants with a mean age of 55.8±9.8 years, and 60.5% of them were female. The mean potassium excretion was 54.36±12.58 mmol/d , which was higher in males and people living in the north. Findings revealed a positive correlation between low urinary potassium levels and CVD death , and the lowest adjusted hazard rate for CVD mortality was 0.65 (95% CI: 0.58-0.73) in the group with the highest potassium excretion (i.e. ≥64.27 mmol/d) compared with the reference group (<43.79 mmol/d), after adjusting for sociodemographic characteristics, medical histories, and lifestyles. Age modified the association between potassium excretion and risk of CVD death (P for interaction=0.031). In addition to systolic blood pressure (16.6%), heart rate (2.2%) also served as the significant mediator between urinary potassium excretion and CVD death. The relative excess risk of interaction (RERI) of lower potassium excretion and lower sodium was significantly positive (RERI=0.22, 95% CI: 0.02-0.42), which implied the synergy effect. Conclusion Potassium intake in the Chinese population is evidently lower than the guideline recommendations, and increasing potassium intake, especially in the population aged <65 years, may reduce the risk and burden of cardiovascular and other diseases. Moreover, when sodium intake is insufficient, supplementation with both sodium and potassium salt can achieve greater health benefits.Graphic abstract

Diabetes mellitus and adverse clinical events in patients with atrial fibrillation: implications of insulin treatment: a report from the GLORIA-AF Registry Phase III

Abstract Background Atrial Fibrillation (AF) and diabetes mellitus (DM) are both associated with adverse clinical events, but the associations has not been fully elucidated, especially in relation to insulin use. Purpose To analyze the associations between DM and the risk of clinical adverse events in patients with AF, and second, explore the impact of insulin treatment in these patients. Methods We studied patients with AF from the prospective Global Registry on Long-Term Oral Anti-Thrombotic Treatment in Patients with Atrial Fibrillation (GLORIA-AF) registry with 3-years follow-up. Clinical events included all-cause death, major bleeding, myocardial infarction (MI), stroke, thromboembolism (TE), and major adverse cardiovascular events (MACE). MACE was defined as a composite of stroke, MI and major bleeding. Kaplan-Meier curves were used to estimate the cumulative incidence of clinical events. Multivariable cox regression models with subgroups were used to estimate the association between DM and the risk of mortality and clinical events. Results A total of 15,861 AF patients were included (mean age 70.00 ± 10,21 years old; 55% male, 20% Asia), of which 3,666 had DM (mean age 70.04 ± 9.54 years old; 59% male, 21% Asia). Kaplan-Meier curves showed that AF patients with DM had higher cumulative hazard of all outcomes, including all-cause death (OR: 1.56, 95%CI: 1.38-1.77), CVD (OR: 1.72, 95%CI: 1.44-2.06), major bleeding (OR: 1.4, 95%CI: 1.17-1.67), stroke (OR: 1.29, 95%CI: 1.04-1.61), TE (OR: 1.26, 95%CI:1.02-1.56), MI (OR: 1.88, 95%CI: 1.48-2.39) and MACE (OR: 1.61, 95%CI: 1.41-1.84). After adjustment by prior disease and drugs, the outcomes of stroke (OR: 1.19, 95%CI: 0.95-1.49) and TE (OR: 1.22, 95%CI: 0.98-1.52) showed not significant. Subgroup analysis found that increased risks of stroke were found in female (OR: 1.43, 95%CI: 1.03-1.98, Pinteraction = 0.062) and non-Asian patients (OR: 1.39, 95%CI: 1.06-1.82, Pinteraction = 0.175) with DM. For all cause death, subgroup results were similar with overall patients. In addition, insulin use increased the risk of all cause death (OR: 1.82, 95%CI: 1.45-2.29), CVD (OR: 1.70, 95%CI: 1.22-2.37), major bleeding (OR: 1.54, 95%CI: 1.08-2.18), MI (OR: 1.72, 95%CI: 1.12-2.64), MACE (OR: 1.65, 95%CI: 1.28-2.11) in patients with AF and DM. Multivariable model showed similar result. Conclusions DM was independently associated with higher risk of all-cause death, CVD, MI, major bleeding, and MACE in patients with AF. Insulin use was associated with higher risk of all-cause death, CVD, MI, major bleeding, and MACE in patients with AF and DM.Figure 1Figure 2

Interactive effects of outdoor fine particulate matter and metabolic, behavioural, and psychosocial risk factors on cardiovascular disease: analysis of the PURE-China cohort study

