Cardiovascular Disease Risk Assessment Research Articles

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.

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

Office-based risk equation of Globorisk for prediction of ten-years cardiovascular risk among Iranian population: findings from Fasa PERSIAN cohort study

BackgroundGloborisk is one of the prediction tools for 10-year risk assessment of cardiovascular disease, featuring an office-based (non-laboratory-based) version. This version does not require laboratory tests for determining the CVD risk. The present study aims to determine the 10-year CVD risk using the office-based Globorisk model and factors associated with the 10-year CVD risk.MethodsIn this study, baseline data from 6810 individuals participating in the Fasa cohort study, with no history of CVD or stroke, were utilized. The risk equation of the office-based Globorisk model incorporates age, sex, systolic blood pressure (SBP), body mass index (BMI), and smoking status. The Globorisk model categorizes the risk into three groups: low risk (< 10%), moderate risk (10% to < 20%), and high risk (≥ 20%). To identify factors associated with the 10-year CVD risk, the predicted risk was categorized into two groups: <10% and ≥ 10%. Multivariable logistic regression analysis was employed to determine factors associated with an increased CVD risk.ResultsAccording to the 10-year CVD risk categorization, 78.3%, 16.4%, and 5.3% of men were in the low, moderate, and high risk groups, respectively, while 85.8%, 10.0%, and 4.2%, of women were in the respective risk groups. Multivariable logistic regression results indicated that in men, the 10-year CVD risk decreases with being an opium user, and increases with being illiterate, having abdominal obesity, and low or moderate physical activity compared to high physical activity. In women, being married, and higher fiber consumption decrease the 10-year CVD risk, while being illiterate, low or moderate physical activity compared to high physical activity, having abdominal obesity, opium use, and being in wealth quintiles 1 to 4 compared to quintile 5 increase the risk.ConclusionsConsidering the factors associated with increased CVD risk, there is a need to enhance awareness and modify lifestyle to mitigate and reduce the risk of CVD. Additionally, early identification of individuals at moderate to high risk is essential for preventing disease progression. The use of the office-based Globorisk model can be beneficial in settings where resources are limited for determining the 10-year CVD risk.

Risk-enhancing factors and social determinants of health in risk assessment for atherosclerotic cardiovascular disease.

The Pooled Cohort Equations (PCEs) do not accurately estimate atherosclerotic cardiovascular disease (ASCVD) risk in certain populations. The 2018 AHA/ACC cholesterol guideline identified risk-enhancing factors as a supplement to PCEs-based risk assessment. However, the role of each risk-enhancing factor in ASCVD risk assessment has not been well quantified. Further, social determinants of health (SDOH) are not included in the PCEs nor considered as risk-enhancing factors in the US cholesterol guideline. We sought to evaluate ASCVD risk associated with each risk-enhancing factor and commonly collected SDOH including education, income, and employment status, and to assess if adding risk-enhancing factors and SDOH to the PCEs improve ASCVD risk prediction. We included individuals aged 40 to 75 years, without ASCVD or diabetes at baseline, and with low-density lipoprotein cholesterol 70-189 mg/dL from two contemporary prospective cohort studies (MESA and REGARDS) and from Kaiser Permanente Southern California (KPSC). The primary endpoint was incident ASCVD defined as nonfatal myocardial infarction, fatal coronary heart disease, or fatal or nonfatal stroke over a 10-year period (median follow-up 10 years). We used Cox proportional hazards models to estimate associations between risk-enhancing factors and SDOH with ASCVD. We also assessed changes in model performance after adding risk-enhancing factors and SDOH to the PCEs. We included 13,863 adults (mean age 60.7 years) from the prospective cohorts and 307,931 adults (mean age 54.8 years) from KPSC. Risk-enhancing factors including hypercholesterolemia, hypertriglyceridemia, metabolic syndrome, and chronic kidney disease were associated with a higher ASCVD risk, independent of 10-year risk estimated by the PCEs. Low education, low income, and unemployment were also associated with higher ASCVD risk. While adding individual risk-enhancing factors or SDOH to the PCEs had limited impact on model performance, adding multiple risk-enhancing factors and SDOH simultaneously led to modest improvements in discrimination (C-index increased by up to 0.07), calibration (integrated Brier score reduced by up to 2.3%), and net reclassification improvement up to 41.4%. These findings suggest including SDOH and risk-enhancing factors may improve ASCVD risk assessment.

