Use of Risk Assessment Tools to Guide Decision-Making in the Primary Prevention of Atherosclerotic Cardiovascular Disease: A Special Report From the American Heart Association and American College of Cardiology

Cardiovascular disease risk assessment in patients with rheumatoid arthritis: A scoping review

Patients with rheumatoid arthritis (RA) have an increased risk of developing cardiovascular disease (CVD). Identification of at-risk patients is paramount to initiate preventive care and tailor treatments accordingly. Despite international guidelines recommending all patients with RA undergo CVD risk assessment, rates remain suboptimal. The objectives of this review were to map the strategies used to conduct CVD risk assessments in patients with RA in routine care, determine who delivers CVD risk assessments, and identify what composite measures are used. The Joanna Briggs Institute methodological guidelines were used. A literature search was conducted in electronic and grey literature databases, trial registries, medical clearing houses, and professional rheumatology organisations. Findings were synthesised narratively. A total of 12 studies were included. Strategies reported in this review used various system-based interventions to support delivery of CVD risk assessments in patients with RA, operationalised in different ways, adopting two approaches: (a) multidisciplinary collaboration, and (b) education. Various composite measures were cited in use, with and without adjustment for RA. Results from this review demonstrate that although several strategies to support CVD risk assessments in patients with RA are cited in the literature, there is limited evidence to suggest a standardised model has been applied to routine care. Furthermore, extensive evidence to map how health care professionals conduct CVD risk assessments in practice is lacking. Research needs to be undertaken to establish the extent to which healthcare professionals are CVD risk assessing their patients with RA in routine care. Key Points • A limited number of system-based interventions are in use to support the delivery of CVD risk assessments in patients with RA. • Multidisciplinary team collaboration, and education are used to operationalise interventions to support Health Care Professionals in conducting CVD risk assessments in practice. • The extent to which Health Care Professionals are CVD risk assessing their patients with RA needs to be established.

Atherosclerotic cardiovascular disease risk among Ghanaians: A comparison of the risk assessment tools

Objectives

Risk stratification is a cornerstone for preventing atherosclerotic cardiovascular disease (ASCVD). Ghana has yet to develop a locally derived and validated ASCVD risk model. A critical first step towards this goal is assessing how the commonly available risk models perform in the Ghanaian population. This study compares the agreement and correlation between four ASCVD risk assessment models commonly used in Ghana.

Methods

The Ghana Heart Study collected data from four regions in Ghana (Ashanti, Greater Accra, Northern, and Central regions) and excluded people with a self-declared history of ASCVD. The 10-year fatal/non-fatal ASCVD risk of participants aged 40-74 was calculated using mobile-based apps for Pooled Cohort Equation (PCE), laboratory-based WHO/ISH CVD risk, laboratory-based Framingham risk (FRS), and Globorisk, categorizing them as low, intermediate, or high risk. The risk categories were compared using the Kappa statistic and Spearman correlation.

Results

A total of 615 participants were included in this analysis (median age 55 [Inter quartile range 46, 64]) years with 365 (59.3 %) females. The WHO/ISH risk score categorized 504 (82.0 %), 58 (9.4 %), and 53 (8.6 %) as low-, intermediate-, and high-risk, respectively. The PCE categorized 345 (56.1 %), 181 (29.4 %), and 89 (14.5 %) as low-, intermediate- and high-risk, respectively. The Globorisk categorized 236 (38.4 %), 273 (44.4 %), and 106 (17.2 %) as low-, intermediate-, and high-risk, respectively. Significant differences in the risk categorization by region of residence and age group were noted. There was substantial agreement between the PCE vs FRS (Kappa = 0.8, 95 % CI 0.7 - 0.8), PCE vs Globorisk (Kappa = 0.6; 95 % CI 0.6 - 0.7), and FRS vs Globorisk (Kappa = 0.6; 95 % CI 0.6 - 0.7). However, there was only fair agreement between the WHO vs Globorisk (Kappa = 0.3; 95 % CI 0.3-0.4) and moderate agreement between the WHO vs PCE and WHO vs FRS.

Conclusion

There are significant differences in the ASCVD risk prediction tools in the Ghanaian population, posing a threat to primary prevention. Therefore, there is a need for locally derived and validated tools.

Polygenic risk and incident coronary heart disease in a large multiethnic cohort

Objective

Many studies support the notion that polygenic risk scores (PRS) improve risk prediction for coronary heart disease (CHD) beyond conventional risk factors. However, PRS are not yet considered risk-enhancing factor in guidelines. Our objective was to determine the predictive performance of a commercially available PRS (CARDIO inCode-Score®) compared with the Pooled Cohorts Equations (PCE) in a contemporary, multi-ethnic cohort.

Methods

Participants (n = 63,070; 67 % female; 18 % non-European) without prior CHD were followed from 2007 through 12/31/2022. The association between the PRS and incident CHD was assessed using Cox regression adjusting for genetic ancestry and risk factors. Event rates were estimated by categories of PCE and by low/intermediate/high genetic risk within PCE categories; risk discrimination and net reclassification improvement (NRI) were also assessed.

Results

There were 3,289 incident CHD events during 14 years of follow-up. Adjusted hazard ratio (aHR) for incident CHD per 1 SD increase in PRS was 1.18 (95 % CI:1.14-1.22), and the aHR for the upper vs lower quintile of the PRS was 1.66 (95 % CI:1.49-1.86). The association was consistent in both sexes, in European participants compared with all minority groups combined and was strongest in the first 5 years of follow-up. The increase in the C-statistic was 0.004 (0.747 vs. 0.751; p < 0.0001); the NRI was 2.4 (0.9-3.8) for the entire cohort and 9.7 (7.5-12.0) for intermediate PCE risk individuals. After incorporating high genetic risk, a further 10 percent of participants at borderline/intermediate PCE risk would be candidates for statin therapy.

Conclusion

Inclusion of polygenic risk improved identification of primary prevention individuals who may benefit from more intensive risk factor modification.

High lipoprotein(a): Actionable strategies for risk assessment and mitigation

High levels of lipoprotein(a) [Lp(a)] are causal for atherosclerotic cardiovascular disease (ASCVD). Lp(a) is the most prevalent inherited dyslipidemia and strongest genetic ASCVD risk factor. This risk persists in the presence of at target, guideline-recommended, LDL-C levels and adherence to lifestyle modifications. Epidemiological and genetic evidence supporting its causal role in ASCVD and calcific aortic stenosis continues to accumulate, although various facets regarding Lp(a) biology (genetics, pathophysiology, and expression across race/ethnic groups) are not yet fully understood. The evolving nature of clinical guidelines and consensus statements recommending universal measurements of Lp(a) and the scientific data supporting its role in multiple disease states reinforce the clinical merit to start population screening for Lp(a) now. There is a current gap in the implementation of recommendations for primary and secondary cardiovascular disease (CVD) prevention in those with high Lp(a), in part due to a lack of protocols for management strategies. Importantly, targeted apolipoprotein(a) [apo(a)]-lowering therapies that reduce Lp(a) levels in patients with high Lp(a) are in phase 3 clinical development. This review focuses on the identification and clinical management of patients with high Lp(a). Specifically, we highlight the clinical value of measuring Lp(a) and its use in determining Lp(a)-associated CVD risk by providing actionable guidance, based on scientific knowledge, that can be utilized now to mitigate risk caused by high Lp(a).

Flexible cost-penalized Bayesian model selection: Developing inclusion paths with an application to diagnosis of heart disease

We propose a Bayesian model selection approach that allows medical practitioners to select among predictor variables while taking their respective costs into account. Medical procedures almost always incur costs in time and/or money. These costs might exceed their usefulness for modeling the outcome of interest. We develop Bayesian model selection that uses flexible model priors to penalize costly predictors a priori and select a subset of predictors useful relative to their costs. Our approach (i) gives the practitioner control over the magnitude of cost penalization, (ii) enables the prior to scale well with sample size, and (iii) enables the creation of our proposed inclusion path visualization, which can be used to make decisions about individual candidate predictors using both probabilistic and visual tools. We demonstrate the effectiveness of our inclusion path approach and the importance of being able to adjust the magnitude of the prior's cost penalization through a dataset pertaining to heart disease diagnosis in patients at the Cleveland Clinic Foundation, where several candidate predictors with various costs were recorded for patients, and through simulated data.

Patients' and physicians' beliefs and attitudes towards integrating personalized risk estimates into patient education about left ventricular assist device therapy

BACKGROUND

Personalized risk (PR) estimates may enhance clinical decision making and risk communication by providing individualized estimates of patient outcomes. We explored stakeholder attitudes toward the utility, acceptability, usefulness and best-practices for integrating PR estimates into patient education and decision making about Left Ventricular Assist Device (LVAD).

METHODS AND RESULTS

As part of a 5-year multi-institutional AHRQ project, we conducted 40 interviews with stakeholders (physicians, nurse coordinators, patients, and caregivers), analyzed using Thematic Content Analysis. All stakeholder groups voiced positive views towards integrating PR in decision making. Patients, caregivers and coordinators emphasized that PR can help to better understand a patient's condition and risks, prepare mentally and logistically for likely outcomes, and meaningfully engage in decision making. Physicians felt it can improve their decision making by enhancing insight into outcomes, enhance tailored pre-emptive care, increase confidence in decisions, and reduce bias and subjectivity. All stakeholder groups also raised concerns about accuracy, representativeness and relevance of algorithms; predictive uncertainty; utility in relation to physician's expertise; potential negative reactions among patients; and overreliance.

CONCLUSION

Stakeholders are optimistic about integrating PR into clinical decision making, but acceptability depends on prospectively demonstrating accuracy, relevance and evidence that benefits of PR outweigh potential negative impacts on decision making quality.

Changes in bile acid subtypes and improvements in lipid metabolism and atherosclerotic cardiovascular disease risk: the Preventing Overweight Using Novel Dietary Strategies (POUNDS Lost) trial

BACKGROUND

Distinct circulating bile acid (BA) subtypes may play roles in regulating lipid homeostasis and atherosclerosis.

OBJECTIVES

We investigated whether changes in circulating BA subtypes induced by weight-loss dietary interventions were associated with improved lipid profiles and atherosclerotic cardiovascular disease (ASCVD) risk estimates.