Abstract Background Long-term PM2.5 exposure has been associated with an elevated risk of cardiovascular disease (CVD) and its associated risk factors.[1–4] There is a paucity of studies investigating the interactive effects of PM2.5 exposure and a comprehensive list of risk factors including metabolic, behavioural, and psychosocial risk factors on CVD risk.[5] Purpose This study aims to examine the interactive effects of PM2.5 exposure and metabolic, behavioural, and psychosocial risk factors on incident CVD. Methods The Prospective Urban Rural Epidemiology (PURE)-China cohort study is a population-based cohort study recruiting participants aged 35–70 years from 115 communities in 12 provinces of China between 2005 and 2009, and followed up until August 31, 2021.[6] Participants’ metabolic, behavioural, and psychosocial risk factor information was recorded. PM2.5 concentrations were extracted from a 1x1 km2 global model.[7,8] For this analysis, we included participants aged 35–70 years at baseline without a history of CVD, with at least one follow-up visit. The primary outcome was a composite of major cardiovascular events (CVD deaths, myocardial infarction, stroke, and heart failure). Additive interaction was measured by relative excess risk due to interaction (RERI), the proportion of disease attributable to interaction (AP), and the synergy index (SI).[9,10] To comply with the additive interaction method, we classified concentrations of PM2.5 into low and high levels by the median of 3-year average PM2.5 concentration (45.7 μg/m3, IQR: 33.7-74). Cox proportional hazard models were used to assess the associations of metabolic, behavioural, and psychosocial risk factors on incident CVD by PM2.5 concentrations. Results The PURE-China study recruited 47 931 participants, of which 39 329 are eligible for this analysis. During the median follow-up period of 11.9 years (IQR: 9.6-12.6), 1462 and 2155 major CVD events had occurred in the low and high PM2.5 group respectively. There was a synergistic interaction between PM2.5 and the systolic blood pressure (SBP) for CVD: RERI: 0.363, 95% CI: 0.196-0.531; AP: 0.098, 95% CI: 0.081-0.115; SI: 1.155, 95% CI: 1.132-1.177; high LDL cholesterol: RERI: 0.219, 0.003-0.436; AP: 0.135, 0.008-0.263; SI: 1.549, 0.947-2.533. A significant synergistic interaction was also identified between PM2.5 and household air pollution (RERI: 0.457, 0.292-0.622; AP: 0.277, 0.184-0.37; SI: 3.362, 1.409-8.019). Interactions between PM2.5 and low grip strength on CVD were significantly synergistic, but antagonistic between PM2.5 and low physical activity (RERI: -0.248, -0.485--0.012; AP: -0.174, -0.349-0.001; SI: 0.633, 0.412-0.971). Conclusion Addictive interaction was between PM2.5 and SBP, high LDL cholesterol, household air pollution, low grip strength and low physical activity on incident CVD, indicating the benefit of coordinated control strategies for metabolic, physical, and environmental risk factors for the prevention of CVD.

Using deep learning to detect atherosclerotic plaques on carotid ultrasound images in the UK Biobank

Abstract Background Atherosclerosis is the main underlying cause of cardiovascular disease (CVD). Existing CVD risk assessment tools do not consider the burden of subclinical atherosclerosis. The presence of carotid plaques on carotid ultrasound is a well-known marker of subclinical atherosclerosis. The accumulation of population-scale data on the presence of atherosclerotic plaques, along with deep phenotyping, can allow not only to address the effectiveness of carotid ultrasound in routine clinical practice, but to shed light on the biology of atherosclerosis development. Purpose To develop an effective deep learning model for plaque detection in carotid ultrasound images in the UK Biobank. Methods We used 680 carotid ultrasound images with manually annotated plaques to train a deep learning model employing the YOLOv8 architecture. Different augmentation techniques were used to increase the generalizability of the model. The developed model was applied to automatically detect plaques in raw ultrasound images from 19,507 UK Biobank participants. Logistic and Cox regression were used to explore the associations of plaque presence and number as predicted by the model with conventional CVD risk factors and the risk of future CVD events over follow-up. To explore the genetic architecture of subclinical atherosclerosis, we conducted a genome-wide association study (GWAS) on plaque presence, followed by meta-analysis with data from the CHARGE Consortium. Results Our plaque detection model achieved high classification metrics of accuracy, sensitivity, and specificity (89.3%, 89.5%, and 89.2%, respectively) and detected atherosclerotic plaques in 44% of UK Biobank participants. As expected, plaques were more common among men than women and their prevalence increased linearly with age. Both plaque presence and number of plaques were correlated with conventional CVD risk factors including diabetes, hypertension, and hyperlipidemia, and showed strong associations with future risk of incident CVD events (Hazard Ratio for plaque presence: 1.48 [95%CI: 1.21-1.82], for 2 plaques or more: 1.65, [95% CI: 1.28-2.13]). Incorporating plaque-derived phenotypes minimally altered the C-index of the time-to-event model. GWAS meta-analysis of carotid plaque presence revealed 5 previously known loci, as well as a significant locus including the LPA gene that had not previously been associated with carotid plaque. Conclusion We have developed and implemented an efficient plaque detection model to data from the UK Biobank, which holds significant promise for studying atherosclerosis at a population-wide scale through integration with multiomics data and electronic health records.

Machine learning and traditional analysis of the interaction between cardiovascular diseases and hematological malignancies

Abstract Background Cardiovascular diseases and clonal hematopoiesis of indetermine potential (CHIP), the premalignant state of hematological cancers, exhibit reciprocal interactions. While the presence of CHIP confer a risk for heart failure, it is unclear if cardiovascular diseases are associated with elevated risk hematological cancers. Purpose To determine the association between cardiovascular diseases (CVD) and cardiovascular risk, and hematological cancer. Methods We evaluated 27,231 adults, free of CVD and cancer, who participated in preventive healthcare program between 2000-2018. Each participant underwent a complete physical evaluation, blood test and exercise stress test at baseline. CVD was defines as ischemic heart disease, stroke, atrial fibrillation or hypertension. Then, we used machine learning and traditional survival analysis to evaluate the association between CVD and hematological cancer. For machine learning, we used the random forest method using Curat package in r, and incorporated all continuous variables gathered into the model (70% training, 30% test). For survival analysis, we first matches each CVD patient to a control patient by propensity scores to balance for age, sex, smoking, diabeles mellitus, renal function, body mass index and length of follow-up. Then, we compared the CVD and non-CVD patients using cox proportional hazard regression. Results Using machine learning, we found that the strongest predictors for hematological cancer in our cohort are low eGFR, age, high atherosclerosis cardiovascular disease score (ASCVD) and BMI. Of note, systolic and diastolic blood pressure were also strong predictors of hematological cancer (Figure A). Then, we matched 5500 CVD patients to controls with median follow-up of 9.2 years (Interquartile range 5-15 years). During follow-up, 1380 developed cancer. Of them, 186 developed hematological cancer. We used cox proportional hazard regression and Kaplan Mayer method to determine the risk and hazard ratio of developing hematological cancer (Figure B-C). Compared with subjected without CVD, patients with CVD were 91% more likely to develop cancer during follow-up, and 62% more likely to develop hematological cancer (Figure C, HR=1.61. 95%CI 1.21-2.16). Moreover, the 10-year risk to develop hematological cancer was 1.9% for patients with CVD and 1.0% for individuals without CVD (Figure D). Notably, the increased incidence of hematological cancers included 38% increase in cases of leukemia but only 11% increase in cases of lymphoma. Conclusions Using machine learning and traditional analysis we show that CVD risk and CVD were associated with increased incidence of hematological cancer. Understanding this relationship could lead to advances in cardiovascular and cancer treatment and could ultimately help to improve patient outcomes.