The complete blood count and cardiovascular disease: analyses across six cohorts of 23,370 adults.

The complete blood count (CBC) is one of the most commonly performed laboratory studies. Although studies have found associations between the CBC and cardiovascular disease (CVD), there is limited contemporary information regarding the relationship between the CBC and traditional risk factors and their joint association with CVD endpoints. We sought to define the relationships between the CBC and traditional CVD risk factors and their joint association with CVD endpoints in diverse adult populations. We first examined the relationships between the CBC variables (directly and their principal components), traditional CVD risk factors, and mortality in NHANES (n=7843). Next, we validated and extended these findings to more refined CVD endpoints in five additional cohorts (n=15,527). We first examined the variance accounted for by common laboratory studies (lipid panel, HbA1c, hs-CRP, and basic metabolic panel) by traditional risk factors in NHANES. With the exception of hemoglobin (Hb)-related components, we found that traditional risk factors accounted for less than 20% of the variance in CBC values, similar to that of lipid parameters. Additionally, in the clinically adjusted model, the CBC was more strongly associated with all-cause mortality than the lipid panel or CRP (p<0.0001). Next, we validated and extended these findings across five additional longitudinal cohorts with a mean follow-up of 16 years to evaluate the association of individual CBC parameters and their principal components with refined CVD endpoints. In the fully adjusted meta-analyses across the five cohorts, several CBC components including the white blood cell (WBC) count, neutrophil (PMN) count, hemoglobin (Hb) level, and an integrated immune cell score, were associated with individual CVD endpoints and a composite CV endpoint (MACE3: incident stroke, MI, and revascularization) with standardized hazard ratios of 1.13 (p=0.002), 1.15 (p=0.0006), 0.82 (p<0.0001), and 2.16 (p<0.0001) respectively. This study represents the first systematic examination of the relationship between CBC features and established risk factors, as well as numerous CVD endpoints, in a diverse cohort of 23,370 adults. The findings of this study underscore the potential utility of integrating CBC features into CVD risk assessment and suggest important mechanistic insights into the association between individual CBC components and the genesis of CVD.

Assessing the relative importance of vitamin D deficiency in cardiovascular health.

Previous research has suggested a potential link between vitamin D (VD) deficiency and adverse cardiovascular health outcomes, although the findings have been inconsistent. This study investigates the association between VD deficiency and cardiovascular disease (CVD) within the context of established CVD risk factors. We utilized a Random Forest model to predict both CVD and VD deficiency risks, using a dataset of 1,078 observations from a rural Chinese population. Feature importance was evaluated using SHapley Additive exPlanations (SHAP) to discern the impact of various risk factors on the model's output. The results showed that the model for CVD prediction achieved a high accuracy of 87%, demonstrating robust performance across precision, recall, and F1 score metrics. Conversely, the VD deficiency prediction model exhibited suboptimal performance, with an accuracy of 52% and lower precision, recall, and F1 scores. Feature importance analysis indicated that traditional risk factors such as systolic blood pressure, diastolic blood pressure, age, body mass index, and waist-to-hip ratio significantly influenced CVD risk, collectively contributing to 70% of the model's predictive power. Although VD deficiency was associated with an increased risk of CVD, its importance in predicting CVD risk was notably low. Similarly, for VD deficiency prediction, CVD risk factors such as systolic blood pressure, glucose levels, diastolic blood pressure, and body mass index emerged as influential features. However, the overall predictive performance of the VD deficiency prediction model was weak (52%), indicating the absence of VD deficiency-related risk factors. Ablation experiments confirmed the relatively lower importance of VD deficiency in predicting CVD risk. Furthermore, the SHAP partial dependence plot revealed a nonlinear relationship between VD levels and CVD risk. In conclusion, while VD deficiency appears directly or indirectly associated with increased CVD risk, its relative importance within predictive models is considerably lower when compared to other risk factors. These findings suggest that VD deficiency may not warrant primary focus in CVD risk assessment and prevention strategies, however, further research is needed to explore the causal relationship between VD deficiency and CVD risk.