METHODS

This study included adults with overweight or obesity (n = 536) who participated in a randomized weight-loss dietary intervention trial. Circulating primary and secondary unconjugated BAs and their taurine-/glycine-conjugates were measured at baseline and 6 mo after the weight-loss diet intervention. The ASCVD risk estimates were calculated using the validated equations.

RESULTS

At baseline, higher concentrations of specific BA subtypes were related to higher concentrations of atherogenic very low-density lipoprotein lipid subtypes and ASCVD risk estimates. Weight-loss diet-induced decreases in primary BAs were related to larger reductions in triglycerides and total cholesterol [every 1 standard deviation (SD) decrease of glycocholate, glycochenodeoxycholate, or taurochenodeoxycholate was related to β (standard error) -3.3 (1.3), -3.4 (1.3), or -3.8 (1.3) mg/dL, respectively; PFDR < 0.05 for all]. Greater decreases in specific secondary BA subtypes were also associated with improved lipid metabolism at 6 mo; there was β -4.0 (1.1) mg/dL per 1-SD decrease of glycoursodeoxycholate (PFDR =0.003) for changes in low-density lipoprotein cholesterol. We found significant interactions (P-interaction < 0.05) between dietary fat intake and changes in BA subtypes on changes in ASCVD risk estimates; decreases in primary and secondary BAs (such as conjugated cholate or deoxycholate) were significantly associated with improved ASCVD risk after consuming a high-fat diet, but not after consuming a low-fat diet.

CONCLUSIONS

Decreases in distinct BA subtypes were associated with improved lipid profiles and ASCVD risk estimates, highlighting the importance of changes in circulating BA subtypes as significant factors linked to improved lipid metabolism and ASCVD risk estimates in response to weight-loss dietary interventions. Habitual dietary fat intake may modify the associations of changes in BAs with ASCVD risk. This trial was registered at clinicaltrials.gov as NCT00072995.

Low income and education are associated with greater ASCVD risk scores among adults in the US

Introduction

Social determinants of health (SDOH) are fundamental causes of poor cardiovascular health, yet cardiovascular disease (CVD) risk assessment tools exclude SDOH. Our objective was to determine whether SDOH are independently associated with CVD risk in US adults.

Methods

Utilizing the National Health and Nutrition Examination Survey (NHANES), we combined years 1999-2018 and included participants aged 40-79 without history of CVD and with information to calculate CVD risk (n = 21,694). Ten-year risk of atherosclerotic CVD (ASCVD) was calculated using the American Heart Association/American College of Cardiology (AHA/ACC) pooled cohort equations. We used linear regression models to estimate the association between SDOH and ASCVD risk, after adjusting for demographic factors. All analyses accounted for the complex survey design.

Results

Mean age was 54.7 years, with 52.7 % female, 73.8 % non-Hispanic White, 9.4 % non-Hispanic Black, and 10.7 % Hispanic. From adjusted models, compared with an income of ≥ $75 K, ASCVD risk was greater by 3.06 (95 % CI: 2.65, 3.47) among those with income < $25 K, by 1.55 (95 % CI: 1.21, 1.89) among those with income $25 K-<$55 K, and by 1.20 (95 % CI: 0.84, 1.56) among those with income $55 K-<$75 K. Compared to college graduates, ASCVD risk was greater by 3.09 (95 % CI: 2.56, 3.62) among those with less than a high school education, by 1.65 (95 % CI: 1.31, 200) among those who were high school graduates, and by 1.41 (95 % CI: 1.11, 1.72) among those with some college education.

Conclusion

We found strong graded associations between lower income and lower educational attainment with greater CVD risk.

Comparison of the performance of cardiovascular risk prediction tools in rural India: the Rishi Valley Prospective Cohort Study

AIMS

We compared the performance of cardiovascular risk prediction tools in rural India.

METHODS AND RESULTS

We applied the World Health Organization Risk Score (WHO-RS) tools, Australian Risk Score (ARS), and Global risk (Globorisk) prediction tools to participants aged 40-74 years, without prior cardiovascular disease, in the Rishi Valley Prospective Cohort Study, Andhra Pradesh, India. Cardiovascular events during the 5-year follow-up period were identified by verbal autopsy (fatal events) or self-report (non-fatal events). The predictive performance of each tool was assessed by discrimination and calibration. Sensitivity and specificity of each tool for identifying high-risk individuals were assessed using a risk score cut-off of 10% alone or this 10% cut-off plus clinical risk criteria of diabetes in those aged >60 years, high blood pressure, or high cholesterol. Among 2333 participants (10 731 person-years of follow-up), 102 participants developed a cardiovascular event. The 5-year observed risk was 4.4% (95% confidence interval: 3.6-5.3). The WHO-RS tools underestimated cardiovascular risk but the ARS overestimated risk, particularly in men. Both the laboratory-based (C-statistic: 0.68 and χ2: 26.5, P = 0.003) and non-laboratory-based (C-statistic: 0.69 and χ2: 20.29, P = 0.003) Globorisk tools showed relatively good discrimination and agreement. Addition of clinical criteria to a 10% risk score cut-off improved the diagnostic accuracy of all tools.

CONCLUSION

Cardiovascular risk prediction tools performed disparately in a setting of disadvantage in rural India, with the Globorisk performing best. Addition of clinical criteria to a 10% risk score cut-off aids assessment of risk of a cardiovascular event in rural India.

LAY SUMMARY

In a cohort of people without prior cardiovascular disease, tools used to predict the risk of cardiovascular events varied widely in their ability to accurately predict who would develop a cardiovascular event.The Globorisk, and to a lesser extent the ARS, tools could be appropriate for this setting in rural India.Adding clinical criteria, such as sustained high blood pressure, to a cut-off of 10% risk of a cardiovascular event within 5 years could improve identification of individuals who should be monitored closely and provided with appropriate preventive medications.

Development and validation of a deep-learning model to predict 10-year atherosclerotic cardiovascular disease risk from retinal images using the UK Biobank and EyePACS 10K datasets

Background

Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of death globally, and early detection of high-risk individuals is essential for initiating timely interventions. The authors aimed to develop and validate a deep learning (DL) model to predict an individual's elevated 10-year ASCVD risk score based on retinal images and limited demographic data.

Methods

The study used 89,894 retinal fundus images from 44,176 UK Biobank participants (96% non-Hispanic White, 5% diabetic) to train and test the DL model. The DL model was developed using retinal images plus age, race/ethnicity, and sex at birth to predict an individual's 10-year ASCVD risk score using the pooled cohort equation (PCE) as the ground truth. This model was then tested on the US EyePACS 10K dataset (5.8% non-Hispanic White, 99.9% diabetic), composed of 18,900 images from 8969 diabetic individuals. Elevated ASCVD risk was defined as a PCE score of ≥7.5%.

Results

In the UK Biobank internal validation dataset, the DL model achieved an area under the receiver operating characteristic curve of 0.89, sensitivity 84%, and specificity 90%, for detecting individuals with elevated ASCVD risk scores. In the EyePACS 10K and with the addition of a regression-derived diabetes modifier, it achieved sensitivity 94%, specificity 72%, mean error -0.2%, and mean absolute error 3.1%.

Conclusion

This study demonstrates that DL models using retinal images can provide an additional approach to estimating ASCVD risk, as well as the value of applying DL models to different external datasets and opportunities about ASCVD risk assessment in patients living with diabetes.

Public Health Relevance of US EPA Air Quality Index Activity Recommendations

Importance

Reducing exposure to fine particulate matter (<2.5 μm [PM2.5]) air pollution improves cardiopulmonary morbidity and mortality. However, the public health relevance of air quality index (AQI) activity guidelines under present-day environmental conditions in the US has not been critically assessed.

Objective

To evaluate the public health relevance of following PM2.5 AQI activity guidance in preventing serious atherosclerotic cardiovascular disease (ASCVD) and pulmonary events among adults in the US.

Design, Setting, and Participants

This cross-sectional modeling study involved the general adult population and sensitive individuals as designated by the US Environmental Protection Agency (EPA), including adults with preexisting ASCVD or lung disease (asthma or chronic obstructive pulmonary disease). The study was conducted between August 1, 2023, and January 31, 2024.

Exposures

Daily AQI strata for PM2.5 and the corresponding activity recommendations.

Main Outcomes and Measures

The main outcome was the number needed to treat (NNT) per day by following activity guidance across daily AQI strata to prevent 1 serious ASCVD or pulmonary event among relevant populations. To calculate PM2.5-induced excess disease event rates per day, estimated baseline disease-specific daily event rates for each group were multiplied by the increase in risks due to PM2.5 levels at each AQI stratum. The number of events prevented per day was calculated by multiplying each excess disease event rate by the percentage in exposure reduction plausibly incurred by following population-specific activity guidance at each AQI level. The NNT is the reciprocal of the number of events prevented.

Results

The NNT to prevent ASCVD events was high for the general population and for patients with ASCVD across all AQI strata. The range of values was comparatively lower to prevent pulmonary events among adults with lung disease. During most days (96%) when activity recommendations were promulgated due to elevated PM2.5 (AQI, 101-200), the NNT to prevent a serious disease event remained very high for the general population (>18 million), patients with ASCVD (approximately 1.6-5 million), and adults with lung disease (approximately 66 000-202 000).

Conclusions and Relevance

These findings suggest that existing PM2.5 AQI activity recommendations are of questionable public health relevance in present-day conditions and merit consideration for updating to improve their potential effectiveness.

Is LDL cholesterol associated with long-term mortality among primary prevention adults? A retrospective cohort study from a large healthcare system

OBJECTIVES

Among primary prevention-type adults not on lipid-lowering therapy, conflicting results exist on the relationship between low-density lipoprotein cholesterol (LDL-C) and long-term mortality. We evaluated this relationship in a real-world evidence population of adults.

DESIGN

Retrospective cohort study.

SETTING

Electronic medical record data for adults, from 4 January 2000 through 31 December 2022, were extracted from the University of Pittsburgh Medical Center healthcare system.

PARTICIPANTS

Adults without diabetes aged 50-89 years not on statin therapy at baseline or within 1 year and classified as primary prevention-type patients. To mitigate potential reverse causation, patients who died within 1 year or had baseline total cholesterol (T-C) ≤120 mg/dL or LDL-C <30 mg/dL were excluded.

MAIN EXPOSURE MEASURE

Baseline LDL-C categories of 30-79, 80-99, 100-129, 130-159, 160-189 or ≥190 mg/dL.

