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

Microfluidics as diagnostic tools

The challenges in the management of human diseases are largely determined by the precision, speed and ease of diagnostic procedures available. Developments in biomedical engineering technologies have greatly helped in transforming human health care, especially for disease diagnosis which in turn lead to better patient outcomes. One such development is in the form of microfluidic chip technology which has transformed various aspects of human health care. We present in this review, a comprehensive account on the utility of microfluidic chip technologies for the diagnosis of autoimmune disorders, cardiovascular diseases (CVDs), infectious diseases, and neurodegenerative conditions. We have included the diseases posing global threat such as rheumatoid arthritis, diabetes, pernicious anemia, tuberculosis, COVID-19, influenza, alzheimer's, multiple sclerosis, and epilepsy. Apart from discussing the ways of microfluidic chip in diagnosis, we included a section presenting electrochemical, electrical, optical, and acoustic detection technologies for the precise diagnosis of CVDs. Microfluidics platforms have thus revolutionized novel capabilities in addressing the requirements of point-of-care diagnostics enabling miniaturization by integrating multiple laboratory functions into a single chip resulting in "one flow - one solution" systems. Hence, the precision and early diagnoses of diseases are now possible due to the advancements of microfluidics-based technology.

Automatic thoracic aorta calcium quantification using deep learning in non-contrast ECG-gated CT images

Thoracic aorta calcium (TAC) can be assessed from cardiac computed tomography (CT) studies to improve cardiovascular risk prediction. The aim of this study was to develop a fully automatic system to detect TAC and to evaluate its performance for classifying the patients into four TAC risk categories. The method started by segmenting the thoracic aorta, combining three UNets trained with axial, sagittal and coronal CT images. Afterwards, the surrounding lesion candidates were classified using three combined convolutional neural networks (CNNs) trained with orthogonal patches. Image datasets included 1190 non-enhanced ECG-gated cardiac CT studies from a cohort of cardiovascular patients (age 57 ± 9 years, 80% men, 65% TAC > 0). In the test set (N = 119), the combination of UNets was able to successfully segment the thoracic aorta with a mean volume difference of 0.3 ± 11.7 ml (<6%) and a median Dice coefficient of 0.947. The combined CNNs accurately classified the lesion candidates and 87% of the patients (N = 104) were accurately placed in their corresponding risk categories (Kappa = 0.826, ICC = 0.9915). TAC measurement can be estimated automatically from cardiac CT images using UNets to isolate the thoracic aorta and CNNs to classify calcified lesions.

Generalisability of trials on antithrombotic treatment intensification in patients with cardiovascular disease

OBJECTIVE

Assessment of generalisability of guideline-informing trials on antithrombotic treatment intensification to real-world patients with cardiovascular disease (CVD).

METHODS

Inclusion and exclusion criteria of the Cardiovascular Outcomes for People Using Anticoagulation Strategies (COMPASS), Clopidogrel for High Atherothrombotic Risk and Ischemic Stabilization, Management and Avoidance (CHARISMA), Prevention of Cardiovascular events in Patients with Prior Heart Attack Using Ticagrelor Compared to Placebo on a Background of Aspirin-Thrombolysis in Myocardial Infarction (PEGASUS-TIMI) and Dual Antiplatelet Therapy (DAPT) study were applied to coronary artery disease (CAD) and/or peripheral artery disease (PAD) patients from Utrecht Cardiovascular Cohort-Second Manifestations of Arterial Disease (UCC-SMART) to determine real-world eligibility. Eligible and ineligible patients were compared on baseline characteristics, cardiovascular events, major bleeding and mortality.

RESULTS

Eligibility ranged from 11%-94% for CAD to 75%-90% for patients with PAD. Cardiovascular, bleeding and mortality risks were higher in COMPASS-eligible patients with CAD (rate ratios (RR) 1.98 (95% CI 1.74 to 2.26), 2.02 (95% CI 1.47 to 2.78) and 3.11 (95% CI 2.71 to 3.57), respectively) and CHARISMA-eligible patients (RR 1.51 (95% CI 1.12 to 2.06), 2.25 (95% CI 1.01 to 6.21) and 4.43 (95% CI 2.79 to 7.51), respectively), and lower in COMPASS-eligible patients with PAD (RR 0.45 (95% CI 0.36 to 0.56), 0.29 (95% CI 0.18 to 0.46) and 0.45 (95% CI 0.38 to 0.54), respectively) and DAPT-eligible patients with CAD (RR CVD 0.49 (95% CI 0.34 to 0.69) and mortality 0.67 (95% CI 0.48 to 0.94)) than ineligible patients. After adjustment for trial eligibility criteria, only higher cardiovascular and mortality risks in COMPASS-eligible patients with CAD and lower cardiovascular risks in CHARISMA-eligible and DAPT-eligible patients persisted with CAD.

CONCLUSION

A large proportion of contemporary CVD patients would be eligible for intensified antithrombotic treatment trials, with mostly similar adjusted event risks to ineligible patients. Trial-based guideline recommendations are largely applicable to real-world patients.

Nobiletin alleviates atherosclerosis by inhibiting lipid uptake via the PPARG/CD36 pathway

BACKGROUND

Atherosclerosis (AS) is a persistent inflammatory condition triggered and exacerbated by several factors including lipid accumulation, endothelial dysfunction and macrophages infiltration. Nobiletin (NOB) has been reported to alleviate atherosclerosis; however, the underlying mechanism remains incompletely understood.

METHODS

This study involved comprehensive bioinformatic analysis, including multidatabase target prediction; GO and KEGG enrichment analyses for function and pathway exploration; DeepSite and AutoDock for drug binding site prediction; and CIBERSORT for immune cell involvement. In addition, target intervention was verified via cell scratch assays, oil red O staining, ELISA, flow cytometry, qRT‒PCR and Western blotting. In addition, by establishing a mouse model of AS, it was demonstrated that NOB attenuated lipid accumulation and the extent of atherosclerotic lesions.

RESULTS

(1) Altogether, 141 potentially targetable genes were identified through which NOB could intervene in atherosclerosis. (2) Lipid and atherosclerosis, fluid shear stress and atherosclerosis may be the dominant pathways and potential mechanisms. (3) ALB, AKT1, CASP3 and 7 other genes were identified as the top 10 target genes. (4) Six genes, including PPARG, MMP9, SRC and 3 other genes, were related to the M0 fraction. (5) CD36 and PPARG were upregulated in atherosclerosis samples compared to the normal control. (6) By inhibiting lipid uptake in RAW264.7 cells, NOB prevents the formation of foam cell. (7) In RAW264.7 cells, the inhibitory effect of oxidized low-density lipoprotein on foam cells formation and lipid accumulation was closely associated with the PPARG signaling pathway. (8) In vivo validation showed that NOB significantly attenuated intra-arterial lipid accumulation and macrophage infiltration and reduced CD36 expression.