LDL-C target attainment and statin use in patients with ASCVD, familial hypercholesterolaemia, and those otherwise at moderate/high-risk of ASCVD in australian general practice (SCOPE-GP)

Abstract Background The proportion of Australian general practice patients not attaining low-density lipoprotein cholesterol (LDL-C) goals is not well described. The SCOPE-GP study evaluated duration of LDL-C exceeding treatment goals, statin use and discontinuation rates in patients with atherosclerotic cardiovascular disease (ASCVD), without ASCVD events but at moderate/high-risk, and familial hypercholesterolemia (FH). Methods This population-based retrospective cohort study used de-identified medical records of adult patients captured in the IQVIA GP-EMR database. Patients were indexed at the earliest date of ASCVD, FH, or hyperlipidemia diagnosis from January 1, 2010 to June 30, 2022, with a variable follow-up period from index to June 30, 2022. Ascertainment of study cohort was based on the 2021 ESC/EAS guidelines and Framingham Risk Equation. LDL-C test result levels were extracted per patient, summarised and analysed. Patients were stratified based on their test results at latest results/closest to censor date. Average time above target levels is the proportion of number of days above LDL-C target levels over total number of follow-up days for each patient. A Poisson distribution was fitted to estimate 95% confidence interval. Lipid lowering therapies (LLT) were stratified by (ASCVD, FH and moderate/high risk of CVD) at last visit/censor date. Combination of LLT were defined as prescriptions for fixed dose combinations or ≥2 separate scripts of LLT from different classes within 180 days from last visit/censor date (look back period). Discontinuation is defined as no statins were prescribed again after the last script for 270 days or more, limited to the first occurrence. Results The average time with LDL-C levels above target was 1077.5 days in ASCVD patients (n=2,688), 938.6 days in moderate-risk ASCVD (n=37,003), 980.9 days in high-risk ASCVD (n=85,199), and 900.8 days in FH (n=279). The proportion of days above target level for all four cohorts is described in Figure 1. Among 107,552 patients with recorded LDL-C levels ≥1.8mmol/L at their last visit/censor date, 30.9% were on statin monotherapy and 1.0% were on statin+ezetimibe. Statin use was highest in ASCVD patients (65.4%), followed by FH (49.5%), high risk (40.0%) and moderate risk subjects (29.5%) (Table 1). Statin discontinuation rates were 60.3%, 76.3, 66.1%, and 65.8% in these groups, respectively. The predominant reason for statin discontinuation was non-specific adverse drug reactions (12.2% ASCVD, 11.7% moderate-risk, 13.2% high-risk and 17.9% FH). The proportion of subjects contraindicated to statins was highest in moderate risk subjects (0.05%). Conclusions Prolonged periods of elevated LDL-C and high statin discontinuation rates were prevalent among at-risk individuals in Australian primary care. This underscores a significant ASCVD burden that could be prevented with more active lipid management.

Innovative Approaches for Personalized Cardiovascular Prevention: the INNOPREV multicentric trial

Abstract Background Cardiovascular diseases (CVD) represent a major global health concern, requiring innovative primary prevention strategies. Personalized prevention, through the use of digital technologies and genetic risk scores (PRS), holds promise but requires further investigation to assess clinical efficacy. Consequently, the INNOPREV trial aims to investigate the efficacy of PRS and/or digital technologies in the uptake of CV preventive behaviors uptakes. Methods The INNOPREV trial is a multicenter randomized controlled trial conducted in Italy across three hospital centers in Rome, Catania, and Palermo. It aims to recruit 1020 participants aged 40-69 with a high 10-year CVD risk. Participants are allocated to traditional CVD risk assessment, or genetic testing, or digital interventions, or a combination of both. The study involves comprehensive CV risk assessments at baseline and follow-up visits at one, five, and twelve months. Data analysis will utilize mixed-effects models to analyze longitudinally collected data and explore potential moderators and mediators of behavior change. Results Preliminary results indicate good progress in recruitment, which currently stands at 250 participants (25% of expected). Recruited females have a mean age of 59 ± 6 years, while males have a mean age of 58 ± 6 years. Currently, PRS analyses indicate that 77% of participants have intermediate scores, and 23% have low scores. Follow-up will be essential to evaluate the efficacy of the proposed interventions. Conclusions We expect that the INNOPREV trial will provide evidence towards integration of innovative approaches based on PRS and digital devices, in the traditional preventive approaches for CVDs. Expectations are high based on the limited effectiveness of the current approaches in CV risk reduction based on lifestyle advice. Key messages • INNOPREV trial examines PRS and digital technology for CVD prevention, aiming to enhance preventive efficacy. Initial findings suggest promising potential for innovative CVD prevention strategies. • The INNOPREV trial aims to investigate the efficacy of personalized prevention strategies, including PRS and digital technologies, in improving cardiovascular preventive behaviors.