MAIN OUTCOME MEASURE

All-cause mortality with follow-up starting 365 days after baseline cholesterol measurement.

RESULTS

177 860 patients with a mean (SD) age of 61.1 (8.8) years and mean (SD) LDL-C of 119 (31) mg/dL were evaluated over a mean of 6.1 years of follow-up. A U-shaped relationship was observed between the six LDL-C categories and mortality with crude 10-year mortality rates of 19.8%, 14.7%, 11.7%, 10.7%, 10.1% and 14.0%, respectively. Adjusted mortality HRs as compared with the referent group of LDL-C 80-99 mg/dL were: 30-79 mg/dL (HR 1.23, 95% CI 1.17 to 1.30), 100-129 mg/dL (0.87, 0.83-0.91), 130-159 mg/dL (0.88, 0.84-0.93), 160-189 mg/dL (0.91, 0.84-0.98) and ≥190 mg/dL (1.19, 1.06-1.34), respectively. Unlike LDL-C, both T-C/HDL cholesterol (high-density lipoprotein cholesterol) and triglycerides/HDL cholesterol ratios were independently associated with long-term mortality.

CONCLUSIONS

Among primary prevention-type patients aged 50-89 years without diabetes and not on statin therapy, the lowest risk for long-term mortality appears to exist in the wide LDL-C range of 100-189 mg/dL, which is much higher than current recommendations. For counselling these patients, minimal consideration should be given to LDL-C concentration.

Effects of message framing and risk perception on health communication for optimum cardiovascular disease primary prevention: a protocol for a multicenter randomized controlled study

Background

Although several guidelines for cardiovascular disease (CVD) management have highlighted the significance of primary prevention, the execution and adherence to lifestyle modifications and preventive medication interventions are insufficient in everyday clinical practice. The utilization of effective risk communication can assist individuals in shaping their perception of CVD risk, motivating them to make lifestyle changes, and increasing their willingness to engage with preventive medication, ultimately reducing their CVD risks and potential future events. However, there is limited evidence available regarding the optimal format and content of CVD risk communication.

Objective

The pilot study aims to elucidate the most effective risk communication strategy, utilizing message framing (gain-framed, loss-framed, or no-framed), for distinct subgroups of risk perception (under-perceived, over-perceived, and correctly-perceived CVD risk) through a multi-center randomized controlled trial design.

Methods

A multi-center 3 × 3 factorial, observer-blinded experimental design was conducted. The participants will be assigned into three message-framing arms randomly in a 1:1:1 ratio and will receive an 8-week intervention online. Participants are aged 20-80 years old and have a 10-year risk of absolute CVD risk of at least 5% (moderate risk or above). We plan to enroll 240 participants based on the sample calculation. The primary outcome is the CVD prevention behaviors and CVD absolute risk value. Data collection will occur at baseline, post-intervention, and 3-month follow-up.

Discussion

This experimental study will expect to determine the optimal matching strategy between risk perception subgroups and risk information format, and it has the potential to offer health providers in community or clinic settings a dependable and efficient health communication information template for conducting CVD risk management.Clinical trial registration: https://www.chictr.org.cn/bin/project/edit?pid=207811, ChiCTR2300076337.

Evaluation of Statin Indication and Dose Intensification Among Type 2 Diabetic Patients at a Tertiary Hospital

Background

Diabetes mellitus (DM) increases cardiovascular disease (CVD) incidence and mortality. While guidelines endorse statin use in type 2 DM (T2DM) to mitigate cardiovascular risks and mortality, challenges like statin initiation and prompt treatment adjustments affect patient outcomes. This study aimed to assess the appropriateness of indications for and dose intensification of statin therapy among T2DM patients at Tikur Anbessa Specialized Hospital (TASH).

Methodology

A hospital-based cross-sectional study was conducted from April 1 to June 30 2020. In total, 405 T2DM patients were selected using a systematic random sampling technique. The data were analyzed using SPSS version 26.0. An adjusted odds ratio (OR) was used and a 95% confidence interval (CI) and p-values of <0.05 were utilized to determine statistical significance.

Results

Of the total 405 participants, 346 (85.4%) started taking statins for primary or secondary prevention purposes. Indication for statin use was appropriate in 96.2% patients, while for 216 (62.4%) patients their doses were appropriately intensified. Predictors of the inappropriateness of statin use were an atherosclerotic cardiovascular disease (ASCVD) score of ≥7.5% (AOR=0.28; 95% CI: 0.102-0.738, p=0.01), the presence of dyslipidemia (AOR=4.48; 95% CI: 1.85-10.84; p=0.001), initiation of aspirin therapy (AOR=3.7; 95% CI: 1.522-9.144; p=0.004), and an LDL-cholesterol level of 70-189 mg/dL (AOR=0.124; 95% CI: 0.042-0.365; p=0.001). DM duration of ≥10 years (AOR=2.51; 95% CI: 1.35-4.66, p=0.004), male gender (AOR=2.04; 95% CI: 1.16-3.58, p=0.013), age ≥65 years (AOR=2.15; 95% CI: 1.23-3.75, p=0.007) and uncontrolled blood pressure (AOR=2.09; 95% CI: 1.07-4.08, p=0.031) were associated with inappropriate statin intensification.

Conclusion

The study found that indication of statins was optimal and about two-thirds of patients had their doses appropriately intensified. Monitoring is needed to avoid inappropriate intensification of statin therapy, particularly in patients with longer diabetes duration, those of male gender and advanced age, and those with uncontrolled blood pressure.

Biomarkers of Cardiovascular Risk in Patients With Rheumatoid Arthritis: Results From the TARGET Trial

Cardiovascular disease remains an important comorbidity in patients with rheumatoid arthritis (RA), but traditional models do not accurately predict cardiovascular risk in patients with RA. The addition of biomarkers could improve prediction.

METHODS AND RESULTS

The TARGET (Treatments Against RA and Effect on FDG PET/CT) trial assessed whether different treatment strategies in RA differentially impact cardiovascular risk as measured by the change in arterial inflammation on arterial target to background ratio on fluorodeoxyglucose positron emission tomography/computed tomography scans conducted 24 weeks apart. A group of 24 candidate biomarkers supported by prior literature was assessed at baseline and 24 weeks later. Longitudinal analyses examined the association between baseline biomarker values, measured in plasma EDTA, and the change in arterial inflammation target to background ratio. Model fit was assessed for the candidate biomarkers only, clinical variables only, and models combining both. One hundred nine patients with median (interquartile range) age 58 years (53-65 years), RA duration 1.4 years (0.5-6.6 years), and 82% women had biomarkers assessed at baseline and follow-up. Because the main trial analyses demonstrated significant target to background ratio decreases with both treatment strategies but no difference across treatment groups, we analyzed all patients together. Baseline values of serum amyloid A, C-reactive protein, soluble tumor necrosis factor receptor 1, adiponectin, YKL-40, and osteoprotegerin were associated with significant change in target to background ratio. When selected candidate biomarkers were added to the clinical variables, the adjusted R2 improved from 0.20 to 0.33 (likelihood ratio P=0.0005).

CONCLUSIONS

A candidate biomarker approach identified several promising biomarkers that associate with baseline and treatment-associated changes in arterial inflammation in patients with RA. These will now be tested in an external validation cohort.

A detection system for serum cholesterol based on the fluorescence color detection of beta-cyclodextrin-capped gold nanoclusters

Cholesterol is one of the major markers for cardiovascular diseases. Herein, a portable cholesterol measurement system based on fluorescence color detection was constructed by combining the high sensitivity of fluorescence analysis with the ease of color sensing to determine low levels of serum cholesterol. Cyclodextrin capping gold nanoclusters with blue-green emission were used as fluorescent probes because cholesterol exposure induced fluorescence enhancement of the probe due to the host-guest inclusion interaction between cholesterol and the cavity of cyclodextrin. The integrated sensing system consisted of modules including a microprocessor, a power supply, an LED light with a constant current source, an RGB color sensor, a display, and a darkroom. All the modules except the display screen were placed in a 3D printing darkroom to avoid interference from ambient light. An RGB color sensor TCS230 was applied to capture the RGB signals of the fluorescent color of the probe solution before and after cholesterol addition. Then the obtained RGB signals were converted into the signals in Hue, Saturation, and Value (HSV) color space with a central control chip STM32F407. The Hue value of the fluorescent color of the solution can discriminate the concentration change of cholesterol. Experimental results demonstrate that the system responds linearly to cholesterol in the concentration range of 20.00 ∼ 150.00 μmol·L-1 with a detection limit of 16.07 μmol·L-1 (3σ, n = 3). The detection of the system has good consistency and accuracy compared with the standard instrument, showing potential for the detection of low levels of serum cholesterol.

Development and Validation of the American Heart Association's PREVENT Equations

BACKGROUND

Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD.

METHODS

The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets.

RESULTS

Among 6 612 004 adults included, mean±SD age was 53±12 years, and 56% were women. Over a mean±SD follow-up of 4.8±3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81-1.16) and 0.94 (0.81-1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD- and heart failure-specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004-0.005] and 0.005 [0.004-0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84-1.20] versus 1.39 [1.14-1.65]; P=0.01).

CONCLUSIONS

PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.

Applications of digital health approaches for cardiometabolic diseases prevention and management in the Western Pacific region

Cardiometabolic diseases (CMDs) are the major types of non-communicable diseases, contributing to huge disease burdens in the Western Pacific region (WPR). The use of digital health (dHealth) technologies, such as wearable gadgets, mobile apps, and artificial intelligence (AI), facilitates interventions for CMDs prevention and treatment. Currently, most studies on dHealth and CMDs in WPR were conducted in a few high- and middle-income countries like Australia, China, Japan, the Republic of Korea, and New Zealand. Evidence indicated that dHealth services promoted early prevention by behavior interventions, and AI-based innovation brought automated diagnosis and clinical decision-support. dHealth brought facilitators for the doctor-patient interplay in the effectiveness, experience, and communication skills during healthcare services, with rapidly development during the pandemic of coronavirus disease 2019. In the future, the improvement of dHealth services in WPR needs to gain more policy support, enhance technology innovation and privacy protection, and perform cost-effectiveness research.