CONCLUSIONS

Nobiletin alleviates atherosclerosis by inhibiting lipid uptake via the PPARG/CD36 pathway.

[HEARTS in the Americas: targeting health system change to improve population hypertension controlHEARTS nas Américas: impulsionar mudanças no sistema de saúde para melhorar o controle da hipertensão arterial na população]

Purpose of review

HEARTS in the Americas is the regional adaptation of Global Hearts, the World Health Organization initiative for cardiovascular disease (CVD) prevention and control. Its overarching goal is to drive health services to change managerial and clinical practice in primary care settings to improve hypertension control and CVD risk management. This review describes the HEARTS in the Americas initiative. First, the regional epidemiological situation of CVD mortality and population hypertension control trends are summarized; then the rationale for its main intervention components: the primary care-oriented management system and the HEARTS Clinical Pathway are described. Finally, the key factors for accelerating the expansion of HEARTS are examined: medicines, team-based care, and a system for monitoring and evaluation.

Recent findings

Thus far, 33 countries in Latin America and the Caribbean have committed to integrating this program across their primary healthcare network by 2025. The increase in hypertension coverage and control in primary health care settings compared with the traditional model is promising and confirms that the interventions under the HEARTS umbrella are feasible and acceptable to communities, patients, providers, decision-makers, and funders. This review highlights some cases of successful implementation.

Summary

Scaling up effective treatment for hypertension and optimization of CVD risk management is a pragmatic way to accelerate the reduction of CVD mortality while strengthening primary healthcare systems to respond effectively, with quality, and equitably, to the challenge of non-communicable diseases, not only in low-middle income countries but in all communities globally.

Pharmacogenomic biomarkers in coronary artery disease: a narrative review

Coronary artery disease (CAD) has a high mortality rate. Despite various therapeutic targets, non-responsiveness to drugs remains a prevalent issue. Pharmacogenomics assesses the way an individual's genetic attributes affect their likely response to drug therapy. Single-nucleotide polymorphisms play a crucial role in determining these outcomes. This review offers an overview of single-nucleotide polymorphisms investigated in clinical studies and their associations with drug response/nonresponse in the treatment of CAD. A total of 104 studies of whole sets of chromosomes and several genes were explored. A total of 161 polymorphisms exhibited associations with drug response/nonresponse in CAD across diverse ethnic populations. This pool can serve as a pharmacogenomic biomarker for predicting response to drug therapy in patients with CAD.

Twenty years on from the introduction of the high risk strategy for stroke and cardiovascular disease prevention: a systematic scoping review

BACKGROUND AND PURPOSE

Early this century, the high risk strategy of primary stroke and cardiovascular disease (CVD) prevention for individuals shifted away from identifying (and treating, as appropriate) all at-risk individuals towards identifying and treating individuals who exceed arbitrary thresholds of absolute CVD risk. The public health impact of this strategy is uncertain.

METHODS

In our systematic scoping review, the electronic databases (Scopus, MEDLINE, Embase, Google Scholar, Cochrane Library) were searched to identify and appraise publications related to primary CVD/stroke prevention strategies and their effectiveness published in any language from January 1990 to August 2023.

RESULTS

No published randomized controlled trial was found on the effectiveness of the high CVD risk strategy for primary stroke/CVD prevention. Targeting high CVD risk individuals excludes a large proportion of the population from effective blood-pressure-lowering and lipid-lowering treatment and effective CVD prevention. There is also evidence that blood pressure lowering and lipid lowering are beneficial irrespective of blood pressure and cholesterol levels and irrespective of absolute CVD risk and that risk-stratified pharmacological management of blood pressure and lipids to only high CVD risk individuals leads to significant underuse of blood-pressure-lowering and lipid-lowering medications in individuals otherwise eligible for such treatment.

CONCLUSIONS

Primary stroke and CVD prevention needs to be done in all individuals with increased risk of CVD/stroke. Pharmacological management of blood pressure and blood cholesterol should not be solely based on the high CVD risk treatment thresholds. International guidelines and global strategies for primary CVD/stroke prevention need to be revised.

High-fat diet promotes coagulation and endothelial activation in Sprague Dawley rats: Short-term effects of combined oral contraceptives

BACKGROUND

Combined oral contraceptives (COCs), use in individuals are associated with increased risk of thrombotic events. This highlights the significance of assessing the impact of COC on promoting coagulation and endothelial activation in high-fat diet (HFD)-fed Sprague Dawley rats.

METHODS

Twenty (20) five-weeks-old female Sprague Dawley rats weighing between 150 and 200g were subjected to both LFD and HFD-feeding for 8-weeks to determine its influence on basic metabolic status, hemostatic profile, hemodynamic parameters (blood pressure and heart rate), as well as selected biomarkers of coagulation (tissue factor and D-dimer) and endothelial activation (Von Willebrand factor and nitric oxide). Thereafter HFD-fed animals were treated with receive high dose combined oral contraceptive (HCOC) and low dose combine oral contraceptive (LCOC) for 6 weeks.

RESULTS

Our results showed that beyond weight gain, HFD-feeding was associated with hyperglycemia, increased mean arterial pressure, and reduced nitric oxide levels when compared with LFD group (p<0.05). Interestingly, treatment with high dose of COC for 6-weeks did not significantly alter atherothrombotic markers (p>0.05). However, this study is not without limitation as regulation of these markers remains to be confirmed within the cardiac tissues or endothelial cells of these animals.

CONCLUSION

HFD-feeding orchestrate the concomitant release of pro-coagulants and endothelial activation markers in rats leading to haemostatic imbalance and endothelial dysfunction. Short-term treatment with COC shows no detrimental effects in these HFD-fed rats. Although in terms of clinical relevance, our findings depict the notion that the risk of CVD in association with COC may depend on the dosage and duration of use among other factors especially in certain conditions. However, additional studies are required to confirm these findings, especially long-term effects of this treatment within the cardiac tissues or endothelial cells of these animals in certain conditions relating to postmenopausal state.