Calling for Action: The Need of Large-Scale Cohorts to Uncover the Cardiovascular Risk in Non-Sleepy Obstructive Sleep Apnea.

Since randomized clinical trials currently do not support continuous positive airway pressure treatment of asymptomatic obstructive sleep apnea (OSA) we proposed the Obesity, Symptoms, and CARdiovascular assessment (OSCAR) algorithm to aid clinicians in the management of asymptomatic low-risk moderate-severe OSA, focusing on weight loss, symptoms and cardiovascular disease (CVD) risk assessment. Exploiting the data of the Sleep Heart Health Study we selected subjects with a body mass index (BMI) < 30 Kg/m2, no history of CVD or sleepiness and compared 552 patients with moderate-severe OSA (OSCAR(-)) to 916 individuals without OSA (No-OSA). After adjusting for age, gender, and BMI, there was no significant difference in the risk of major adverse cardiovascular events (MACE) between OSCAR(-) and No-OSA (1.05; 95%CI 0.81-1.37). The study suggests that low-risk moderate-severe OSA patients may not have a greater risk of MACE compared to those without OSA and highlights the need for further research on this topic.

Neutrophil-to-High-Density Lipoprotein Ratio (NHR) and Neutrophil-to-Lymphocyte Ratio (NLR) as prognostic biomarkers for incident cardiovascular disease and all-cause mortality: A comparison study

Cardiovascular diseases (CVD) remain a leading cause of global mortality, with atherosclerosis and inflammation playing pivotal roles in their development. The neutrophil-to-lymphocyte ratio (NLR) and neutrophil-to-HDL cholesterol ratio (NHR) have emerged as potential biomarkers for assessing CVD risk. In this community-based cohort study conducted in Taiwan, involving 3278 participants, we investigated the associations between NHR, NLR, and the risks of CVD and all-cause mortality. Our findings revealed that both NHR and NLR were effective in identifying individuals at high risk for CVD. However, when assessing their joint effect, NHR alone demonstrated a stronger predictive value for CVD prognosis than NLR or the combination of both markers. Furthermore, NLR alone showed potential as a predictor of all-cause mortality when compared with NHR alone or in combination with NLR and NHR. These findings underscore the complex interplay between inflammation and lipid metabolism in the pathogenesis of CVD. While NHR shows promise as a cost-effective tool for CVD risk assessment, NLR emerges potential as a prognostic marker for mortality. Further research is warranted to explore the dynamic changes in these markers and their implications for clinical practice.

Aortic-Femoral Stiffness Gradient and Cardiovascular Risk in Older Adults.