Uncovering a dose-response relationship between positive fecal immunochemical test (FIT) and all-cause, cardiovascular and cancer-related mortality

BACKGROUND

Fecal immunochemical test (FIT) is for colorectal cancer (CRC) screening. Its association with non-CRC mortality has been overlooked. Given the quantitative FIT values, its dose-response relationships with different causes of deaths and years of life shortened were assessed.

METHODS

This retrospective study included 546,214 adults aged ≥ 20 who attended a health surveillance program from 1994 to 2017 and were followed up until the end of 2020. FIT ≥ 20 μg Hb/g was defined as positive. The Cox model was used to assess adjusted hazard ratios (aHR).

RESULTS

Positive FIT was associated with increased all-cause mortality (aHR: 1.34, 95 % CI: 1.25-1.44) and all-cancer mortality (aHR: 1.71, 95 % CI: 1.55-1.89), with a reduction of life expectancy by 4 years. The association remained even with CRC excluded. With each 10 μg Hb/g increase in FIT above 20 μg Hb/g, life expectancy was reduced by one year, and mortality increased by 4 %. About 18.6 % of deaths with positive FIT were attributed to cardiovascular disease (CVD), followed by CRC (13.5 %) and upper gastrointestinal (GI) cancers (4.5 %). The all-cause mortality rate after excluding CRC for positive FIT was 3.56/1,000 person-year, comparable to the all-cause mortality rate of 3.69/1,000 person-year for hypertension.

CONCLUSION

Positive FIT was associated with increased mortality in a dose-response manner and shortened life expectancy by 4 years, an overlooked risk comparable to hypertension, even with CRC excluded. After a negative colonoscopy, subjects with positive FIT should undergo a workup on CVD risk factors and look for other upper GI cancers.

Differences and Disparities Among Self-Referred and Physician-Referred Populations Undergoing Coronary Artery Calcium Scanning

BACKGROUND

Coronary artery calcium computed tomography (CAC) is an important tool for identifying subclinical atherosclerosis and cardiovascular risk stratification. Despite robust evidence and inclusion in current guidelines, CAC is considered investigational by some US insurance carriers and requires out-of-pocket expenses. CAC can be obtained via self-referral (SR) or physician referral (PR). We aimed to examine differences in patient, socioeconomic, and CAC characteristics between referral groups.

METHODS

We evaluated demographic, medical history, and CAC results of consecutive patients with a CAC completed at one of multiple Wisconsin sites from March 1, 2019, to June 30, 2021. We separated patients into SR and PR groups. Through census data, we analyzed socioeconomic variables at the block level including race and ethnicity, median income, average household size, and high school completion in the areas where patients resided at the time of CAC.

RESULTS

The final analysis included 19 726 patients: 13 835 (70.1%) PR and 5891 (29.9%) SR. Most patients in both groups were White (95.2% versus 95.1%), with the Black/African American population representing 2.7% (SR) and 2.3% (PR). The PR group had a higher prevalence of cardiovascular risk factors. SR patients were more likely to have a score of 0 (41.2% versus 38.1%; P<0.001); PR patients had a higher prevalence of CAC >300 (16.8% versus 14.8%; P<0.001). SR patients were more likely to be women (55.1% versus 48.9%; P<0.001) and were found to live in higher income areas (19.5% versus 16.4%; P<0.001). Patients from low-income areas comprised the smallest proportion in both groups (7.5%).

CONCLUSIONS

Patients who obtain out-of-pocket CAC live predominantly in medium- and high-income areas, and patients from lower income locations are less likely to obtain CAC despite having more cardiovascular disease risk factors. Consideration should be made from a policy perspective to promote health equity and improve utilization of CAC testing among underrepresented groups.

Evaluation of the relationship between occupational-specific task performance and measures of physical fitness, cardiovascular and musculoskeletal health in firefighters

INTRODUCTION

Firefighters are required to perform physically strenuous tasks such as hose drags, victim rescues, forcible entries and stair climbs to complete their public safety mission. Occupational-specific tasks are often used to evaluate the ability of firefighters to adequately/safely perform their duties. Depending on the regions, occupational-specific tasks include six to eight individual tasks, which emphasize distinct aspects of their physical fitness, while also requiring different levels of cardiovascular (CVH) and musculoskeletal health (MSH). Therefore, the aim of this study was to evaluate the relationship between specific occupational task performance and measures of physical fitness, cardiovascular and musculoskeletal health.

METHODS

Using a cross-sectional design, 282 full-time male and female firefighters were recruited. A researcher-generated questionnaire and physical measures were used to collect data on sociodemographic characteristics, CVH, MSH and weekly physical activity habits. Physical measures were used to collect data on physical fitness and occupational-specific task performance.

RESULTS

Absolute cardiorespiratory fitness (abV̇O2max), grip strength, leg strength, push-ups, sit-ups and lean body mass (all p < 0.001) had an inverse association with completion times on all occupational-specific tasks. Age was positively related to the performance of all tasks (all p < 0.05). Higher heart rate variability (HRV) was associated with better performance on all tasks (all p < 0.05). Bodyfat percentage (BF%) and diastolic blood pressure were positively associated with the step-up task (p < 0.05). Lower back musculoskeletal injury (LoBMSI), musculoskeletal discomfort (MSD), and lower limb MSD were associated with a decreased odds of passing the step-up. Upper body MSIs (UBMSI), LoBMSIs and Lower back MSD were associated with decreased odds of passing the rescue drag.

CONCLUSION

Firefighters that were taller, leaner, stronger and fitter with a more favourable CVH profile, higher HRV and less musculoskeletal discomfort performed best on all occupational-specific tasks.

10. Cardiovascular Disease and Risk Management: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

The effects of substituting red and processed meat for mycoprotein on biomarkers of cardiovascular risk in healthy volunteers: an analysis of secondary endpoints from Mycomeat

PURPOSE

Mycoprotein is a relatively novel food source produced from the biomass of Fusarium venenatum. It has previously been shown to improve CVD risk markers in intervention trials when it is compared against total meat. It has not hitherto been assessed specifically for benefits relative to red and processed meat.

METHODS

We leveraged samples from Mycomeat, an investigator-blind randomised crossover controlled trial in metabolically healthy male adults (n = 20), randomised to consume 240 g/day of red and processed meat for 14 days followed by mycoprotein, or vice versa. Blood biochemical indices were a priori defined secondary endpoints.

RESULTS

Mycoprotein consumption led to a 6.74% reduction in total cholesterol (P = 0.02) and 12.3% reduction in LDL cholesterol (P = 0.02) from baseline values. Change in fasted triglycerides was not significantly different between diets (+ 0.19 ± 0.11 mmol/l with mycoprotein, P = 0.09). There was a small but significant reduction in waist circumference for mycoprotein relative to meat (- 0.95 ± 0.42 cm, P = 0.04). Following the mycoprotein diet, mean systolic (- 2.41 ± 1.89 mmHg, P = 0.23) and diastolic blood pressure (- 0.80 ± 1.23 mmHg, P = 0.43) were reduced from baseline. There were no statistically significant effects of the intervention on urinary sodium, nitrite or TMAO; while urinary potassium (+ 126.12 ± 50.30 mmol/l, P = 0.02) and nitrate (+ 2.12 ± 0.90 mmol/l, P = 0.04) were both significantly higher with mycoprotein relative to meat. The study population comprised metabolically healthy adults, therefore, changes in plasma lipids had little effect on cardiovascular risk scores (- 0.34% FRS for mycoprotein P = 0.24).

CONCLUSIONS

These results confirm potential cardiovascular benefits when displacing red and processed meat with mycoprotein in the diet. Longer trials in higher risk study populations are needed to fully elucidate suggested benefits for blood pressure and body composition.

CLINICALTRIALS

gov Identifier: NCT03944421.

The predictive accuracy of coronary heart disease risk prediction models in rural Northwestern China

Cardiovascular risk models developed may have limitations when applied to rural Chinese. This study validated and compared the Framingham Risk Score (FRS) and Prediction for Atherosclerotic Cardiovascular Disease Risk in China (PAR) models in predicting 10-year risk of coronary heart disease (CHD) in a rural cohort in Ningxia, China from 2008 to 2019. The FRS and PAR models were validated by estimating predicted events, C index, calibration χ2 and plots. 1381 adults without CHD at baseline were followed up for 9.75 years on average. 168 CHD cases were observed. The FRS and PAR underestimated CHD events by 22 % and 46 % for the total population, while overestimated for males by 152 % and 78 %, respectively. The C index was slightly higher for PAR than FRS. Both models showed weak calibration with chi-square values above 20 (p < 0.001). Bland-Altman plots indicated FRS predicted higher CHD risk than PAR, lacking consistency. Overall, FRS and PAR demonstrated limited performance in predicting 10-year CHD risk in this rural population. PAR had slightly better discrimination than FRS, but require further improvement in calibration and individual risk estimation to suit the rural population in Northwest China.

A Synopsis of the Evidence for the Science and Clinical Management of Cardiovascular-Kidney-Metabolic (CKM) Syndrome: A Scientific Statement From the American Heart Association

A growing appreciation of the pathophysiological interrelatedness of metabolic risk factors such as obesity and diabetes, chronic kidney disease, and cardiovascular disease has led to the conceptualization of cardiovascular-kidney-metabolic syndrome. The confluence of metabolic risk factors and chronic kidney disease within cardiovascular-kidney-metabolic syndrome is strongly linked to risk for adverse cardiovascular and kidney outcomes. In addition, there are unique management considerations for individuals with established cardiovascular disease and coexisting metabolic risk factors, chronic kidney disease, or both. An extensive body of literature supports our scientific understanding of, and approach to, prevention and management for individuals with cardiovascular-kidney-metabolic syndrome. However, there are critical gaps in knowledge related to cardiovascular-kidney-metabolic syndrome in terms of mechanisms of disease development, heterogeneity within clinical phenotypes, interplay between social determinants of health and biological risk factors, and accurate assessments of disease incidence in the context of competing risks. There are also key limitations in the data supporting the clinical care for cardiovascular-kidney-metabolic syndrome, particularly in terms of early-life prevention, screening for risk factors, interdisciplinary care models, optimal strategies for supporting lifestyle modification and weight loss, targeting of emerging cardioprotective and kidney-protective therapies, management of patients with both cardiovascular disease and chronic kidney disease, and the impact of systematically assessing and addressing social determinants of health. This scientific statement uses a crosswalk of major guidelines, in addition to a review of the scientific literature, to summarize the evidence and fundamental gaps related to the science, screening, prevention, and management of cardiovascular-kidney-metabolic syndrome.