Major Limitations of Cardiovascular Risk Scores

Background. Epidemiological studies conducted in extensive population cohorts have led to the creation of numerous cardiovascular risk predictor models. However, these tools have certain limitations that restrict its applicability. The aim behind the following work is to summarize today's best-known limitations of cardiovascular risk assessment models through presenting the critical analyses conducted in this area, with the intention of offering practitioners a comprehensive understanding of these restrictions. Critical analyses revealed that these scales exhibit numerous limitations that could impact their performance. Most of these models evaluate cardiovascular risk based on classic risk factors and other restrictions, thereby negatively affecting their sensitivity. Scientists have made significant advancements in improving cardiovascular risk models, tailoring them to accommodate a wide range of populations and devising scales for estimating cardiovascular risks that can account for all prevailing restrictions. Better understanding these limitations could improve the cardiovascular risk stratification.

Exploring Therapeutic Potential of Pleurotus ostreatus and Agaricus bisporus Mushrooms against Hyperlipidemia and Oxidative Stress Using Animal Model

The mushrooms oyster (Pleurotus ostreatus) and white button (Agaricus bisporus) contain bioactive compounds that have potential beneficial effects on hypercholesterolemia and cardiovascular diseases. In this study, hypolipidemic and antioxidative potential of these mushrooms' extract were explored using hypercholesterolemic (HC) rats as animal model. For the study, 56 adult rats were divided into seven groups, i.e., G1 (negative control), G2 (positive control group), G3 (HC rats with statin drug orally), G4 and G5 (HC rats @ 100 and 200 mg/kg body weight (BW) dose of oyster mushroom extracts), and G6 and G7 (HC rats @ 100 and 200 mg/kg BW dose of white button mushroom extracts). The hypercholesterolemia was induced experimentally in fasted rats through a high-fat diet along with injection of triton WR-1339. After 48 h, the treatment groups were given extract for 28 days along with standard diet. At the trial termination, we analyzed the blood sugar levels, antioxidant parameters, lipid profile, and renal function, as well as conducting liver function tests of the rats. The results indicated that positive control group rats exhibited increased levels of total cholesterol (TC), triglycerides (TG), low-density level (LDL), and very-low-density level (vLDL) by 19%, 37%, 52%, and 32%, respectively, and 53% decrease in HDL, whereas treatment groups that received 200 mg oyster and white button mushroom extracts reported 15%, 34%, 22% reduction in TC, TG, vLDL, respectively, and 22% improvement in HDL level. The enzyme profiles of different groups showed non-significant differences, although both mushroom extracts provision reduced glutamic oxaloacetic transaminase (GOT) and glutamic pyruvic transaminase (GPT) levels. Overall, the results indicated that mushroom extracts were helpful in maintaining oxidative stress and have the potential to improve dyslipidemia in the tested rat animal model.

To What Extent Does Cardiovascular Risk Classification of Patients with Type 2 Diabetes Differ between European Guidelines from 2023, 2021, and 2019? A Cross-Sectional Study

Background and Objectives: Type 2 Diabetes (T2DM) is intricately associated with an increased cardiovascular (CV) risk, highlighting the imperative for tailored intervention in the prevention and management of CV diseases. To assess the CV risk and subsequent interventions in patients with diabetes, the European Society of Cardiology (ESC) has been consistently developing and updating specific guidelines for risk assessment and patient management since 2019. The 2023 risk classification method has significantly changed, introducing a novel probability-based assessment through the implementation of SCORE2-Diabetes instrument. This marks a shift from the risk factor-based classification employed in the 2019 and 2021 methods, representing an innovative approach in risk assessment for individuals with T2DM. This study aims to evaluate the differences in the CV risk classification among hospitalized patients with T2DM using the three proposed methods within the Romanian population, a European population considered to be at very high cardiovascular risk. Materials and Methods: in a consecutive-case, population-based study design, 70 patients hospitalized with T2DM from a European population characterized by very high CV risk were assessed for CV risk using the three proposed methods. The differences between these classifications were subsequently analyzed. Results: In the study group, according to 2023 classification, one patient (1.4%) was classified with moderate CV risk, eight (11.4%) with high cardiovascular risk, and sixty-one (87.2%) with very high cardiovascular risk. A total of 36 patients (51.4%) were classified differently compared to 2021 criteria, the differences being statistically significant (p = 0.047), while 13 (18.6%) were different compared to 2019 criteria, the differences being statistically non-significant (p = 0.731). By comparing the 2021 to the 2019 ESC Guidelines recommendations, 40 patients had a one-step decrease in cardiovascular risk category, from very high to high risk. Conclusions: Most patients included in the analysis were classified as very high CV risk (87.2%). Within a European population characterized by very high CV risk, the SCORE2-Diabetes instrument proves to be a valuable tool, contributing to most step-ups in CV risk classes within the 2023 classification. In a very-high-risk demographic, the 2023 algorithm resulted in different classifications in contrast to the 2021 method but similar classifications observed with the 2019 method.

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.

Artificial intelligence in the risk prediction models of cardiovascular disease and development of an independent validation screening tool: a systematic review

BACKGROUND

A comprehensive overview of artificial intelligence (AI) for cardiovascular disease (CVD) prediction and a screening tool of AI models (AI-Ms) for independent external validation are lacking. This systematic review aims to identify, describe, and appraise AI-Ms of CVD prediction in the general and special populations and develop a new independent validation score (IVS) for AI-Ms replicability evaluation.

METHODS

PubMed, Web of Science, Embase, and IEEE library were searched up to July 2021. Data extraction and analysis were performed for the populations, distribution, predictors, algorithms, etc. The risk of bias was evaluated with the prediction risk of bias assessment tool (PROBAST). Subsequently, we designed IVS for model replicability evaluation with five steps in five items, including transparency of algorithms, performance of models, feasibility of reproduction, risk of reproduction, and clinical implication, respectively. The review is registered in PROSPERO (No. CRD42021271789).

RESULTS

In 20,887 screened references, 79 articles (82.5% in 2017-2021) were included, which contained 114 datasets (67 in Europe and North America, but 0 in Africa). We identified 486 AI-Ms, of which the majority were in development (n = 380), but none of them had undergone independent external validation. A total of 66 idiographic algorithms were found; however, 36.4% were used only once and only 39.4% over three times. A large number of different predictors (range 5-52,000, median 21) and large-span sample size (range 80-3,660,000, median 4466) were observed. All models were at high risk of bias according to PROBAST, primarily due to the incorrect use of statistical methods. IVS analysis confirmed only 10 models as "recommended"; however, 281 and 187 were "not recommended" and "warning," respectively.