Protein quantitative trait loci identifies genetic biomarkers of proteins associated with measures of myocardial fibrosis in new-onset, treatment naive rheumatoid arthritis

Abstract Introduction The excess risk of cardiovascular disease (CVD) in patients with rheumatoid arthritis (RA) compared to the general population is attributed to chronic inflammation. Identifying the underlying mechanisms and shared inflammatory pathways more precisely would enable tailored treatment. Purpose To identify genetic variants associated with the cardio-metabolic-inflammatory proteomic signature in patients with early, treatment-naïve RA and low CVD risk. Methods The Coronary Artery Disease Evaluation in RA (CADERA) study was a bolt-on to a RCT of patients with early, treatment-naïve RA and low CVD risk profile (maximum of 1 traditional CVD risk factor and no diabetes mellitus). Normalised expression of 334 proteins from 75 CADERA patients who underwent cardiovascular magnetic resonance imaging (CMR) was measured using the Olink Proximity Extension Immunoassay across Inflammation, Cardiovascular II, III and Cardiometabolic panels. Genome-wide single nucleotide polymorphism (SNP) data were generated using the Illumina Global Screening Array and was imputed and checked for data quality using standard approaches. Proteins associated with CMR parameters were identified using Bayesian mixed effects linear regression. Protein quantitative trait locus (pQTL) analysis was then performed using linear regression models adjusted for age, gender, and systolic blood pressure. Cis-pQTLs were defined as SNPs within 1Mb of the protein-encoding gene, and significance threshold was set at 1e-5. Due to sample size, trans-pQTLs were not considered in this analysis. Linkage disequilibrium (LD) clumping was performed using PLINK software to identify index SNPs defined as the most significant variant in LD (r2 <0.5) within a region of +/- 250Kb. Results Following quality control 318 proteins and 5,971,781 SNPs were available for analysis in 75 CADERA patients. The median age was 51 years [inter-quartile range (IQR) 40 - 61] with 52/75 (69%) females, 40/75 (53%) current/ex-smokers, and median body mass index (BMI) 26.4kg/m2 (IQR 23.3 - 28). Participants had a median RA symptom duration of 21.9 weeks (IQR 14.4 - 32.7). Only 8/75 (10%) reported a history of hypertension, hypercholesteroaemia or family history of CVD. 54 out of 318 proteins were associated with CMR measures of myocardial fibrosis and/or vascular stiffness. 460 cis-pQTLs were identified for 20 out of the 318 proteins. LD clumping revealed 40 cis-pQTLs independently associated with these 20 proteins. Of these, NOTCH3 (rs34763630) was positively associated with extracellular volume, and SELPLG (rs7980427) was negatively associated with late gadolinium enhancement as detected on CMR (table 1). No other proteins with genetic support were associated with CMR measures. Conclusion This study for the first time, implicates genetic markers associated with two proteins as putative candidate biomarkers of CMR-identified myocardial fibrosis in new-onset RA that now warrant validation in an independent cohort.

Linking antibody against apolipoprotein A-1 to metabolic dysfunction-associated steatohepatitis in mice

Abstract Background Metabolic dysfunction-associated fatty liver disease (MASLD) is a common liver condition associated with increased cardiovascular disease (CVD) risk. Cytokeratin 18 (CK-18) is indicative of liver injury and used as a surrogate biomarker covering MASLD to cirrhosis phenotypes. Autoantibodies against apolipoprotein A-1 (AAA-1) are known CVD risk factors inducing MASLD in vitro, but their role in modulating steatohepatitis and fibrosis in vivo is still elusive. We investigated AAA-1's contribution to systemic low-grade inflammation, liver steatosis, and fibrosis using a MASLD mouse model and a validated passive immunization protocol (PIP). Methods 10 weeks-old male C57BL/6J mice were fed a choline-deficient, L-amino acid-defined, high-fat diet (CDAHFD) and immunized with AAA-1 (200ug) or control antibodies for ten days. At sacrifice, plasma samples were collected, and CK-18 levels, and proinflammatory cytokines were measured using the Mesoscale Discovery platform. Hematoxylin and Eosin and Sirius Red Fast Green staining were used to reveal liver steatosis and fibrosis, respectively. RNA were extracted from mouse liver samples and mRNA were then analyzed using a commercial fibrosis-specific genes panel (nCounter Human Fibrosis V2 Panel) and the nCounter Analysis System. Results Compared to control IgG recipients, CDAHFD mice injected with AAA-1 exhibited significantly elevated plasma levels of CK-18 (5.3 vs 2.1, p=0.031), IL-6 (13 vs 6.9, p=0.035), IL-10 (27.3 vs 9.8, p=0.007) and TNF-α (32.1 vs 24.2, p=0.032), and liver steatosis (93.4% vs 73.8%, p=0.007). Nanostring technology experiments revealed upregulation of several pro-fibrotic m-RNAs in liver tissue from AAA-1 immunized mice compared to the IgG immunized control group. These included Serum Amyloid A (Fold Change (FC) AAA-1 vs IgG : 2.5, p=0.02) , G-protein coupled receptors 65 (FC: 2.7, p=0.01), Periostin (FC: 2.6, p=0.001), Phospholipid transfer protein (FC: 2.2, p=0.0004), Vascular Cell Adhesion Molecule 1 (FC: 2.5, p=0.02) and Angiopoietin-like 4 (FC: 2.8, p=0.01). Histologically, the amount of liver fibrosis remained unaffected, probably due to the short time of the study. Conclusions Short AAA-1 PIP induced enhanced liver steatosis and inflammation accompanied by an elevation of the expression of several pro-fibrotic genes in CDAHFD mice, suggesting that AAA-1 may contribute to the transition from MASLD to MASH. Knowing whether increased exposure time to AAA-1 could lead to end stage disease (including cirrhosis and HCC), and if this could apply to humans as well warrant further investigations.