Cardiometabolic risk estimation using exposome data and machine learning

BACKGROUND

The human exposome encompasses all exposures that individuals encounter throughout their lifetime. It is now widely acknowledged that health outcomes are influenced not only by genetic factors but also by the interactions between these factors and various exposures. Consequently, the exposome has emerged as a significant contributor to the overall risk of developing major diseases, such as cardiovascular disease (CVD) and diabetes. Therefore, personalized early risk assessment based on exposome attributes might be a promising tool for identifying high-risk individuals and improving disease prevention.

OBJECTIVE

Develop and evaluate a novel and fair machine learning (ML) model for CVD and type 2 diabetes (T2D) risk prediction based on a set of readily available exposome factors. We evaluated our model using internal and external validation groups from a multi-center cohort. To be considered fair, the model was required to demonstrate consistent performance across different sub-groups of the cohort.

METHODS

From the UK Biobank, we identified 5,348 and 1,534 participants who within 13 years from the baseline visit were diagnosed with CVD and T2D, respectively. An equal number of participants who did not develop these pathologies were randomly selected as the control group. 109 readily available exposure variables from six different categories (physical measures, environmental, lifestyle, mental health events, sociodemographics, and early-life factors) from the participant's baseline visit were considered. We adopted the XGBoost ensemble model to predict individuals at risk of developing the diseases. The model's performance was compared to that of an integrative ML model which is based on a set of biological, clinical, physical, and sociodemographic variables, and, additionally for CVD, to the Framingham risk score. Moreover, we assessed the proposed model for potential bias related to sex, ethnicity, and age. Lastly, we interpreted the model's results using SHAP, a state-of-the-art explainability method.

RESULTS

The proposed ML model presents a comparable performance to the integrative ML model despite using solely exposome information, achieving a ROC-AUC of 0.78±0.01 and 0.77±0.01 for CVD and T2D, respectively. Additionally, for CVD risk prediction, the exposome-based model presents an improved performance over the traditional Framingham risk score. No bias in terms of key sensitive variables was identified.

CONCLUSIONS

We identified exposome factors that play an important role in identifying patients at risk of CVD and T2D, such as naps during the day, age completed full-time education, past tobacco smoking, frequency of tiredness/unenthusiasm, and current work status. Overall, this work demonstrates the potential of exposome-based machine learning as a fair CVD and T2D risk assessment tool.

Genetic and clinical factors underlying a self-reported family history of heart disease

AIMS

To estimate how much information conveyed by self-reported family history of heart disease (FHHD) is already explained by clinical and genetic risk factors.

METHODS AND RESULTS

Cross-sectional analysis of UK Biobank participants without pre-existing coronary artery disease using a multivariable model with self-reported FHHD as the outcome. Clinical (diabetes, hypertension, smoking, apolipoprotein B-to-apolipoprotein AI ratio, waist-to-hip ratio, high sensitivity C-reactive protein, lipoprotein(a), triglycerides) and genetic risk factors (polygenic risk score for coronary artery disease [PRSCAD], heterozygous familial hypercholesterolemia [HeFH]) were exposures. Models were adjusted for age, sex, and cholesterol-lowering medication use. Multiple logistic regression models were fitted to associate FHHD with risk factors, with continuous variables treated as quintiles. Population attributable risks (PAR) were subsequently calculated from the resultant odds ratios. Among 166 714 individuals, 72 052 (43.2%) participants reported an FHHD. In a multivariable model, genetic risk factors PRSCAD (OR 1.30, CI 1.27-1.33) and HeFH (OR 1.31, 1.11-1.54) were most strongly associated with FHHD. Clinical risk factors followed: hypertension (OR 1.18, CI 1.15-1.21), lipoprotein(a) (OR 1.17, CI 1.14-1.20), apolipoprotein B-to-apolipoprotein AI ratio (OR 1.13, 95% CI 1.10-1.16), and triglycerides (OR 1.07, CI 1.04-1.10). For the PAR analyses: 21.9% (CI 18.19-25.63) of the risk of reporting an FHHD is attributed to clinical factors, 22.2% (CI% 20.44-23.88) is attributed to genetic factors, and 36.0% (CI 33.31-38.68) is attributed to genetic and clinical factors combined.

CONCLUSIONS

A combined model of clinical and genetic risk factors explains only 36% of the likelihood of FHHD, implying additional value in the family history.

Metformin reduces the risk of developing influenza A virus related cardiovascular disease

This study investigated the drug repositioning potential of metformin for cardiovascular risk due to influenza A virus infection. Statistical analysis was performed to analyze factors related to the risk of death after IAV infection in diabetic patients. Through in vitro and in vivo experiments, the effect of metformin on influenza A virus infection in non-diabetic conditions was analyzed. In logistic regression analysis, influenza vaccination (OR = 0.378, p-value = 0.007, 0.186 < 95% C·I < 0.768) and metformin treatment (OR = 0.380, p-value = 0.016, 0.173 < 95% C·I < 0.835) were associated with a decreased influenza-related mortality in diabetic patients. In vitro and in vivo studies showed that viral replication and influenza A virus-induced cytokine expression were inhibited by metformin. In particular, MCP-1 and IP-10, cytokines related to cell infiltration and cardiovascular disease development, were significantly reduced by metformin under influenza A virus infection condition. As a result, the acute exacerbation of atherosclerosis caused by influenza A virus in mouse aorta was inhibited by metformin. In addition, we found that regulation of AKT/MAPK signaling plays an important role in the mechanism of metformin. In conclusion, we demonstrated the potential and mechanism of metformin as a treatment for acute exacerbation of atherosclerosis caused by influenza A virus infection.

Dynamic assessment of coronary artery during different cardiac cycle in patients with coronary artery disease using coronary CT angiography

INTRODUCTION

To evaluate the effect of the cardiac cycle for the coronary artery opening and coronary stenosis at the plaque to determine the phase of measuring maximum diameters required for coronary artery disease (CAD).

METHODS

This retrospective study assessed data for 208 consecutive patients who underwent coronary computed tomography angiography (CTA). The cross-sectional area and diameters of the opening of the left main coronary artery (LM), left anterior descending branch (LAD), left circumflex branch (LCX) and right coronary artery (RCA), the stenosis rate of involved vessels were measured in 10 cardiac cycles. And all their dynamic changes were estimated by the linear mixed model. The relationship between stenosis rate and opening orifice were analyzed by monofactorial variance.

RESULTS

The opening parameters and stenosis rate of the four main coronary arteries varied within the cardiac cycle (p < .05). The maximum opening area occurred at the 45%-55% phase; The range of stenosis rate varied approximately 11%-14% and the maximum stenosis rate was at the 65% phase. The degree of vascular stenosis for LM, LAD and LCX were not associated with their corresponding opening diameters, but were positively intercorrelation with each other.

CONCLUSION

For patients with CAD, the maximum coronary artery stenosis rate were at 65% phase and the maximum value of coronary artery opening were at 45%-55% phase, which were chosen for the appropriate measurement and evaluation by CTA.

Evaluating Plasma Galectin-3 Levels in Patients With an Increased Risk of Atherosclerotic Cardiovascular Disease Who Underwent Coronary Artery Revascularization

Coronary artery disease (CAD) is a common atherosclerotic cardiovascular disease (ASCVD) associated with significant mortality. Galectin-3 is a novel inflammatory factor implicated in the initiation and progression of atherosclerosis. We aimed to evaluate the association of plasma galectin-3 with the risk of ASCVD and the need for coronary artery revascularization. Patients with angina who underwent coronary angiography were divided into groups per their risk of ASCVD. Patients (n = 385) were stratified into having low (n = 21), moderate (n = 40), high (n = 41), and very high risk (n = 283) for ASCVD. The mean age ± standard error of the mean was 53.9 ± 0.5 years and 73% of patients were men. Plasma galectin-3 levels were higher in patients with CAD than non-CAD primarily in patients with stable and unstable angina. Patients with stable CAD had higher levels of galectin-3 relative to acute coronary syndrome patients. Increased plasma galectin-3 level was associated with increased risk of ASCVD and degree of coronary stenosis. By multivariate analysis, the plasma galectin-3 level was independently associated with increased ASCVD risk and body mass index. Plasma galectin-3 levels were independently higher in patients who underwent percutaneous coronary intervention (PCI) than medically treated patients. In addition, age, male gender, smoking, and diabetes mellitus were associated with PCI. In conclusion, plasma galectin-3 levels are elevated in patients with CAD and associated with increased risk of ASCVD and the need for PCI. Plasma galectin-3 could be used as a potential improving predictor of ASCVD risk and when making therapeutic guidance or selecting patients who underwent PCI when the decision is difficult.

Shared Decision-Making and Cardiovascular Health: A Scientific Statement From the American Heart Association

Shared decision-making is increasingly embraced in health care and recommended in cardiovascular guidelines. Patient involvement in health care decisions, patient-clinician communication, and models of patient-centered care are critical to improve health outcomes and to promote equity, but formal models and evaluation in cardiovascular care are nascent. Shared decision-making promotes equity by involving clinicians and patients, sharing the best available evidence, and recognizing the needs, values, and experiences of individuals and their families when faced with the task of making decisions. Broad endorsement of shared decision-making as a critical component of high-quality, value-based care has raised our awareness, although uptake in clinical practice remains suboptimal for a range of patient, clinician, and system issues. Strategies effective in promoting shared decision-making include educating clinicians on communication techniques, engaging multidisciplinary medical teams, incorporating trained decision coaches, and using tools (ie, patient decision aids) at appropriate literacy and numeracy levels to support patients in their cardiovascular decisions. This scientific statement shines a light on the limited but growing body of evidence of the impact of shared decision-making on cardiovascular outcomes and the potential of shared decision-making as a driver of health equity so that everyone has just opportunities. Multilevel solutions must align to address challenges in policies and reimbursement, system-level leadership and infrastructure, clinician training, access to decision aids, and patient engagement to fully support patients and clinicians to engage in the shared decision-making process and to drive equity and improvement in cardiovascular outcomes.