CONCLUSION

AI has led the digital revolution in the field of CVD prediction, but is still in the early stage of development as the defects of research design, report, and evaluation systems. The IVS we developed may contribute to independent external validation and the development of this field.

Hypertension care cascades and reducing inequities in cardiovascular disease in low- and middle-income countries

Improving hypertension control in low- and middle-income countries has uncertain implications across socioeconomic groups. In this study, we simulated improvements in the hypertension care cascade and evaluated the distributional benefits across wealth quintiles in 44 low- and middle-income countries using individual-level data from nationally representative, cross-sectional surveys. We raised diagnosis (diagnosis scenario) and treatment (treatment scenario) levels for all wealth quintiles to match the best-performing country quintile and estimated the change in 10-year cardiovascular disease (CVD) risk of individuals initiated on treatment. We observed greater health benefits among bottom wealth quintiles in middle-income countries and in countries with larger baseline disparities in hypertension management. Lower-middle-income countries would see the greatest absolute benefits among the bottom quintiles under the treatment scenario (29.1 CVD cases averted per 1,000 people living with hypertension in the bottom quintile (Q1) versus 17.2 in the top quintile (Q5)), and the proportion of total CVD cases averted would be largest among the lowest quintiles in upper-middle-income countries under both diagnosis (32.0% of averted cases in Q1 versus 11.9% in Q5) and treatment (29.7% of averted cases in Q1 versus 14.0% in Q5) scenarios. Targeted improvements in hypertension diagnosis and treatment could substantially reduce socioeconomic-based inequalities in CVD burden in low- and middle-income countries.

Targeting systemic inflammation in metabolic disorders. A therapeutic candidate for the prevention of cardiovascular diseases?

Cardiovascular disease (CVD) remains the leading cause of death and disability worldwide. While many factors can contribute to CVD, atherosclerosis is the cardinal underlying pathology, and its development is associated with several metabolic risk factors including dyslipidemia and obesity. Recent studies have definitively demonstrated a link between low-grade systemic inflammation and two relevant metabolic abnormalities: hypercholesterolemia and obesity. Interestingly, both metabolic disorders are also associated with endothelial dysfunction/activation, a proinflammatory and prothrombotic phenotype of the endothelium that involves leukocyte infiltration into the arterial wall, one of the earliest stages of atherogenesis. This article reviews the current literature on the intricate relationship between hypercholesterolemia and obesity and the associated systemic inflammation and endothelial dysfunction, and discusses the effectiveness of present, emerging and in-development pharmacological therapies used to treat these metabolic disorders with a focus on their effects on the associated systemic inflammatory state and cardiovascular risk.

A novel ternary pattern-based automatic psychiatric disorders classification using ECG signals

Neuropsychiatric disorders are one of the leading causes of disability. Mental health problems can occur due to various biological and environmental factors. The absence of definitive confirmatory diagnostic tests for psychiatric disorders complicates the diagnosis. It's critical to distinguish between bipolar disorder, depression, and schizophrenia since their symptoms and treatments differ. Because of brain-heart autonomic connections, electrocardiography (ECG) signals can be changed in behavioral disorders. In this research, we have automatically classified bipolar, depression, and schizophrenia from ECG signals. In this work, a new hand-crafted feature engineering model has been proposed to detect psychiatric disorders automatically. The main objective of this model is to accurately detect psychiatric disorders using ECG beats with linear time complexity. Therefore, we collected a new ECG signal dataset containing 3,570 ECG beats with four categories. The used categories are bipolar, depression, schizophrenia, and control. Furthermore, a new ternary pattern-based signal classification model has been proposed to classify these four categories. Our proposal contains four essential phases, and these phases are (i) multileveled feature extraction using multilevel discrete wavelet transform and ternary pattern, (ii) the best features selection applying iterative Chi2 selector, (iii) classification with artificial neural network (ANN) to calculate lead wise results and (iv) calculation the voted/general classification accuracy using iterative majority voting (IMV) algorithm. tenfold cross-validation is one of the most used validation techniques in the literature, and this validation model gives robust classification results. Using ANN with tenfold cross-validation, lead-by-lead and voted results have been calculated. The lead-by-lead accuracy range of the proposed model using the ANN classifier is from 73.67 to 89.19%. By deploying the IMV method, the general classification performance of our ternary pattern-based ECG classification model is increased from 89.19 to 96.25%. The findings and the calculated classification accuracies (single lead and voted) clearly demonstrated the success of the proposed ternary pattern-based advanced signal processing model. By using this model, a new wearable device can be proposed.

Elevated atherogenic index of plasma increased the risk of myocardial infarction in a general population

PURPOSE

The atherogenic index of plasma (AIP) has been shown to be related to cardiovascular disease risk, but evidence on the longitudinal pattern of AIP during follow-up is limited. We aimed to explore the associations of baseline and long-term AIP with the risk of myocardial infarction (MI).

METHODS

We included 98,861 participants in the Kailuan Study who were free of MI at baseline. AIP was calculated as log (triglyceride/high-density lipoprotein cholesterol). Long-term AIP included the long-term mean AIP (mean AIP from baseline to the first occurrence of MI or the end of follow-up) and number of visits with high AIP (above the cutoff value at the first three visits). The baseline and updated mean AIP were in operationalized as quartiles. Cox proportional hazard models were used to determine the associations between AIP and risk of MI. We excluding all deaths during the follow-up visits in the sensitivity analysis.

RESULTS

During a median follow-up of 12.80 years, 1804 participants developed MI. Compared with quartile 1, the adjusted hazard ratios in baseline and updated mean AIP quartile 4 were 1.63 (95% CI, 1.41-1.88) and 1.59 (95% CI, 1.37-1.83), respectively. Compared with participants who did not have a high AIP, the HR among individuals with AIP elevated by three times was 1.94 (95% CI,1.55-2.45). The sensitivity analysis showed similar associations.

CONCLUSIONS

Elevated levels of both baseline and long-term AIP increased the risk of MI.

Olive leaf extract effect on cardiometabolic risk factors: a systematic review and meta-analysis of randomized clinical trials

CONTEXT

Olive leaf extract (OLE) is rich in phenolic compounds, which are known for their health benefits. Cardiovascular diseases, primarily coronary heart disease and stroke, are leading causes of mortality globally.

OBJECTIVE

This systematic review aimed to assess the impact of OLE on cardiometabolic risk factors in adults. The selection of studies was based on intervention and outcomes, using relevant search descriptors.