Sleep characteristics in relation to cardiovascular disease incidence and mortality in individuals with diabetes

Abstract Background/Introduction Evidence regarding the potential health effects of sleep characteristics among individuals with type 2 diabetes (T2D) is limited. Purpose We aimed to examine sleep characteristics in relation to subsequent risk of cardiovascular disease (CVD), including coronary heart disease (CHD), and stroke, and all-cause and cause-specific mortality among individuals with T2D. Methods We prospectively followed 21,902 men and women with T2D at baseline or diagnosed during follow-up (Nurses' Health Study: 1986-2018, Health Professionals Follow-Up Study: 1986-2018). Sleep characteristics, including sleep duration, snoring, sleep apnea, and sleep quality, were repeatedly assessed using self-reported questionnaires at baseline and follow-up. Associations of sleep characteristics with CVD risk and mortality were assessed using Cox proportional hazards models with adjustments for demographic, dietary and lifestyle factors, and medical history. Results During 170,355 and 196,458 person-years of follow-up in participants with T2D, there were 2,486 incident CVD events and 3,922 deaths, respectively. Compared with sleeping for 7-8 h/day, the multivariable-adjusted hazard ratios (HRs) of sleeping for ≤5 h/day were 1.21 (1.02, 1.45) for CVD incidence, 1.24 (1.20, 1.51) for CHD incidence, 1.40 (1.24, 1.58) for total mortality, 1.52 (1.20, 1.92) for CVD mortality, and 1.27 (1.01, 1.61) for other non-CVD and non-cancer mortality, while the HRs of ≥10 h/day were 1.42 (1.21, 1.66) for total mortality, and 1.63 (1.20, 2.10) for other non-CVD and non-cancer mortality. Furthermore, compared with participants without habitual snoring, those with habitual snoring had a 21%, 24%, 18%, and 33% higher risk for CVD incidence, CHD incidence, CVD mortality, and total mortality, respectively. Compared with participants without diagnosed sleep apnea, those with sleep apnea had a 27%-58% higher risk for CVD incidence, CVD mortality, and total mortality. In addition, lower habitual sleep quality, including sleep difficulties and restless sleep, was associated with a substantially higher risk of CVD, CHD, or CVD mortality. No associations were observed between sleep characteristics with risk of stroke and cancer mortality in individuals with T2D. Conclusions Short and long sleep durations as well as habitual snoring, sleep apnea, and lower sleep quality were independently associated with higher risks of CVD incidence and mortality, particularly CVD mortality in individuals with T2D.

ASCVD risk scores versus a novel cancer-specific Machine Learning-based calculator among patients with breast, colorectal, lung or prostate cancer

Abstract Background Patients with cancer have up to a 3-fold higher risk for cardiovascular disease (CVD) than the general population. Consequently, traditional risk scores developed to predict CVD in the general population (i.e., Pooled Cohort Equations (PCE), Predicting Risk of cardiovascular disease EVENTs [PREVENT]) may provide less accurate risk prediction for this population. Purpose Compare cancer-specific Machine Learning (ML)-based score to PCE and PREVENT to predict 10-year CVD risk in patients with breast cancer (BC), colorectal cancer (CRC), lung cancer (LC), or prostate cancer (PC). Methods Patients aged ≥18 years, diagnosed with BC, CRC, LC, or PC between 2005-2012 at a large hybrid academic-community practice in Northeast Ohio, United States, were included. An ML Extreme Gradient Boosting (XGBoost) algorithm, adapted for survival modeling, was developed using a training subset of the cohort (55% train + 20% test) and ranked 40 to 50 covariates (including social determinants of health, cancer treatment) for predicting 10-year CVD risk for each cancer type using SHAP (SHapley Additive exPlanations) values. The top 10 ML predictors were utilized to create a predictive equation using logistic regression models. This equation was then tested in the cohort validation subset (25%) and subsequently compared to the PCE and PREVENT (both simple and enhanced versions) using the area under the curve (AUC) of the time-dependent receiver operating characteristic curve. The CVD events were identified using ICD codes corresponding to Acute Coronary Syndrome, Ischemic Stroke, and Heart Failure. CVD risk was assessed through Kaplan-Meier. Results We included 10,240 patients (Table 1). The actual 10-year CVD events were: BC 21% (95% CI 19-23), CRC 10% (95% CI 8-12), LC 27% (95% CI 24-30), and PC 20% (95% CI 17-23). The ACC/AHA PCE predicted mean 10-year CVD risks of 16% (95% CI 15-18) for BC, 19% (95% CI 17-21) for CRC, 28% (95% CI 25-32) for LC, and 19% (95% CI 19-20) for PC, with corresponding AUCs of 0.75, 0.65, 0.76, and 0.61, respectively. The PREVENT simple version predicted mean 10-year CVD risks of 13% (95% CI 13-14) for BC, 13% (95% CI 12-13) for CRC, 15% (95% CI 14-15) for LC, and 16% (95% CI 12-19) for PC, with AUCs of 0.55, 0.55, 0.55, and 0.53, respectively. The PREVENT enhanced equation predicted mean 10-year CVD risks of 17% (95% CI 17-18) for BC, 15% (95% CI 14-15) for CRC, 15% (95% CI 15-16) for LC, and 17% (95% 16-19) for PC, with AUCs of 0.75, 0.62, 0.79, and 0.63, respectively. The predictive equation derived from the top 10 ML predictors (Table 2) achieved AUCs of 0.84 for BC, 0.76 for CRC, 0.83 for LC, and 0.71 for PC. Conclusion(s) Conventional CVD equations inadequately assess the risk in patients with BC, CRC, LC, or PC, often resulting in underestimation or overestimation. Cancer-specific ML-derived equations show good performance and emphasize the importance of integrating cancer-related covariates for precise prediction.Table 1Table 2