The aortic-femoral arterial stiffness gradient, calculated as the ratio of lower-limb pulse-wave velocity (PWV) to central (aortic) PWV, is a promising tool for assessing cardiovascular disease (CVD) risk, but whether it predicts incident CVD is unknown. We examined the association of the aortic-femoral arterial stiffness gradient measures carotid-femoral stiffness gradient (femoral-ankle PWV divided by carotid-femoral PWV) and the heart-femoral stiffness gradient (femoral-ankle PWV divided by heart-femoral PWV), as well as PWV, with incident CVD (coronary disease, stroke, and heart failure) and all-cause mortality among 3109 participants of the Atherosclerosis Risk in Communities Study cohort (age, 75±5 years; carotid-femoral PWV, 11.5±3.0 m/s), free of CVD. Cox regression was used to estimate hazard ratios (HR) and 95% CIs. Over a median 7.4-year follow-up, there were 322 cases of incident CVD and 410 deaths. In fully adjusted models, only top quartiles of carotid-femoral stiffness gradient (quartile 4: HR, 1.43 [95% CI, 1.03-1.97]; and quartile 3: HR, 1.49 [95% CI, 1.08-2.05]) and heart-femoral stiffness gradient (quartile 4: HR, 1.77 [95% CI, 1.27-2.48]; and quartile 3: HR, 1.41 [95% CI, 1.00-2.00]) were significantly associated with a greater risk of incident CVD. Only high aortic stiffness in combination with low lower-limb stiffness was significantly associated with incident CVD (HR, 1.46 [95% CI, 1.06-2.02]) compared with the referent low aortic stiffness and high lower-limb stiffness. No PWVs were significantly associated with incident CVD. No exposures were associated with all-cause mortality. The aortic-femoral arterial stiffness gradient may enhance CVD risk assessment in older adults in whom the predictive capacity of traditional risk factors and PWV are attenuated.

A-001 The Postprandial Levels of the Metabolites in the Metaorganismal Trimethylamine N-Oxide (TMAO) Pathway are Altered in A Diet-, Microbe-, and Sex-Specific Manner

Abstract Background Cardiovascular disease (CVD) remains the leading cause of death in developed countries. Elevated levels of the gut-microbe-associated metabolite trimethylamine-N-oxide (TMAO) have been associated with increased risk for CVD mortality in many large independent studies. In fact, large laboratory corporations such as Labcorp and Quest Diagnostic now offer TMAO diagnostic tests for the assessment of CVD risk and as a marker for disease-associated dysbiosis, using samples obtained from fasting patients. Although the strong association between TMAO levels and CVD risk has been established in fasting blood samples, here we are investigating the potential for a single meal to dynamically alter TMAO-related metabolites based on sex, diverse dietary substrates, and microbial influences. Methods 35 healthy participants were randomized to one of four study groups with approximately 8-9 subjects in each arm. Half of the participants were randomly assigned to receive a three-day broad spectrum antibiotic regimen (ciprofloxacin, metronidazole, and vancomycin) while the others received no antibiotics. These two groups were further subdivided into a group consuming a highly processed meal (originating from local fast food restaurants) or alternatively a whole food meal (containing a variety of fruits, vegetables, and healthy fiber). Blood samples were taken at baseline (after an overnight fast), and then postprandially at 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, and 6 hours after meal ingestion. Targeted plasma metabolites were quantified using a stable isotope dilution, liquid chromatography - tandem mass spectrometry (LC-MS/MS) method Results While plasma TMAO levels between food groups did not change significantly within the total cohort, there were clear individualized responses to either highly processed or whole food meals. Separation based on sex showed that TMAO levels were significantly reduced in females at 6 hours but remained steady in males for both food groups. Particularly, in the processed food group, TMAO levels were significantly lower in females than males at the 6-hour time point. Neither of these observations held true for TMAO precursors choline, carnitine, or betaine. However, plasma levels of a dietary precursor for TMAO, γ-butyrobetaine, showed clear diet-microbe-host interactions. For males in the processed food group, plasma γ-butyrobetaine levels were significantly increased in subjects on broad spectrum antibiotics. Conclusions Our results show the postprandial levels of TMAO, and its nutrient precursors dynamically change in a diet-, microbe-, and sex-dependent manner. These findings provide new insights into the postprandial levels of TMAO-related metabolites and may inform precision nutritional approaches in those who could benefit from TMAO-lowering strategies.