DATA SOURCES

The databases PubMed, EMBASE, and Web of Science were systematically searched for pertinent studies published up to August 2021.

DATA EXTRACTION

Only randomized clinical trials, either cross-over or parallel, involving adult individuals aged ≥18 years, were considered. Additionally, trials that had a comparative or placebo group and used pure OLEs for oral treatment were included.

DATA ANALYSIS

Twelve randomized clinical trials (RCTs) met the inclusion criteria. These trials had follow-up periods ranging from 2 days to 12 weeks and involved 703 patients aged 18 years-79 years. The outcomes demonstrated a positive correlation between the intervention group and glucose metabolism (4 RCTs), blood pressure (2 RCTs), lipid profile (2 RCTs), and inflammatory markers (2 RCTs). The RoB2 tool and the GRADE system were used to evaluate the risk of bias and the quality of evidence in the studies.

CONCLUSIONS

In the meta-analysis, fasting glycemia, as evaluated in studies using a low dose of OLE, showed a significant result favoring the control group. To obtain more consistent results, further clinical studies in humans, using similar methodologies, are required.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration no. CRD42020200877.

CardiOmics signatures reveal therapeutically actionable targets and drugs for cardiovascular diseases

Cardiovascular diseases are the leading cause of death worldwide, with heart failure being a complex condition that affects millions of individuals. Single-nucleus RNA sequencing has recently emerged as a powerful tool for unraveling the molecular mechanisms behind cardiovascular diseases. This cutting-edge technology enables the identification of molecular signatures, intracellular networks, and spatial relationships among cardiac cells, including cardiomyocytes, mast cells, lymphocytes, macrophages, lymphatic endothelial cells, endocardial cells, endothelial cells, epicardial cells, adipocytes, fibroblasts, neuronal cells, pericytes, and vascular smooth muscle cells. Despite these advancements, the discovery of essential therapeutic targets and drugs for precision cardiology remains a challenge. To bridge this gap, we conducted comprehensive in silico analyses of single-nucleus RNA sequencing data, functional enrichment, protein interactome network, and identification of the shortest pathways to physiological phenotypes. This integrated multi-omics analysis generated CardiOmics signatures, which allowed us to pinpoint three therapeutically actionable targets (ADRA1A1, PPARG, and ROCK2) and 15 effective drugs, including adrenergic receptor agonists, adrenergic receptor antagonists, norepinephrine precursors, PPAR receptor agonists, and Rho-associated kinase inhibitors, involved in late-stage cardiovascular disease clinical trials.

Survey of Medical Applications of Federated Learning

OBJECTIVES

Medical artificial intelligence (AI) has recently attracted considerable attention. However, training medical AI models is challenging due to privacy-protection regulations. Among the proposed solutions, federated learning (FL) stands out. FL involves transmitting only model parameters without sharing the original data, making it particularly suitable for the medical field, where data privacy is paramount. This study reviews the application of FL in the medical domain.

METHODS

We conducted a literature search using the keywords "federated learning" in combination with "medical," "healthcare," or "clinical" on Google Scholar and PubMed. After reviewing titles and abstracts, 58 papers were selected for analysis. These FL studies were categorized based on the types of data used, the target disease, the use of open datasets, the local model of FL, and the neural network model. We also examined issues related to heterogeneity and security.

RESULTS

In the investigated FL studies, the most commonly used data type was image data, and the most studied target diseases were cancer and COVID-19. The majority of studies utilized open datasets. Furthermore, 72% of the FL articles addressed heterogeneity issues, while 50% discussed security concerns.

CONCLUSIONS

FL in the medical domain appears to be in its early stages, with most research using open data and focusing on specific data types and diseases for performance verification purposes. Nonetheless, medical FL research is anticipated to be increasingly applied and to become a vital component of multi-institutional research.

Improving cardiovascular risk prediction through machine learning modelling of irregularly repeated electronic health records

Aims

Existing electronic health records (EHRs) often consist of abundant but irregular longitudinal measurements of risk factors. In this study, we aim to leverage such data to improve the risk prediction of atherosclerotic cardiovascular disease (ASCVD) by applying machine learning (ML) algorithms, which can allow automatic screening of the population.

Methods and results

A total of 215 744 Chinese adults aged between 40 and 79 without a history of cardiovascular disease were included (6081 cases) from an EHR-based longitudinal cohort study. To allow interpretability of the model, the predictors of demographic characteristics, medication treatment, and repeatedly measured records of lipids, glycaemia, obesity, blood pressure, and renal function were used. The primary outcome was ASCVD, defined as non-fatal acute myocardial infarction, coronary heart disease death, or fatal and non-fatal stroke. The eXtreme Gradient boosting (XGBoost) algorithm and Least Absolute Shrinkage and Selection Operator (LASSO) regression models were derived to predict the 5-year ASCVD risk. In the validation set, compared with the refitted Chinese guideline-recommended Cox model (i.e. the China-PAR), the XGBoost model had a significantly higher C-statistic of 0.792, (the differences in the C-statistics: 0.011, 0.006-0.017, P < 0.001), with similar results reported for LASSO regression (the differences in the C-statistics: 0.008, 0.005-0.011, P < 0.001). The XGBoost model demonstrated the best calibration performance (men: Dx = 0.598, P = 0.75; women: Dx = 1.867, P = 0.08). Moreover, the risk distribution of the ML algorithms differed from that of the conventional model. The net reclassification improvement rates of XGBoost and LASSO over the Cox model were 3.9% (1.4-6.4%) and 2.8% (0.7-4.9%), respectively.

Conclusion

Machine learning algorithms with irregular, repeated real-world data could improve cardiovascular risk prediction. They demonstrated significantly better performance for reclassification to identify the high-risk population correctly.

Mapping evidence on barriers to and facilitators of diagnosing noncommunicable diseases (NCDs) among people living with human immunodeficiency virus (PLWH) in low- and middle-income countries (LMICs) in Africa: A scoping review protocol

BACKGROUND

Noncommunicable diseases (NCDs) represent a global public health challenge in all population groups, but the prevalence of major NCDs, such as depression, hypercholesterolemia, hypertension, obesity and diabetes, is increasing at a rapid rate among people living with human immunodeficiency virus (PLWH). Studies show that integrated NCDs and human immunodeficiency virus (HIV) services have improved the patient outcome of PLWH with comorbidities with NCDs. It requires a strengthened and sustainable way of diagnosing major NCDs early among PLWH. However, there is limited evidence regarding the barriers to and facilitators of early diagnosis of NCDs (depression, hypercholesterolemia, hypertension, obesity and diabetes) among PLWH in low- and middle-income countries (LMICs). This review will systematically map the literature and describe the barriers and facilitators of diagnosing NCDs (depression, hypercholesterolemia, hypertension, obesity and diabetes) among PLWH in LMICs in Africa.