A deep learning-based electrocardiogram risk score for long term cardiovascular death and disease

The electrocardiogram (ECG) is the most frequently performed cardiovascular diagnostic test, but it is unclear how much information resting ECGs contain about long term cardiovascular risk. Here we report that a deep convolutional neural network can accurately predict the long-term risk of cardiovascular mortality and disease based on a resting ECG alone. Using a large dataset of resting 12-lead ECGs collected at Stanford University Medical Center, we developed SEER, the Stanford Estimator of Electrocardiogram Risk. SEER predicts 5-year cardiovascular mortality with an area under the receiver operator characteristic curve (AUC) of 0.83 in a held-out test set at Stanford, and with AUCs of 0.78 and 0.83 respectively when independently evaluated at Cedars-Sinai Medical Center and Columbia University Irving Medical Center. SEER predicts 5-year atherosclerotic disease (ASCVD) with an AUC of 0.67, similar to the Pooled Cohort Equations for ASCVD Risk, while being only modestly correlated. When used in conjunction with the Pooled Cohort Equations, SEER accurately reclassified 16% of patients from low to moderate risk, uncovering a group with an actual average 9.9% 10-year ASCVD risk who would not have otherwise been indicated for statin therapy. SEER can also predict several other cardiovascular conditions such as heart failure and atrial fibrillation. Using only lead I of the ECG it predicts 5-year cardiovascular mortality with an AUC of 0.80. SEER, used alongside the Pooled Cohort Equations and other risk tools, can substantially improve cardiovascular risk stratification and aid in medical decision making.

Association Between the 10-Year ASCVD Risk Score and COVID-19 Complications Among Healthy Adults (Analysis from the National Cohort COVID Collaborative)

COVID-19 complications have been linked to worse outcomes among patients with established atherosclerotic cardiovascular disease (ASCVD). Less is known about the cumulative consequences of multiple ASCVD risk factors on COVID-19 outcomes. We evaluated the dose-response associations between 10-year ASCVD risk scores and COVID-19 complications. The National COVID-19 Cohort Collaborative collects electronic health record data from over 70 US health systems. Our analysis was limited to patients with positive COVID-19 tests without documented ASCVD events at the time of the first positive test. We evaluated the dose-response associations between 10-year ASCVD risk scores, categorized into categorized as low (<7.5%), intermediate (7.5% to 20.0%), or high (>20.0%), and COVID-19 complications, including hospitalizations and mortality. We reported the outcomes using multivariable-adjusted hazard ratios and 95% confidence intervals (CIs). Our cohort included 120,335 patients with documented positive COVID-19 test results who were free of ASCVD events. The mean age was 51.9 ± 16.1 years, 59.4% were women, 15.3% were Black, and 13.7% were Hispanic/Latino. Overall, 15,363 patients (12.8%) were hospitalized and 2,058 (1.7%) died. Patients at intermediate risk of developing ASCVD were had a 1.49 (95% CI 1.41 to 1.56) increased risk of hospitalization and 1.77 (95% CI 1.76 to 1.79) increased risk of mortality compared with patients at low risk. Patients at high risk had a 2.23 (95% CI 2.10 to 2.38) increased risk of hospitalization and a 5.98 (95% CI 5.93 to 6.03) increased risk of mortality. In conclusion, patients in this nationwide cohort at high risk of developing ASCVD are at substantially greater risk of COVID-19 complications. COVID-19 mitigation efforts should focus on these patient populations.

Cardiovascular Disease in Women: An Update for Nurses

Cardiovascular disease (CVD) is the leading cause of death in women but is often underrecognized and undertreated. Women are more likely to experience delay in treatment and worse outcomes, even though they experience similar symptoms as men. Women are more likely to experience ischemia related to microvascular dysfunction, which is not readily diagnosed by commonly used diagnostic tests. Nurses are ideally positioned to be patient advocates and use evidence-based guidelines to encourage primary prevention and ensure prompt treatment. This paper provides an update on CVD in women for clinical nurses based on the latest research evidence.

Personalised decision making to predict absolute metastatic risk in cutaneous squamous cell carcinoma: development and validation of a clinico-pathological model

Background

Cutaneous squamous cell carcinoma (cSCC) is a common skin cancer, affecting more than 2 million people worldwide yearly and metastasising in 2-5% of patients. However, current clinical staging systems do not provide estimates of absolute metastatic risk, hence missing the opportunity for more personalised treatment advice. We aimed to develop a clinico-pathological model that predicts the probability of metastasis in patients with cSCC.

Methods

Nationwide cohorts from (1) all patients with a first primary cSCC in The Netherlands in 2007-2008 and (2) all patients with a cSCC in 2013-2015 in England were used to derive nested case-control cohorts. Pathology records of primary cSCCs that originated a loco-regional or distant metastasis were identified, and these cSCCs were matched to primary cSCCs of controls without metastasis (1:1 ratio). The model was developed on the Dutch cohort (n = 390) using a weighted Cox regression model with backward selection and validated on the English cohort (n = 696). Model performance was assessed using weighted versions of the C-index, calibration metrics, and decision curve analysis; and compared to the Brigham and Women's Hospital (BWH) and the American Joint Committee on Cancer (AJCC) staging systems. Members of the multidisciplinary Skin Cancer Outcomes (SCOUT) consortium were surveyed to interpret metastatic risk cutoffs in a clinical context.

Findings

Eight out of eleven clinico-pathological variables were selected. The model showed good discriminative ability, with an optimism-corrected C-index of 0.80 (95% Confidence interval (CI) 0.75-0.85) in the development cohort and a C-index of 0.84 (95% CI 0.81-0.87) in the validation cohort. Model predictions were well-calibrated: the calibration slope was 0.96 (95% CI 0.76-1.16) in the validation cohort. Decision curve analysis showed improved net benefit compared to current staging systems, particularly for thresholds relevant for decisions on follow-up and adjuvant treatment. The model is available as an online web-based calculator (https://emc-dermatology.shinyapps.io/cscc-abs-met-risk/).

Interpretation

This validated model assigns personalised metastatic risk predictions to patients with cSCC, using routinely reported histological and patient-specific risk factors. The model can empower clinicians and healthcare systems in identifying patients with high-risk cSCC and offering personalised care/treatment and follow-up. Use of the model for clinical decision-making in different patient populations must be further investigated.

Funding

PPP Allowance made available by Health-Holland, Top Sector Life Sciences & Health, to stimulate public-private partnerships.

Physical fitness, cardiovascular and musculoskeletal health, and occupational performance in firefighters

Introduction

To perform their work efficiently and safely, firefighters should maintain all aspects of physical fitness. Cardiac-related incidents are the leading cause of duty-related deaths in firefighters, and many firefighters have poor musculoskeletal health (MSH) that hinder their occupational performance (OP). Establishing the relationship between physical fitness, cardiovascular health (CVH), MSH and OP may add new insight on the most significant factors influencing OP in firefighters, specifically in the City of Cape Town Fire and Rescue Service (CoCTFS), which had not been studied before. Therefore, the purpose of this study was to investigate whether physical fitness, CVH and MSH were associated with OP in firefighters, in the COCTFRS.

Methods

This cross-sectional study included 283 full-time firefighters aged 20-65 years from Cape Town, South Africa. A researcher-generated questionnaire was used to collect data on sociodemographic characteristics, lifestyle factors and MSH. Physical measures were used to collect information on physical fitness, CVH, and OP [using a physical ability test (PAT)]. Linear and binary logistic regressions, adjusted for age, sex, height and weekly metabolic equivalent minutes (WMETM), multivariate analysis of covariance (MANCOVA), adjusted for age, sex, height and body mass index (BMI) and backward stepwise regressions were used to investigate the associations between the various constructs.

Results

From multivariable analyses, age, lean body mass, body fat percentage (BF%), estimated absolute oxygen consumption (abV̇O2max), grip strength, leg strength, push-ups, sit-ups, WMETM and heart rate variability were associated with PAT completion times (all p < 0.01). The MANCOVA showed a significant difference between performance categories of the PAT based on physical fitness and CVH (both p < 0.001). WMETM, BF%, abV̇O2max, grip strength, leg strength and sit-ups explained the highest proportion (50.5%) of the variation in PAT completion times.

Conclusion

Younger, non-obese, fitter and stronger firefighters, with a better CVH status, performed significantly better and were most likely to pass the PAT in firefighters, in Cape Town, South Africa. Firefighters should maintain high levels of physical fitness and a good level of CVH to ensure a satisfactory level of OP.

Evaluation of Large-Scale Proteomics for Prediction of Cardiovascular Events

Importance

Whether protein risk scores derived from a single plasma sample could be useful for risk assessment for atherosclerotic cardiovascular disease (ASCVD), in conjunction with clinical risk factors and polygenic risk scores, is uncertain.

Objective

To develop protein risk scores for ASCVD risk prediction and compare them to clinical risk factors and polygenic risk scores in primary and secondary event populations.

Design, Setting, and Participants

The primary analysis was a retrospective study of primary events among 13 540 individuals in Iceland (aged 40-75 years) with proteomics data and no history of major ASCVD events at recruitment (study duration, August 23, 2000 until October 26, 2006; follow-up through 2018). We also analyzed a secondary event population from a randomized, double-blind lipid-lowering clinical trial (2013-2016), consisting of individuals with stable ASCVD receiving statin therapy and for whom proteomic data were available for 6791 individuals.

Exposures

Protein risk scores (based on 4963 plasma protein levels and developed in a training set in the primary event population); polygenic risk scores for coronary artery disease and stroke; and clinical risk factors that included age, sex, statin use, hypertension treatment, type 2 diabetes, body mass index, and smoking status at the time of plasma sampling.

Main Outcomes and Measures

Outcomes were composites of myocardial infarction, stroke, and coronary heart disease death or cardiovascular death. Performance was evaluated using Cox survival models and measures of discrimination and reclassification that accounted for the competing risk of non-ASCVD death.

Results

In the primary event population test set (4018 individuals [59.0% women]; 465 events; median follow-up, 15.8 years), the protein risk score had a hazard ratio (HR) of 1.93 per SD (95% CI, 1.75 to 2.13). Addition of protein risk score and polygenic risk scores significantly increased the C index when added to a clinical risk factor model (C index change, 0.022 [95% CI, 0.007 to 0.038]). Addition of the protein risk score alone to a clinical risk factor model also led to a significantly increased C index (difference, 0.014 [95% CI, 0.002 to 0.028]). Among White individuals in the secondary event population (6307 participants; 432 events; median follow-up, 2.2 years), the protein risk score had an HR of 1.62 per SD (95% CI, 1.48 to 1.79) and significantly increased C index when added to a clinical risk factor model (C index change, 0.026 [95% CI, 0.011 to 0.042]). The protein risk score was significantly associated with major adverse cardiovascular events among individuals of African and Asian ancestries in the secondary event population.