A-223 Direct LDL or not Direct-LDL, that is the question

Abstract Background Management of Cardiovascular Disease (CVD) risk is dependent on Low Density Lipoprotein Cholesterol (LDL-C) levels; therefore LDL-C serves as the marker for the assessment of CVD risk and the focus of lipid lowering treatment. The gold standard reference method for measurement of LDL-C is beta-quantification. We compared calculated LDL-C with Friedewald (F-LDL-C), Martin-Hopkins (M-LDL-C) and Sampson (S-LDL-C) equations versus LDL-C directly measured (D-LDL-C). In CVD management also cholesterol ratios are evaluated. TC/HDL is associated with morbidity and mortality in the general population. Furthermore, several studies have stated that high triglycerides (TG) levels and low HDL-C (TG/HDL ratio) could function as an atherogenic index. Methods 11399 samples were analyzed on Siemens Atellica Solution® for the lipid profile determination measuring Total Cholesterol (TC), D-LDL-C, HDL-C and TG. In the absence of additional clinical parameters, based on desirable levels for LDL-C recommended by guidelines, CVD risk was evaluated by assigning to LDL-C a cut-off of 100 mg/dL. In presence of misclassifications, we used two other parameters to assess LDL-C results: TG/HDL-C ratio and CT/HDL-C. Results Patients cohort had a mean age of 57.7 (±16.8) years of which 53% (age=58.6, ±15.9) were males and 47% (age=56.5, ±17.8 years) were females. Of these, the 57.7% were outpatients and 42.3% inpatients (42.1% of infectious diseases - 24.4% of the cardiovascular department). Data about LDL-C misclassification and ratio data parameters are shown in table 1. Discordant patients for D-LDL-C vs F-LDL-C are 8.5%, that of D-LDL-C vs M-LDL-C are 7.7% and D-LDL-C vs S-LDL-C are 7.2%. Conclusions Is known that LDL plays a central role in the pathogenesis of atherosclerosis. Accurate estimation of LDL-C is a fundamental point for the stratification of CVD risk and the achievement of the therapeutic goal; however, we are still uncertain about the best and accurate way to measure it.

A-224 Non HDL Cholesterol: could be e new cardiovascular disease risk stratification factor?

Abstract Background A worldwide study demonstrated that among all modifiable risk factors of Cardiovascular Disease (CVD) to the abnormal cholesterol levels is attributable the highest risk of events. LDL-C is considered the most important lipoprotein risk factor. Some recent epidemiologic studies have suggested that non-HDL cholesterol (N-HDL-C) may be superior to LDL-C for identifying CVD risk. N-HDL-C is easily calculated from a lipid profile and represents all apolipoprotein B containing lipoproteins. Recent guidelines recommend LDL-C as a primary indicator and non-HDL-C as secondary. Moreover, cholesterol ratios are useful to stratification; the TC/HDL-C is associated with morbidity and mortality in the general population; in addition, several studies have stated that high triglycerides (TG) levels and low HDL-C are associated with increased risk and could function as atherogenic index. Methods 11399 samples were analyzed on Atellica Solution for the determination of Total Cholesterol (TC), D-LDL-C, HDL-C and TG. In the absence of clinical parameters, based on the desirable levels recommended by the guidelines, CVD risk was evaluated by assigning a cut-off of 100 and 130 mg/dL for D-LDL-C and N-HDL-C respectively Results Patients cohort mean (±SD) for CT, D-LDL, HDL, TG and N-HDL-C are 180 mg/dL (±43.2), 113 mg/dL (± 38.5), 51.7 mg/dL (±15.6), 116 mg/dL (±73.8), 128 mg/dL (±39.5) respectively. Of the examined patients, the 57.7% were outpatients, 21.8% of infectious diseases and 12.6% of the cardiovascular department. Data about D-LDL-C and N-HDL-C comparison, evaluated on discordant patients, are shown in table 1. Conclusions The data obtained from evaluation would seem to confirm hypothesis according to which non-HDL cholesterol would have a greater power in the identification of CVD risk because of cholesterol ratios are suggestive of increased risk for patients with an LDL-C&amp;lt;100 and N-LDL-C&amp;gt;130 mg/dL. Further studies assessing CVD risk, not only through laboratory data, are necessary to confirm this supposition.