METHODS

The methodology presented by Arksey and O'Malley and the recommendation set out by Levac and colleagues will be used. PubMed, MEDLINE with full text via the EBSCO host, Google Scholar, Science Direct and Scopus will be used for a comprehensive search for data extraction. The search will be conducted using keywords, Boolean terms, and Medical Subject Headings (MeSH). All studies with eligible titles will be exported to the EndNote citation manager for deduplication and imported to Rayyan software for screening. Two reviewers will independently screen abstracts, and the preferred reporting items for systematic review and meta-analysis extension to scoping review (PRISMA-Sc) guidelines will be used to guide the search in conducting the scoping review. We will perform descriptive data analysis for quantitative studies, NVivo software version 12 will be used for qualitative studies, and thematic content analysis will be carried out. This scoping review will include studies that included PLWH with those diagnosed with major NCDs (depression, hypercholesterolemia, hypertension, obesity, and diabetes) in LMICs in Africa.

DISCUSSION

This scoping review will highlight evidence mapping on barriers and facilitators of diagnosing NCDs (depression, hypercholesterolemia, hypertension, obesity, and diabetes) among PLWH LMICs in Africa. Scoping Review Registration: registered on Open Science Framework (https://osf.io/xvtwd/).

Deep Learning Paradigm and Its Bias for Coronary Artery Wall Segmentation in Intravascular Ultrasound Scans: A Closer Look

BACKGROUND AND MOTIVATION

Coronary artery disease (CAD) has the highest mortality rate; therefore, its diagnosis is vital. Intravascular ultrasound (IVUS) is a high-resolution imaging solution that can image coronary arteries, but the diagnosis software via wall segmentation and quantification has been evolving. In this study, a deep learning (DL) paradigm was explored along with its bias.

METHODS

Using a PRISMA model, 145 best UNet-based and non-UNet-based methods for wall segmentation were selected and analyzed for their characteristics and scientific and clinical validation. This study computed the coronary wall thickness by estimating the inner and outer borders of the coronary artery IVUS cross-sectional scans. Further, the review explored the bias in the DL system for the first time when it comes to wall segmentation in IVUS scans. Three bias methods, namely (i) ranking, (ii) radial, and (iii) regional area, were applied and compared using a Venn diagram. Finally, the study presented explainable AI (XAI) paradigms in the DL framework.

FINDINGS AND CONCLUSIONS

UNet provides a powerful paradigm for the segmentation of coronary walls in IVUS scans due to its ability to extract automated features at different scales in encoders, reconstruct the segmented image using decoders, and embed the variants in skip connections. Most of the research was hampered by a lack of motivation for XAI and pruned AI (PAI) models. None of the UNet models met the criteria for bias-free design. For clinical assessment and settings, it is necessary to move from a paper-to-practice approach.

Evaluation of the Probiotic Properties of Lacticaseibacillus casei 431® Isolated from Food for Special Medical Purposes§

Research background

Increasing awareness of the importance of nutrition in health promotion and disease prevention has driven to the development of foods for special medical purposes (FSMPs). In this study, the probiotic strain Lacticaseibacillus paracasei ssp. paracasei (Lacticaseibacillus casei 431®) was incorporated into FSMPs to develop an innovative product. The aim was to investigate the influence of the FSMP matrix on the specific probiotic properties of L. casei 431® in vitro.

Experimental approach

A series of in vitro experiments were performed as part of the probiotic approach. After evaluation of antibiotic susceptibility profiles, functional properties such as survival under simulated gastrointestinal tract (GIT) conditions, bile salt deconjugation activities, cholesterol assimilation, antagonistic activity against spoilage bacteria and adhesion to Caco-2 cell line monolayers and extracellular matrix proteins were investigated.

Results and conclusions

The L. casei 431® strain, both the lyophilised strain and the strain isolated from the FSMP matrix, effectively survived the simulated adverse gastrointestinal conditions without significant effects of the food matrix. The effect of the FSMP matrix on the deconjugation activity of the bile salts of L. casei 431® was minimal; however, cholesterol assimilation was increased by 16.4 %. L. casei 431® had antibacterial activity against related lactic acid bacteria regardless of whether it was used in FSMPs or not. Conversely, the probiotic strain isolated from FSMP matrix had significantly higher inhibitory activity against six potential pathogens than the lyophilised culture. The autoaggregation ability of the L. casei 431® cells was not affected by the FSMP matrix. The adhesion of L. casei 431® bacterial cells to the extracellular matrix proteins was reduced after treatment with proteinase K, with the highest adhesion observed to laminin. The adhesion of L. casei 431® reduced the binding of E. coli 3014 by 1.81 log units and the binding of S. Typhimurium FP1 to Caco-2 cell lines by 1.85 log units, suggesting the potential for competitive exclusion of these pathogens.

Novelty and scientific contribution

The results support the positive effect of the FSMP matrix on the specific probiotic properties of L. casei 431®, such as antibacterial activity, bile salt deconjugation and cholesterol assimilation, while the incorporation of this probiotic strain adds functional value to the FSMPs. The synergistic effect achieved by the joint application of L. casei 431® and innovative FSMP matrix contributed to the development of the novel formulation of an improved functional food product with added value.

Effects of inappropriate cause-of-death certification on mortality from cardiovascular disease and diabetes mellitus in Tonga

BACKGROUND

Cardiovascular disease (CVD) and diabetes mellitus are major health issues in Tonga and other Pacific countries, although mortality levels and trends are unclear. We assess the impacts of cause-of-death certification on coding of CVD and diabetes as underlying causes of death (UCoD).

METHODS

Tongan records containing cause-of-death data (2001-2018), including medical certificates of cause-of-death (MCCD), had UCoD assigned according to International Classification of Diseases 10th revision (ICD-10) coding rules. Deaths without recorded cause were included to ascertain total mortality. Diabetes and hypertension causes were reallocated from Part 1 of the MCCD (direct cause) to Part 2 (contributory cause) if potentially fatal complications were not recorded, and an alternative UCoD was assigned. Proportional mortality by cause based on the alternative UCoD were applied to total deaths then mortality rates calculated by age and sex using census/intercensal population estimates. CVD and diabetes mortality rates for unaltered and alternative UCoD were compared using Poisson regression.