Conclusions and Relevance

A protein risk score was significantly associated with ASCVD events in primary and secondary event populations. When added to clinical risk factors, the protein risk score and polygenic risk score both provided statistically significant but modest improvement in discrimination.

Plasma Interleukin-6 (IL-6), Angiopoietin-2, and C-Reactive Protein Levels Predict Subsequent Type 1 Myocardial Infarction in Persons With Treated HIV Infection

BACKGROUND

HIV infection leads to endothelial activation, promoting platelet adhesion, and accelerating atherosclerosis. Our goal was to determine whether biomarkers of endothelial activation and hemostasis/thrombosis were elevated in people with treated HIV (PWH) before myocardial infarction (MI).

METHODS

In a case-control study nested within the CFAR Network of Integrated Clinical Systems (CNICS) cohort, we compared 69 adjudicated cases with type 1 MI with 138 controls matched for antiretroviral therapy regimen. We measured angiopoietin-1, angiopoietin-2 (ANG-2), intercellular adhesion molecule 1 (ICAM-1), vascular cell adhesion molecule 1 (VCAM-1), a disintegrin and metalloproteinase with a thrombospondin type 1 motif, member 13 (ADAMTS13), von Willebrand factor, C-reactive protein (CRP), interleukin-6 (IL-6), plasminogen activation inhibitor-1, P-selectin, serum amyloid-A, soluble CD14, and apolipoprotein A1 in stored plasma. Conditional logistic regression identified associations with subsequent MI, with and without adjustment for Atherosclerotic Cardiovascular Disease (ASCVD) and Veterans Aging Cohort Study (VACS) scores.

RESULTS

Higher IL-6 was associated with MI after adjustment for ASCVD score (adjusted odds ratio [AOR] 1.51, 95% confidence interval [95% CI]: 1.05 to 2.17 per standard-deviation-scaled log 2 increment). In a separate model adjusting for VACS score, higher ANG-2 (AOR 1.49, 95% CI: 1.04 to 2.14), higher CRP (AOR 1.45, 95% CI: 1.06 to 2.00), and higher IL-6 (AOR 1.68, 95% CI: 1.17 to 2.41) were associated with MI. In a sensitivity analysis excluding PWH with viral load ≥400 copies/mL, higher IL-6 remained associated with MI after adjustment for ASCVD score and after adjustment for VACS score.

CONCLUSIONS

Among PWH, higher levels of plasma IL-6, CRP, and ANG-2 predict subsequent type 1 MI, independent of conventional risk scores. IL-6 had the most consistent associations with type 1 MI, regardless of viral load suppression.

Rate of Change in 10-Year Atherosclerotic Cardiovascular Disease Risk and Its Implications for Primary Prevention

BACKGROUND

Contemporary cardiovascular primary prevention is based on the assessment of the 10-year risk of atherosclerotic cardiovascular disease (ASCVD). However, the clinical implications of temporal change in the 10-year ASCVD risk estimate (∆10-year ASCVD risk/year) are unknown.

METHODS

A total of 211 077 participants without established ASCVD and with repetitive 10-year ASCVD risk assessment at an interval of 4 to 5 years were selected from the Korean National Health Insurance Service data. The primary end point was a composite of myocardial infarction, stroke, coronary revascularization, and all-cause death.

RESULTS

ASCVD event rates were proportional to the ∆10-year ASCVD risk/year regardless of the baseline 10-year ASCVD risk. Adjusted hazard ratio for ASCVD events per 1% increase in ∆10-year ASCVD risk/year was 1.53 (95% CI, 1.44-1.63), 1.24 (95% CI, 1.15-1.32), 1.18 (95% CI, 1.13-1.23), and 1.05 (95% CI, 1.00-1.10) in those with a baseline 10-year ASCVD risk of <5%, 5% to 7.5%, 7.5% to 20%, and ≥20%, respectively. Appropriate control of risk factors, including low-density lipoprotein cholesterol, blood pressure, body mass index, exercise habits, and smoking status, was associated with lower ASCVD event rates, whereas failure to control these risk factors resulted in higher ASCVD event rates.

CONCLUSIONS

The temporal change in 10-year ASCVD risk over a period of 4 to 5 years reflects success or failure in controlling major cardiovascular risk factors and indicates the risk of future ASCVD events. The ∆10-year ASCVD risk/year can be used as an indicator of primary prevention and guide the application of preventive measures.

Risk Stratification for Sarcopenic Obesity in Subjects With Nonalcoholic Fatty Liver Disease

BACKGROUND & AIMS

The impact of the severity of sarcopenic obesity (SO) in nonalcoholic fatty liver disease (NAFLD) on the risk of significant liver fibrosis or cardiovascular disease (CVD) remains unclear. We aimed to identify high-risk subjects with SO for significant liver fibrosis or CVD among subjects with SO and NAFLD.

METHODS

This multicenter, retrospective study involved 23,889 subjects with NAFLD who underwent a health screening program (2014-2020). Sarcopenia was defined based on gender-specific sarcopenia index cutoff using multi-frequency bioelectric impedance analysis. High-risk subjects with SO were defined as those with significant liver fibrosis by fibrosis-4 index >2.67 or atherosclerotic CVD risk score >20%. Multivariable logistic regression analysis for identifying high-risk subjects with SO was performed in a cross-sectional cohort with SO, and further validation was performed in a longitudinal cohort.

RESULTS

SO prevalence was 5.4% (n = 1297 of 23,889). Older age (unstandardized beta [β] = 3.23; P < .001), male (β = 1.66; P = .027), sarcopenia index (β = -6.25; P = .019), and metabolic syndrome (β = 1.75; P < .001) were significant risk factors for high-risk SO. Based on a high-risk SO screening model, high-risk subjects with SO had significantly higher odds of significant liver fibrosis (training: adjusted odds ratio [aOR], 3.72; validation: aOR, 2.38) or CVD (training: aOR, 5.20; validation: aOR, 3.71) than subjects without SO (all P < .001). In subgroup analyses, the cumulative incidence of significant liver fibrosis or CVD development was significantly higher in high-risk subjects with SO than in low-risk subjects with SO in a longitudinal cohort considering all-cause mortality and liver transplantation as competing risks (sub-distribution hazard ratio, 5.37; P < .001).

CONCLUSION

The high-risk screening model may enable the identification of high-risk subjects with SO with NAFLD.

Trends in Cardiovascular Health Counseling Among Postpartum Individuals

Importance

Poor prepregnancy cardiovascular health (CVH) and adverse pregnancy outcomes (APOs) are key risk factors for subsequent cardiovascular disease (CVD) in birthing adults. The postpartum visit offers an opportunity to promote CVH among at-risk individuals.

Objective

To determine prevalence, predictors, and trends in self-reported CVH counseling during the postpartum visit.

Design, Setting, and Participants

Serial, cross-sectional analysis of data from 2016-2020 from the Pregnancy Risk Assessment Monitoring System (PRAMS), a nationally representative, population-based survey. The primary analysis included individuals who attended a postpartum visit 4 to 6 weeks after delivery with available data on receipt of CVH counseling, self-reported prepregnancy CVD risk factors (obesity, diabetes, and hypertension), and APOs (gestational diabetes, hypertensive disorders of pregnancy, and preterm birth) (N = 167 705 [weighted N = 8 714 459]).

Exposures

Total number of CVD risk factors (0, 1, or ≥2 prepregnancy risk factors or APOs).

Main Outcomes and Measures

Annual, age-adjusted prevalence of self-reported postpartum CVH counseling per 100 individuals, defined as receipt of counseling for healthy eating, exercise, and losing weight gained during pregnancy, was calculated overall and by number of CVD risk factors. Average annual percent change (APC) assessed trends in CVH counseling from 2016 through 2020. Data were pooled to calculate rate ratios (RRs) for counseling that compared individuals with and without CVD risk factors after adjustment for age, education, postpartum insurance, and delivery year.

Results

From 2016 through 2020, prevalence of self-reported postpartum CVH counseling declined from 56.2 to 52.8 per 100 individuals among those with no CVD risk factors (APC, -1.4% [95% CI, -1.8% to -1.0%/y]), from 58.5 to 57.3 per 100 individuals among those with 1 risk factor (APC, -0.7% [95% CI, -1.3% to -0.1%/y]), and from 61.9 to 59.8 per 100 individuals among those with 2 or more risk factors (APC, -0.8% [95% CI, -1.3% to -0.3%/y]). Reporting receipt of counseling was modestly higher among individuals with 1 risk factor (RR, 1.05 [95% CI, 1.04 to 1.07]) and with 2 or more risk factors (RR, 1.11 [95% CI, 1.09 to 1.13]) compared with those who had no risk factors.

Conclusions and Relevance

Approximately 60% of individuals with CVD risk factors or APOs reported receiving CVH counseling at their postpartum visit. Prevalence of reporting CVH counseling decreased modestly over 5 years.

Prevalence, awareness, treatment, and risk factor control of high atherosclerotic cardiovascular disease risk in Guangzhou, China

Background

Identifying individuals at high risk of atherosclerotic cardiovascular disease (ASCVD) and implementing targeted prevention strategies might be the key to reducing the heavy disease burden in China. This study aimed to evaluate the prevalence, awareness, treatment, and risk factor control among individuals with high 10-year ASCVD risk in Guangzhou, China.

Methods

This study included 15,165 adults (aged 18 years and older) from 138 urban and rural communities in the 2018 survey of China Chronic Disease and Risk Factors Surveillance in Guangzhou. 10-year ASCVD risk was estimated using the risk assessment models recommended in the Chinese Guideline for the Prevention of Cardiovascular Disease 2017. The prevalence, awareness, treatment, and risk factor control of high ASCVD risk (defined as 10-year risk ≥10%) were examined.