External Validation of the American Heart Association PREVENT Cardiovascular Disease Risk Equations

The American Heart Association's Predicting Risk of Cardiovascular Disease Events (PREVENT) equations were developed to extend and improve on previous cardiovascular disease (CVD) risk assessments for the purpose of treatment initiation and patient-clinician communication. To assess prognostic capabilities, calibration, and discrimination of the PREVENT equations in a study sample representative of the noninstitutionalized, US general population. This prognostic study used data from the National Health and Nutrition Examination Survey (NHANES) 1999 to 2010 data cycles. Participants included adults for whom 10-year follow-up data were available. Data curation and analyses took place from December 2023 through May 2024. Primary measures were risk estimated by the PREVENT equations, as well as risk estimates from the previous Pooled Cohort Equations (PCEs). The primary outcome was composite CVD-related mortality at 10 years of follow-up. Additional analyses compared the PREVENT equations against the PCEs. Model discrimination was assessed with receiver-operator characteristic curves and Harrell C statistic from proportional hazard regression; model calibration was determined as the slope of predicted versus observed risk. The study cohort, accounting for NHANES complex survey design, consisted of 172.9 million participants (mean age, 45.0 years [95% CI, 44.6-45.4 years]; 52.1% women [95% CI, 51.5%-52.6%]). In analyses adjusted for the NHANES survey design, a 1% increase in PREVENT risk estimates was statistically significantly associated with increased CVD mortality risk (hazard ratio, 1.090; 95% CI, 1.087-1.094). PREVENT risk scores demonstrated excellent discrimination (C statistic, 0.890; 95% CI, 0.881-0.898) but moderate underfitting of the model (calibration slope, 1.13; 95% CI, 1.06-1.21). PREVENT risk models performed statistically significantly better than the PCEs, as assessed by the net reclassification index (0.093; 95% CI, 0.073-0.115). In this prognostic study of the PREVENT equations, PREVENT risk estimates demonstrated excellent discrimination and only modest discrepancies in calibration. These findings provided evidence supporting utilization of the PREVENT equations for application in the intended population as suggested by the American Heart Association.

Association Between Family Income, Subclinical Myocardial Injury, and Cardiovascular Mortality in the General Population.

Both low family income and subclinical myocardial injury (SCMI) are risk factors for cardiovascular disease (CVD) mortality. However, the impact of their joint association on CVD mortality is unclear. This analysis from the third National Health and Nutrition Examination Survey included 6805 participants (age 59.1 ± 13.4 years, 52.3% women, and 49.8% White) free of CVD at baseline. Family income was assessed using the poverty-income ratio (PIR) and categorized into low (PIR < 1), middle (PIR = 1-4), and high (PIR > 4) income. A validated ECG-based cardiac infarction injury score (CIIS) ≥ 10 was considered positive for SCMI. CVD mortality was determined using the National Death Index. Cox-proportional hazard analysis was used to evaluate the associations of family income and SCMI, separately and jointly, with CVD mortality. A total of 1782 (26.2%) participants had SCMI at baseline. During a median follow-up of 18.2 years, 856 (12.6%) events of CVD mortality occurred. In separate multivariable Cox models, SCMI (vs. no SCMI) and middle- and low-income (vs. high-income) were each associated with a higher risk of CVD mortality (HR [95% CI]: 1.34 [1.16-1.54], 1.44 [1.16-1.78], and 1.59 [1.22-2.07], respectively). Compared to high-income participants without SCMI, those with low-income and SCMI had an increased risk of CVD mortality (HR [95% CI]: 2.17 [1.53-3.08]). The multiplicative interaction between PIR and SCMI was not significant (p = 0.054). Lower family income and SCMI are associated with CVD mortality, and their concomitant presence is associated with the highest risk. Family income and SCMI may help in the individualized assessment of CVD risk.