RESULTS

Over 2001-18, in ages 35-59 years, alternative CVD mortality was higher than unaltered CVD mortality in men (p = 0.043) and women (p = 0.15); for 2010-18, alternative versus unaltered measures in men were 3.3/103 (95%CI: 3.0-3.7/103) versus 2.9/103 (95%CI: 2.6-3.2/103), and in women were 1.1/103 (95%CI: 0.9-1.3/103) versus 0.9/103 (95%CI: 0.8-1.1/103). Conversely, alternative diabetes mortality rates were significantly lower than the unaltered rates over 2001-18 in men (p < 0.0001) and women (p = 0.013); for 2010-18, these measures in men were 1.3/103 (95%CI: 1.1-1.5/103) versus 1.9/103 (95%CI: 1.6-2.2/103), and in women were 1.4/103 (95%CI: 1.2-1.7/103) versus 1.7/103 (95%CI: 1.5-2.0/103). Diabetes mortality rates increased significantly over 2001-18 in men (unaltered: p < 0.0001; alternative: p = 0.0007) and increased overall in women (unaltered: p = 0.0015; alternative: p = 0.014).

CONCLUSIONS

Diabetes reporting in Part 1 of the MCCD, without potentially fatal diabetes complications, has led to over-estimation of diabetes, and under-estimation of CVD, as UCoD in Tonga. This indicates the importance of controlling various modifiable risks for atherosclerotic CVD (including stroke) including hypertension, tobacco use, and saturated fat intake, besides obesity and diabetes. Accurate certification of diabetes as a direct cause of death (Part 1) or contributory factor (Part 2) is needed to ensure that valid UCoD are assigned. Examination of multiple cause-of-death data can improve understanding of the underlying causes of premature mortality to better inform health planning.

Pragmatic solutions to reduce the global burden of stroke: a World Stroke Organization-Lancet Neurology Commission

Stroke is the second leading cause of death worldwide. The burden of disability after a stroke is also large, and is increasing at a faster pace in low-income and middle-income countries than in high-income countries. Alarmingly, the incidence of stroke is increasing in young and middle-aged people (ie, age <55 years) globally. Should these trends continue, Sustainable Development Goal 3.4 (reducing the burden of stroke as part of the general target to reduce the burden of non-communicable diseases by a third by 2030) will not be met.

In this Commission, we forecast the burden of stroke from 2020 to 2050. We project that stroke mortality will increase by 50%—from 6·6 million (95% uncertainty interval [UI] 6·0 million–7·1 million) in 2020, to 9·7 million (8·0 million–11·6 million) in 2050—with disability-adjusted life-years (DALYs) growing over the same period from 144·8 million (133·9 million–156·9 million) in 2020, to 189·3 million (161·8 million–224·9 million) in 2050. These projections prompted us to do a situational analysis across the four pillars of the stroke quadrangle: surveillance, prevention, acute care, and rehabilitation. We have also identified the barriers to, and facilitators for, the achievement of these four pillars. Disability-adjusted life-years (DALYs) The sum of the years of life lost as a result of premature mortality from a disease and the years lived with a disability associated with prevalent cases of the disease in a population. One DALY represents the loss of the equivalent of one year of full health

On the basis of our assessment, we have identified and prioritised several recommendations. For each of the four pillars (surveillance, prevention, acute care, and rehabilitation), we propose pragmatic solutions for the implementation of evidence-based interventions to reduce the global burden of stroke. The estimated direct (ie, treatment and rehabilitation) and indirect (considering productivity loss) costs of stroke globally are in excess of US$891 billion annually. The pragmatic solutions we put forwards for urgent implementation should help to mitigate these losses, reduce the global burden of stroke, and contribute to achievement of Sustainable Development Goal 3.4, the WHO Intersectoral Global Action Plan on epilepsy and other neurological disorders (2022–2031), and the WHO Global Action Plan for prevention and control of non-communicable diseases.

Reduction of the global burden of stroke, particularly in low-income and middle-income countries, by implementing primary and secondary stroke prevention strategies and evidence-based acute care and rehabilitation services is urgently required. Measures to facilitate this goal include: the establishment of a framework to monitor and assess the burden of stroke (and its risk factors) and stroke services at a national level; the implementation of integrated population-level and individual-level prevention strategies for people at any increased risk of cerebrovascular disease, with emphasis on early detection and control of hypertension; planning and delivery of acute stroke care services, including the establishment of stroke units with access to reperfusion therapies for ischaemic stroke and workforce training and capacity building (and monitoring of quality indicators for these services nationally, regionally, and globally); the promotion of interdisciplinary stroke care services, training for caregivers, and capacity building for community health workers and other health-care providers working in stroke rehabilitation; and the creation of a stroke advocacy and implementation ecosystem that includes all relevant communities, organisations, and stakeholders.

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Burden of Cardiovascular Risk in Individuals With Spinal Cord Injury and Its Association With Rehabilitation Outcomes: Results From the Swiss Spinal Cord Injury Cohort

OBJECTIVES

The aims of the study are to determine the cardiovascular risk burden rehabilitation discharge and to explore the association between recovery during rehabilitation and cardiovascular disease risk profile.

METHODS

We included adults without cardiovascular disease admitted for rehabilitation. We evaluated rehabilitation outcomes on admission and discharge. Cardiovascular disease risk profile was assessed by Framingham risk score, high-density lipoprotein, and fasting glucose level.

RESULTS

We analyzed data from 706 participants (69.6% men) with a median age of 53.5 yrs. The median time since injury was 14 days, and the admission length was 5.2 months. Majority had paraplegia (53.3%) and motor incomplete injury (53.7%). One third of the cohort had high cardiovascular risk profile before discharge. At discharge, poorer anthropometric measures were associated with higher Framingham risk score and lower high-density lipoprotein levels. Individuals with higher forced vital capacity (>2.72 l) and peak expiratory flow (>3.4 l/min) had 0.16 mmol/l and 0.14 mmol/l higher high-density lipoprotein compared with those with lower respiratory function, respectively. Individuals with higher mobility score (>12.5) and functional independence score (>74) had 0.21 and 0.18 mmol/l higher high-density lipoprotein compared with those with lower scores.