Cardiovascular disease burden and risk factor management in cancer survivors: insights from a large-scale East London cohort

Abstract Introduction Improvements in cancer survival have led to an urgent need to address long-term health issues among survivors, notably increased risk of cardiovascular disease (CVD). Shared risk factors may underpin at least part of this excess risk. Aims To investigate differences in cardiovascular risk profile between cancer survivors and controls; and to assesses the management of hypertension and statin use among cancer survivors compared with controls in a multi-ethnic and socio-economically diverse population. Methods The data were obtained from electronic health records of 1.2 million people registered with general practices in East London. It provides a snapshot of health records at the time of data extraction (01/01/2023). We identify individuals with record of past cancer (grouped into 20 cancer types) and their cardiovascular profile. Each cancer-exposed patient was age- and sex-matched to four non-cancer comparators. Multivariable logistic regression, with extensive adjustment for demographic and health-related variables, was used to elucidate the independent associations of past cancer with a range of cardiovascular outcomes. Patterns of guideline-directed risk factor control among cancer patients with hypertension and ischaemic CVDs (vs non-cancer controls) were assessed. Results The study consisted of 18,839 cancer survivors and 75,356 matched controls (64±15 years, 43% male), with marked ethnic diversity (cancer survivors: 48% White, 24% Black and 22% Asian) and socio-economic deprivation. Compared to matched controls, patients with past cancer had a higher prevalence of hypertension (44% vs. 41%) and chronic kidney disease (18% vs. 14%). We observed a higher prevalence of CVDs including venous thromboembolism (VTE) (5.6% vs. 2.8%), atrial fibrillation (AF) (6.5% vs. 5%), and heart failure (HF) (4.4% vs. 3.4%) among cancer survivors. Regression models fully adjusted for shared risk factors demonstrated an increased risk of a range of CVDs in patients with (any) past cancer, including VTE (OR 2.01), HF (OR 1.31) and AF (OR 1.27). CVD risk varied across cancer types (Figure 1). For example, lung cancer survivors had an elevated risk of VTE (OR 4.02), AF (OR 2.47), IHD (OR 1.45) and peripheral artery disease (OR 1.67) while colorectal cancer survivors had increased risks of VTE (OR 2.68), HF (OR 1.4) and AF (OR 1.32). In subgroup analyses, control of blood pressure and cholesterol did not differ significantly across cancer survivors and matched controls with hypertension and ischaemic CVDs, respectively. Conclusion We show higher burden of VRFs and an increased risk of CVDs among cancer survivors compared with non-cancer controls, with notable variation across cancer types. The lack of difference in control of blood pressure and cholesterol between cancer survivors and controls suggests that these risk factors did not explain the increased risk. Suggesting that an individualised approach to risk management is likely to be warranted.Risk of CVDs in Cancer Survivors

Mediterranean-type diet trajectories and 20-year cardiovascular disease incidence: the ATTICA study (2002-2022)

Abstract Background/Introduction The protective effects of the Mediterranean-type diet (MTD) against cardiovascular disease (CVD) are well-known. However, based on a recent systematic review of 57 studies with 1,125,560 participants, MTD adherence has declined worldwide, even in the Mediterranean region, compared to the past, especially in the last decade. Moreover, studies evaluating changes in diet and CVD risk are scarce. Purpose The aim of this study was to longitudinally evaluate MTD adherence and changes in MTD adherence during 20-years of follow-up and its relation to 20-year CVD incidence. Methods Participants initially free-of-CVD from the ATTICA study were used (n=1,986). At 2002 and 2022, CVD events were assessed according to WHO-ICD-10 and MTD adherence was assessed via MedDietScore (range: 0-55). Hence, MTD trajectories were defined according to MTD adherence in 2002 and in 2022 as: low-low, low-high, high-low, high-high (i.e., high: MedDietScore >27/55). Results During the 20-year follow-up, 30.2% (n=600) of the participants were always away (i.e., low-low), 30.0% (n=596) went away (high-low), 21.4% (n=424) were always close (high-high) and 22% got closer (low-high) to the MTD. The 20-year CVD incidence was: 38.8% (n=233), 87.7% (n=321), 10.2% (n=61) and 24.3% (n=103) in those in the low-low, low-high, high-low and high-high trajectory, respectively (p-value<0.001). In multi-adjusted models, adjusted for socio-economic, clinical and lifestyle parameters, it was found that compared to those who were always away from the MTD, those who were always close had 68% lower CVD risk [Hazard Ratio-HR: 0.32, 95%Confidence Interval-CI: 0.14, 0.72], while those who went away during the 20-year follow-up had 47% lower CVD risk [HR: 0.53, 95%CI: 0.32, 0.86]. Conclusion Our study findings highlight the long-lasting effects of the MTD adherence early in the life-course. Public health measures to prevent CVD should focus on facilitating MTD adherence, as early in life as possible.