A Cross-Sectional Study on Cardiovascular Disease Risk Assessment among the Adult Population in Poonamallee Taluka, Tiruvallur District, Tamil Nadu

A Cross-Sectional Study on Cardiovascular Disease Risk Assessment among the Adult Population in Poonamallee Taluka, Tiruvallur District, Tamil Nadu

Blood-based HYAL2 methylation as a potential marker for the preclinical detection of coronary heart disease and stroke

BackgroundCoronary heart disease (CHD) and stroke have become the leading cause of premature mortality and morbidity worldwide. Therefore, sensitive and accurate biomarkers for early detection of CHD and stroke are urgently needed for effective prevention and treatment. We aim to investigate the association between blood-based HYAL2 methylation and the risk of CHD and stroke in Chinese population.MethodsIn a prospective nested case–control study comprising 171 CHD cases, 139 stroke cases, who developed the diseases after recruitment and 356 controls who remained healthy during the 2.5 years of follow-up time, the methylation level of HYAL2 in the peripheral blood was quantified using mass spectrometry, and the association was calculated by logistic regression adjusted for covariant.ResultsSignificant association between HYAL2 methylation in the peripheral blood and increased risk of preclinical CHD and stroke were identified [odds ratios (ORs) per − 10% methylation: 1.35–1.64, p ≤ 0.045 for HYAL2_CpG_1, HYAL2_CpG_2 and HYAL2_CpG_3 in CHD; ORs per − 10% methylation: 0.76–1.64, p ≤ 0.033 for HYAL2_CpG_2 and HYAL2_CpG_4 in stroke]. The association in CHD was further enhanced by female gender, younger age (< 70 years old), without the history of hypertension and cancer. The combination of four HYAL2 methylation sites showed an effective discrimination of CHD and stroke cases without hypertension from controls [area under curve (AUC) = 0.78 and 0.75, respectively].ConclusionsThis study presents a strong association of altered HYAL2 methylation in peripheral blood with preclinical CHD and stroke, providing a novel biomarker for risk assessment and early detection of cardiovascular diseases.

Elevated remnant cholesterol as a potential predictor for cardiovascular events in rheumatoid arthritis patients.

The risk of cardiovascular disease (CVD) in patients with rheumatoid arthritis (RA) remains inadequately defined. Consequently, this study aims to evaluate the predictive value of remnant cholesterol (RC) for assessing CVD risk in RA patients. Plasma RC levels were measured in 114 RA patients and 41 healthy controls, calculated as total cholesterol minus HDL-C and LDL-C. These levels were further analyzed using 1H-NMR lipid/metabolomics. Meanwhile, the 28-joint Disease Activity Score (DAS28) assessed RA activity. RC levels were significantly elevated in RA patients (19.0 mg/dl, p < 0.001) compared to healthy controls (14.5 mg/dl). Furthermore, RC levels were significantly elevated at 37.4 mg/dl in patients who experienced cardiovascular event (CVE) compared to 17.4 mg/dl in those without CVE (p < 0.001). To enhance the precision and reliability of RC measurements, RC concentrations were further validated using 1H-NMR spectroscopy. Additionally, a positive correlation was observed between RC levels and DAS28. Multivariate analysis identified RC as a significant predictor of CVE (odds ratio = 1.82, p = 0.013). ROC curve analysis revealed superior predictive capability of RC for CVE (AUC = 0.919, p < 0.001) compared to LDL-C (AUC = 0.669, p = 0.018), with a high sensitivity of 94.7% and a specificity of 82.1%. Elevated RC levels demonstrate greater accuracy in predicting CVE occurrence in RA patients compared to traditional measures such as LDL-C. These findings suggest that elevated RC levels may serve as a novel predictor for occurrence of CVE in RA patients, facilitating early intervention strategies based on the risk stratification.

General practitioner support needs to implement cardiovascular disease risk assessment and management guidelines: Qualitative interviews.