Results

Among the study population, the weighted proportion of men was 51.9%, and the mean age was 41.27 ± 0.52 years. The overall standardized prevalence of high 10-year ASCVD risk was 13.8% (95% CI, 12.4%-15.3%). The awareness rates for hypertension, diabetes, and hyperlipidemia were 48.0% (95% CI, 42.8%-53.4%), 48.3% (95% CI, 43.0%-53.7%), and 17.9% (95% CI, 14.4%-22.1%) among those with corresponding risk factors. The proportions of drug use in prevention were relatively low in primary prevention, with the rates of using BP-lowering, glucose-lowering, lipid-lowering, and aspirin being 37.7% (95% CI, 32.8%-42.8%), 41.4% (95% CI, 35.8%-47.3%), 6.7% (95% CI, 4.5%-10.0%), and 1.0% (95% CI, 0.6%-1.8%), respectively. As for risk factor control, only 29.3% (95% CI, 25.7%-33.2%), 16.8% (95% CI, 15.0%-18.6%), and 36.0% (95% CI, 31.1%-41.2%) of individuals with high ASCVD risk had ideal levels of blood pressure, LDL-C, and body weight.

Conclusion

The estimated prevalence of 10-year high ASCVD risk was high in Guangzhou, while the rates of treatment and risk factor control in primary prevention were still far from optimal, especially for lipid management. These findings suggested that substantial improvement in ASCVD prevention is needed in this population.

Clinical utility of inflammatory and genetic biomarkers for cardiovascular disease prevention, categorization, and treatment

ABSTRACT

The complex interplay of increased atherogenic lipoproteins, inflammation, and immune activation hallmarks the pathogenesis of atherosclerotic cardiovascular disease (ASCVD). Atherosclerotic cardiovascular disease remains a leading cause of death, yet risk estimator tools lack comprehensiveness for genetic/inflammatory biomarkers associated with ASCVD. Unexplained ASCVD risk necessitates a better understanding of primary, secondary, and tertiary prevention variables. This article discusses the clinical utility of genetic and inflammatory biomarkers for ASCVD risk prediction, management, treatment, and recategorization into primary, secondary, and tertiary prevention. Furthermore, nurse practitioners (NPs) should use a ternary prevention classification system instead of the current binary system to mitigate risk in the large group of patients with subclinical ASCVD. High-sensitivity C-reactive protein (hs-CRP)-linearly associated with ASCVD-and lipoprotein-associated phospholipase-A 2 (Lp-PLA 2 ) and myeloperoxidase (MPO), both associated with plaque vulnerability/rupture, are inflammatory biomarkers. Elevated hs-CRP, MPO, and Lp-PLA 2 treatment requires addressing root causes of elevation (e.g., obesity, insulin resistance, tobacco use, gingival disease, and chronic autoimmune/infectious conditions). In addition, haptoglobin (Hp) phenotype determines the antioxidant potential of Hp. Haptoglobin phenotype, a root cause of ASCVD, is a one-time test. Individuals with Hp 2-2 should adopt a gluten-free diet to reduce endothelial and intestinal inflammation. Nurse practitioners should use stricter glycemic goals (hemoglobin A1c ≤6.5%) and add daily vitamin E if this group has type 2 diabetes. Genetic/inflammatory biomarkers should be used to better predict ASCVD risk and tailor primary, secondary, and tertiary prevention treatment. Clinical use of these biomarkers reaches beyond the standard of care to reduce residual ASCVD risk.

Development of a predictive risk stratification tool to identify the population over age 45 at risk for new-onset stroke within 7 years

Background and purpose

With the acceleration of the aging process of society, stroke has become a major health problem in the middle-aged and elderly population. A number of new stroke risk factors have been recently found. It is necessary to develop a predictive risk stratification tool using multidimensional risk factors to identify people at high risk for stroke.

Methods

The study included 5,844 people (age ≥ 45 years) who participated in the China Health and Retirement Longitudinal Study in 2011 and its follow-up up to 2018. The population samples were divided into training set and validation set according to 1:1. A LASSO Cox screening was performed to identify the predictors of new-onset stroke. A nomogram was developed, and the population was stratified according to the score calculated through the X-tile program. Internal and external verifications of the nomogram were performed by ROC and calibration curves, and the Kaplan-Meier method was applied to identify the performance of the risk stratification system.

Results

The LASSO Cox regression screened out 13 candidate predictors from 50 risk factors. Finally, nine predictors, including low physical performance and the triglyceride-glucose index, were included in the nomogram. The nomogram's overall performance was good in both internal and external validations (AUCs at 3-, 5-, and 7-year periods were 0.71, 0.71, and 0.71 in the training set and 0.67, 0.65, and 0.66 in the validation set, respectively). The nomogram was proven to excellently discriminate between the low-, moderate-, and high-risk groups, with a prevalence of 7-year new-onset stroke of 3.36, 8.32, and 20.13%, respectively (P < 0.001).

Conclusion

This research developed a clinical predictive risk stratification tool that can effectively identify the different risks of new-onset stroke in 7 years in the middle-aged and elderly Chinese population.

Machine learning framework for atherosclerotic cardiovascular disease risk assessment

Introduction

Atherosclerotic cardiovascular disease (ASCVD) is the first leading cause of mortality globally. To identify the individual risk factors of ASCVD utilizing the machine learning (ML) approaches.

Materials & methods

This cohort-based cross-sectional study was conducted on data of 500 participants with ASCVD among Tabriz University Medical Sciences employees, during 2020. The data with ML methods were developed and validated to predict ASCVD risk with naive Bayes (NB), spurt vesture machines (SVM), regression tree (RT), k-nearest neighbors (KNN), artificial neural networks (ANN), generalized additive models (GAM), and logistic regression (LR).

Results

Accuracy of the models ranged from 95.7 to 98.1%, with a sensitivity of 50.0 to 97.3%, specificity of 74.3 to 99.1%, positive predictive value (PPV) of 0.0 to 98.0%, negative predictive value (NPV) of 68.4 to 100.0%, positive likelihood ratio (LR +) of 13.8 to 96.4%, negative likelihood ratio (LR-) of 3.6 to 51.9%, and area under ROC curve (AUC) of 62.5 to 99.4%. The ANN fit the data best with an accuracy of 98.1% (95% CI: 96.5-99.1), a specificity of 99.1% (95% CI: 97.7-99.9), a LR + of 96.4% (95% CI: 36.2-258.8), and AUC of 99.4% (95% CI: 85.2-97.0). Based on the optimal model, sex (females), age, smoking, and metabolic syndrome were shown to be the most important risk factors of ASCVD.

Conclusion

Sex (females), age, smoking, and metabolic syndrome were predictors obtained by ANN. Considering the ANN as the optimal model identified, more accurate prevention planning may be designed.

Association of cardiovascular health and risk prediction algorithms with subclinical atherosclerosis identified by carotid ultrasound

Background

The requirement for laboratory tests to assess conventional cardiovascular disease (CVD) risk may be a barrier to the early detection and management of atherosclerosis in some population groups. A simpler risk assessment could facilitate detection of CVD.

Objectives

The association of the Fuster-BEWAT Score (FBS), Framingham Risk Score (FRS), and Pooled Cohort Equation (PCE) with the presence of carotid plaque was investigated, with the intention of developing a stepped screening process for the primary prevention of CVD.

Methods

Asymptomatic participants with a family history of premature CVD had an absolute cardiovascular disease risk (ACVDR) score calculated using the FBS, FRS, and PCE risk equations. This risk classification was compared with the presence or absence of carotid plaque on ultrasound. Prediction of carotid plaque presence by risk scores and risk factors was assessed by logistic regression and area under the curve (AUC) for discrimination and diagnostic performance. A classification and regression-tree (CART) model was obtained for stratification of risk assessment.

Results

Risk score calculation and ultrasound scanning were performed in 1031 participants, of whom 51 had carotid plaques. Participants with plaque and male sex showed higher risk (higher PCE and FRS and lower FBS, as higher scores of FBS indicate better cardiovascular health). Participants ≤50 years of age showed the FBS was a significant predictor; there was a reduced likelihood of plaque presence with a higher score (OR 0.54, 95% CI 0.39-0.75, P < .01). Higher ACVDR (evidenced by higher PCE and FRS scores and lower FBS score) was associated with an increased likelihood of carotid plaque; however, the FBS and the addition of risk factors not included in the equation showed the highest AUC (AUC = 0.76, P < .001). CART modeling showed that participants with FBS between 6 and 9 would be recommended for further risk stratification using the PCE, whereupon a PCE score ≥5% conferred an increased risk and greater possibility for plaque. Validation of the model using a different cohort showed similar risk stratification for plaque presence according to level of risk by CART analysis.

Conclusion

FBS was able to identify the presence of carotid plaque in asymptomatic individuals. Its use for initial risk delineation might improve the selection of patients for more specific and complex assessment, reducing cost and time.

Impact of physician's perception about LDL cholesterol control in clinical practice when treating patients in Spain

BACKGROUND AND AIMS

We aimed to understand the impact of physicians' perception about LDL-cholesterol (LDLc) control on the management of patients with dyslipidemia in Spain.

METHODS

We performed a cross-sectional and multicenter study, in which 435 healthcare professionals participated in face-to-face meetings, collecting qualitative and quantitative information related to hypercholesterolemia management. Additionally, aggregated anonymized data of the last 10 patients with hypercholesterolemia attended by each physician were collected.

RESULTS

A total of 4,010 patients (8%, 13%, 16% and 61% with low, moderate, high, and very high cardiovascular [CV] risk) were included. Physicians' perception was that 62% of their patients attained LDLc goals (66%, 63%, 61% and 56%, for low, moderate, high and very high CV risk, respectively). However, when looking into the data only 31% (vs 62% p<0.01) of patients attained the LDLc goals (47%, 36%, 22% and 25%, respectively). Overall, 33% of patients were taking high intensity statins, 32% statin/ezetimibe, 21% low/moderate intensity statins and 4% PCSK9 inhibitors. These numbers were 38%, 45%, 8% and 6% for very high risk patients and 44%, 21%, 21% and 4% for high CV risk patients. In 32% of patients, a change in lipid lowering therapy was performed after the visit, mainly combining statins/ezetimibe (55%).

CONCLUSIONS

In Spain, most patients with dyslipidemia do not achieve the recommended LDLc goals because of an insufficient intensification of lipid lowering therapy. On the one hand, this is in part due to physicians misperception on preventive LDLc control and the need for repeated advice to patient, and, on the other, to the lack of patient adherence.