Validation of digital cardiovascular risk score (DiCAVA) in the United States All of Us dataset

Abstract Introduction The cardiovascular disease (CVD) risk score DiCAVA was developed in 2021 using UK Biobank data with the aim to be used for population health screening by deriving its predictions only from variables readily available to every individual, omitting difficult-to-obtain measurements such as blood pressure and invasive blood tests for metrics like cholesterol or HbA1c, which are commonly used in clinical CVD risk assessment tools. The original set of variables was reduced to 30 in the DiCAVA Lite score to further improve usability in a digital solution accessible to the general population, while maintaining its discrimination ability. Purpose Like many countries, the US has a large burden of CVD and would benefit from easily accessible screening tools. However, to ensure generalisability of the UK-developed score, it is necessary to evaluate its performance in a population where the score is intended to be used. Methods Data from a large real-world modern observational study in the US, All of Us, was used to evaluate discrimination and calibration metrics of the risk score. Participants with pre-existing CVD and without available electronic health records were excluded from the study. Variables from the All of Us dataset were matched to the original variables and any missing values were imputed using multiple imputation. Results 216,985 participants with a median follow-up time of 3.44 years were included in the study. The median age was 51 years and 63% of the population were female. Discrimination ability in the All of Us dataset (C-index 0.76) slightly surpassed the discrimination achieved at training with UK Biobank (C-index 0.73), and that of Framingham risk score calculated for the All of Us population (C-index 0.72), demonstrating the score’s usability in the US. The score showed very good discrimination in both males (C-index 0.74) and females (C-index 0.77), all ethnic groups and age groups, with the exception of the population over 65 years of age, where the C-index dropped to 0.65 as expected (similar to that observed in the UK Biobank). Calibration of the original model was assessed at 3 years and showed under-estimation of the predicted risk (calibration-in-the-large of 2.37%). Following re-calibration, the algorithm demonstrated excellent results with the average predicted 3-year risk showing 0.59% difference from the observed CVD rate (calibration plot in Figure). Conclusions Overall, the DiCAVA Lite score has shown very good discrimination in the US, showing its generalisability in different demographic populations. Its re-calibrated form is now validated for use in the US population and because of its ability to be utilised outside clinical settings, it can be deployed widely in the general population as an initial screening tool and potentially boost awareness of cardiovascular health in an effort to drive preventative care of CVD.Re-calibration of the DiCAVA Lite score

Rurality and outcomes in prostate cancer: role of socioeconomic status and educational attainment

Abstract Background/Introduction Patients diagnosed with prostate cancer (PC) have a higher cardiovascular disease (CVD) prevalence and mortality risk. Rurality have been associated with up to 33% higher CVD risk and 44% higher all-cause mortality risk in patients with PC. Purpose Analyze the impact of rurality (from both patient and provider perspectives) on the development of adverse outcomes after a PC diagnosis according to socioeconomic and educational status. Methods We included men aged ≥66 with a new primary PC diagnosis (defined as ICD-10 = C61) from 2009-2017 from the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database. The primary outcomes were CVD (comprising heart failure, atrial fibrillation, acute myocardial infarction, peripheral artery disease, and ischemic stroke), PC-specific mortality (PCsm), cardiovascular disease mortality (CVDm), and all-cause mortality. Patients living in areas with a population of <2,500 or <20,000, not adjacent to a metropolitan area, were considered to have a positive rural status. The provider status (metropolitan vs. non-metropolitan) was defined according to the 2013 National Center for Health Statistics' Urban-Rural Classification Scheme for Counties. Low socioeconomic status (SES) was defined according to Yost Index quintiles. Low educational status was defined according to percentiles of people >25 years old with less than a high school diploma. Multivariable Fine-Gray models, accounting for competing mortality/type of mortality, and Cox regression models were applied. Results We included 75,221 patients with PC (Picture 1), of which 1,828 were from rural areas and 362 were from rural areas with providers from non-metropolitan areas. Among patients from rural areas under the care of non-metropolitan providers, 82.6% had low SES (Yost Index ≤ 2). In this subgroup, patients from rural areas with non-metropolitan providers had 30% higher CVD risk (sHR 1.30; 95% CI 1.04-1.62) and 44% higher all-cause mortality risk (sHR 1.44; 95% CI 1.14-1.83; Picture 2) when compared to patients with low SES from urban or rural areas with providers from metropolitan areas. Additionally, within patients from rural areas with non-metropolitan providers, the median % of people with only high school diploma was 38.3 (IQR 36.2-40.9). Among those with low educational status (≤41% of high school county-rate), patients from rural areas with non-metropolitan providers had a 35% higher associated CVD risk (sHR 1.35; 95% CI 1.06-1.71), 54% higher associated CVDm risk (sHR 1.54; 95% CI 1.01-2.36), and a 32% higher associated all-cause mortality risk (sHR 1.32; 95% CI 1.04-1.66). Conclusion Patients with PC from rural areas with non-metropolitan providers have higher rates of low SES and low educational status and suffer from up to 54% higher associated risks of adverse outcomes, emphasizing the role of multiple domains of the Social Determinants of Health in health outcomes.