Previous research identified numerous barriers to general practitioner (GP) use of cardiovascular disease (CVD) risk guidelines, and it is unclear whether these issues have been resolved. This study explored recent GP experiences. Interviews with 18 GPs in an Australian state with relatively few COVID-19 cases in 2021 were transcribed and coded using a framework analysis approach, with data mapped to five previously identified CVD risk assessment strategies: absolute risk focused, absolute risk adjusted, clinical judgement, passive disregard and active disregard. GPs used various CVD risk calculators to inform clinical decision making, but there were concerns about accuracy, the role of extra risk factors and less 'personalised' assessment. GPs addressed these concerns by requesting additional tests, subjectively adjusting the CVD risk assessment to account for extra risk factors and focusing on individual risk factors. Many barriers to CVD risk assessment guidelines remain. GP support is needed to implement revised guidelines.

O84 BLOOD PRESSURE MEASUREMENT VIA IMPEDANCE CARDIOGRAPHY: AN ARTIFICIAL INTELLIGENCE BASED PROOF-OF-CONCEPT

Objective: Accurate blood pressure (BP) measurement is crucial for the diagnosis, risk assessment, treatment decision-making, and monitoring of cardiovascular diseases. Unfortunately, the gold-standard, cuff-based BP measurement suffer from inaccuracies and discomfort. As a result, continuous, cuff-less, and non-invasive BP assessment methods are merging as promising alternatives. This study is the first to comprehensively assess impedance cardiography (ICG) for Machine Learning enabled BP measurement. Methods: We analysed ICG data from 71 young and healthy adults. Nine different Machine Learning algorithms were evaluated for their BP estimation performance. Accuracy measures comprised mean difference, standard deviation, Limits of Agreement, mean absolute error, and root mean squared error. Additionally, the B-Score was calculated to evaluate the “true”, relative performance of the best-performing model. Results: The Multi-Linear Regression model showed the highest performance (mean difference = -0.01, r = 0.82) for systolic BP. The Support Vector Regressor model achieved the best results (mean difference = 0.15, r = 0.51) for diastolic BP. Both models exhibited positive B-Scores, indicative of their predictive capability. All tested models’ estimations correlated with both systolic and diastolic reference BP (r &gt; 0.72 / r &gt; 0.34, p &lt; 0.001). Conclusion: The study highlights the potential of ICG based Machine Learning algorithms for accurately estimating arterial BP. Such algorithms can provide accurate and continuous BP data. This offers the possibility of enhancing patient care, timely diagnostics, and treatment decision-making. Our approach is especially promising for post-surgical and intensive care environments.

Novel metabolic indicators and the risk of cardiovascular disease in patients with hypertension: A primary-care cohort study

Background and aimsData are limited on whether several easily measured indices serve as effective tools for Cardiovascular disease (CVD) risk assessment in hypertensive patients. This study aimed to assess the associations of metabolic score for insulin resistance (METS-IR), lipid accumulation product (LAP), and visceral adiposity index (VAI) with CVD risk in hypertensive patients. Methods and resultsOur data were drawn from the medical records of primary-care institutions in China. The present study included 306,680 individuals with hypertension attending primary healthcare centers. Cox regression analyses were applied to assess the associations of novel metabolic indicators with the risk of CVD. During a median follow-up of 1.98 years, 5820 participants developed CVD. When comparing with the lowest quartile of the indices, the highest quartile of METS-IR, LAP, and VAI was associated with 1.25-fold (95 % CI: 1.16–1.35), 1.15-fold (95 % CI: 1.05–1.25), and 1.19-fold (95 % CI: 1.10–1.28) risk of CVD after adjusting for potential confounders. ConclusionThis study provided additional evidence that novel metabolic indicators like METS-IR, LAP, and VAI were associated with the risk of CVD. These results suggest that proactive assessment of visceral adiposity and insulin resistance could be helpful for the effective clinical management of the hypertensive population.