Evaluating trends and insights in cardiovascular risk among the polish population

Abstract Introduction Cardiovascular diseases (CVD) are the leading cause of death in Poland and worldwide. Lifestyle changes and early diagnosis can reverse this unfavorable trend. In the face of escalating global health challenges, the identification of CVD risk factors becomes paramount, especially within national contexts where demographic shifts and lifestyle changes can significantly impact the health profile of the population. Aim of the study. Determining the prevalence of CVD risk factors in the Polish population and analyzing their changes over time. Material and Methods Data of 705,420 Poles aged 35-55 years who were enrolled in CVD disease prevention programme between 2012 and 2021 were analysed. The prevalence of the following CVD risk factors was determined: nicotinism, hypertension, elevated total cholesterol, elevated LDL, reduced HDL, elevated triglycerides, elevated glucose (indicating pre-diabetes), low physical activity, overweight, obesity, SCORE ≥5%. In addition, we assessed how the mean SCORE, BMI, systolic blood pressure, diastolic blood pressure, total cholesterol, LDL cholesterol, LDL cholesterol, triglycerides, glucose levels and waist circumference changed over time. Results Nicotinism affected 17.98%-24% of women (W) and 27.29%-36% of men (M). Hypertension was in 7.04%-8.58% of W and 17.45%-19.62% of M. Elevated total cholesterol were in 55.69%-63.64% of W and 65.91%-72.68% of M. Elevated LDL were in 44.77%-54.2% of W and 58.26%-65.48% of M. Reduced HDL were in 9.84%-11.52% of W and 14.48%-16.57% of M. Elevated triglyceride were in 13.44%-15.37% of W and in 33.81%-36.29% of M. Elevated glucose indicating a pre-diabetic status were in 10.70%-13.16% of W and in 18.91%-22.76% of M. Low physical activity was in 75.96%-82.2% of W and 73.32%-81.67% of M. Overweight conditions were in 30.37%-31.67% of W and 48.61%-49.45% of M. Obesity affected 14.04%-17.12% of W and 20.67%-24.69% of M. SCORE ≥ 5% was in 0.23%-0.38% of W and in 13.08%-18.72% of M. There was a decrease in the mean SCORE value (-0.08; 95%CI: -0.09 - -0.06) from 2012. An increase over time was noted in mean BMI (-0.01; 95%CI: -0.05 - 0.04). There was a slight decrease followed by a notable increase over time in mean systolic (-0.35; 95%CI: -0.47 - -0.24) and diastolic blood pressure (-0.25; 95%CI: -0.32 - -0.18). There was a decrease in mean total cholesterol (-3.29; 95%CI: -4.27 - -2.31) and mean LDL cholesterol (-3.11 95%CI: -4.22 - -2.01). A notable increase was observed in mean glucose values (0.01; 95%CI: 0-0.01). Over time, there was an increase in mean waist circumference value (-0.19; 95%CI: -0.54-0.16). Conclusions The escalation of CVD risk among the Polish population is illustrated, with a marked increase in obesity, sedentary lifestyles and indicators of metabolic syndrome. These trends highlight the urgent need for targeted public health initiatives and for the implementation of comprehensive strategies to mitigate these risks

Embedding a text message recall system to increase the uptake of cardiovascular screening in Australian general practice. Results of the Text to Detect randomised controlled trial

Abstract Background Australian guidelines recommend cardiovascular disease (CVD) risk screening for adults aged 45-74 years, but less than one in three have blood pressure and cholesterol recorded within their general practitioner (GP) records. Medicare subsidised ‘Heart Health Checks’ were introduced in primary care in 2019, however uptake has been suboptimal. Purpose The aims of this study were to; 1) implement a text mediated Heart Health Check recall program within general practice at scale, 2) determine whether uptake can be increased with nudge reminder text messages and 3) evaluate the impact on risk factor measurement and medication prescription. Methods Australian general practices were invited via advertisement and mailing list. Medical record software identified patients eligible for a Heart Health Check. Practices were randomised to one of three arms: 1) standard SMS: 1 SMS inviting patients to see their GP for a Heart Health Check, 2) nudge reminder: standard SMS + nudge reminder two weeks later, 3) control: no SMS. Aggregate, deidentified, practice-level data was extracted at baseline and 3-months. The primary outcome was the proportion of Heart Health Checks delivered at a practice level. Secondary outcomes included updated CVD risk factor assessment and new medication prescriptions. Analyses used ANOVA and Tukey's HSD. Results Between 2022 and 2023, 206 general practices participated, each with 560 median eligible patients (IQR:297-909). A total of 70,679 recall text messages and 34,406 nudge reminder messages were sent. Heart Health Check uptake was 11 and 16 times higher in the standard and nudge arms (respectively) compared to control (0.4 vs 4.5 vs 6.3 per 100 patients, p<0.001), with a 40% statistically significant increase (p=0.02) for 2 SMS vs 1 SMS. Updated cholesterol values were 31.6 and 60.2% higher in standard and nudge arms (respectively) compared to control (13.7 vs 16.8 vs 17.4 per 100 patients, p=0.02). Both active arms were statistically significantly different from control (standard p=0.047, nudge p=<0.001). Updated blood pressure was 23.0 and 26.8% higher in the standard and nudge arms (respectively) compared to control (13.7 vs 16.8 vs 17.4 per 100 participants), however only the nudge arm was statistically significantly different (p=0.38). New medication prescription (lipid or blood pressure-lowering) was 36.8% higher in the nudge arm compared to control (32.1 vs 43.9 patients per practice, p=0.03). Conclusions This study demonstrates the effectiveness of text mediated recall of eligible patients to increase the uptake of cardiovascular risk screening in Australian general practice. The findings will inform the implementation of new Australian guidelines and policy reform.