CONCLUSIONS

There is high cardiometabolic syndrome burden and cardiovascular disease risk profile upon rehabilitation discharge. Higher respiratory function, mobility, and overall independence were associated with better cardiovascular disease risk profile, although with study design limitations and short follow-up. Future studies should explore whether rehabilitation outcomes could be used to prioritize screening.

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CME OBJECTIVES

Upon reading this journal article, the reader is expected to: (1) Determine the burden of cardiometabolic disease in the early phase of spinal cord injury (SCI); (2) Differentiate the proposed SCI cutoff for high-risk obesity from the able-bodied population; and (3) Increase physicians' acuity for detecting cardiometabolic disease in their practice.

LEVEL

Advanced.

ACCREDITATION

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Percentiles of predicted 10-year cardiovascular disease risk by sex and age in Brazil and their association with estimated risk of long-term atherosclerotic events

OBJECTIVE

Expressing the cardiovascular disease (CVD) risk in relation to peers may complement the estimation of absolute CVD risk. We aimed to determine 10-year CVD risk percentiles by sex and age in the Brazilian population and evaluate their association with estimated long-term atherosclerotic CVD (ASCVD) risk.

METHODS

A cross-sectional analysis of baseline data from the ELSA-Brasil study was conducted in individuals aged 40-74 years without prior ASCVD. Ten-year CVD risk and long-term ASCVD risk were estimated by the WHO risk score and the Multinational Cardiovascular Risk Consortium tool, respectively. Ten-year risk percentiles were determined by ranking the calculated risks within each sex and age group.

RESULTS

Ten-year CVD risk versus percentile plots were constructed for each sex and age group using data from 13,364 participants (55% females; median age, 52 [IQR, 46-59] years). Long-term ASCVD risk was calculated in 12,973 (97.1%) participants. Compared to individuals at the <25th risk percentile, those at the ≥75th percentile had a greater risk of being in the highest quartile of long-term risk (ORs [95% CIs] 6.57 [5.18-8.30] in females and 11.59 [8.42-15.96] in males) in regression models adjusted for age, race, education, and 10-year CVD risk. In both sexes, the association between risk percentile and long-term risk weakened after age 50. A tool for calculating 10-year CVD risk and the corresponding percentile is available at https://bit.ly/3CzPUi6.

CONCLUSIONS

We established percentiles of predicted 10-year CVD risk by sex and age in the Brazilian population, which independently reflect the estimated long-term ASCVD risk in younger individuals.

Validity of the models predicting 10-year risk of cardiovascular diseases in Asia: A systematic review and prediction model meta-analysis

We aimed to review the validity of existing prediction models for cardiovascular diseases (CVDs) in Asia. In this systematic review and meta-analysis, we included studies that validated prediction models for CVD risk in the general population in Asia. Various databases, including PubMed, Web of Science conference proceedings citation index, Scopus, Global Index Medicus of the World Health Organization (WHO), and Open Access Thesis and Dissertations (OATD), were searched up to November 2022. Additional studies were identified through reference lists and related reviews. The risk of bias was assessed using the PROBAST prediction model risk of bias assessment tool. Meta-analyses were performed using the random effects model, focusing on the C-statistic as a discrimination index and the observed-to-expected ratio (OE) as a calibration index. Out of 1315 initial records, 16 studies were included, with 21 external validations of six models in Asia. The validated models consisted of Framingham models, pooled cohort equations (PCEs), SCORE, Globorisk, and WHO models, combined with the results of the first four models. The pooled C-statistic for men ranged from 0.72 (95% CI 0.70 to 0.75; PCEs) to 0.76 (95% CI 0.74 to 0.78; Framingham general CVD). In women, it varied from 0.74 (95% CI 0.22 to 0.97; SCORE) to 0.79 (95% CI 0.74 to 0.83; Framingham general CVD). The pooled OE ratio for men ranged from 0.21 (95% CI 0.018 to 2.49; Framingham CHD) to 1.11 (95%CI 0.65 to 1.89; PCEs). In women, it varied from 0.28 (95%CI 0.33 to 2.33; Framingham CHD) to 1.81 (95% CI 0.90 to 3.64; PCEs). The Framingham, PCEs, and SCORE models exhibited acceptable discrimination but poor calibration in predicting the 10-year risk of CVDs in Asia. Recalibration and updates are necessary before implementing these models in the region.

Plasma proteomic profiles predict individual future health risk

Developing a single-domain assay to identify individuals at high risk of future events is a priority for multi-disease and mortality prevention. By training a neural network, we developed a disease/mortality-specific proteomic risk score (ProRS) based on 1461 Olink plasma proteins measured in 52,006 UK Biobank participants. This integrative score markedly stratified the risk for 45 common conditions, including infectious, hematological, endocrine, psychiatric, neurological, sensory, circulatory, respiratory, digestive, cutaneous, musculoskeletal, and genitourinary diseases, cancers, and mortality. The discriminations witnessed high accuracies achieved by ProRS for 10 endpoints (e.g., cancer, dementia, and death), with C-indexes exceeding 0.80. Notably, ProRS produced much better or equivalent predictive performance than established clinical indicators for almost all endpoints. Incorporating clinical predictors with ProRS enhanced predictive power for most endpoints, but this combination only exhibited limited improvement when compared to ProRS alone. Some proteins, e.g., GDF15, exhibited important discriminative values for various diseases. We also showed that the good discriminative performance observed could be largely translated into practical clinical utility. Taken together, proteomic profiles may serve as a replacement for complex laboratory tests or clinical measures to refine the comprehensive risk assessments of multiple diseases and mortalities simultaneously. Our models were internally validated in the UK Biobank; thus, further independent external validations are necessary to confirm our findings before application in clinical settings.

Impaired oxytocin signaling in the central amygdala in rats with chronic heart failure

Aims

Heart failure (HF) patients often suffer from cognitive decline, depression, and mood impairments, but the molecular signals and brain circuits underlying these effects remain elusive. The hypothalamic neuropeptide oxytocin (OT) is critically involved in the regulation of mood, and OTergic signaling in the central amygdala (CeA) is a key mechanism controlling emotional responses including anxiety-like behaviors. Based on this, we used in this study a well-established ischemic rat HF model and aimed to study alterations in the hypothalamus-to-CeA OTergic circuit.

Methods and Results

To study potential HF-induced changes in the hypothalamus-to-CeA OTertic circuit, we combined patch-clamp electrophysiology, immunohistochemical analysis, RNAScope assessment of OTR mRNA, brain region-specific stereotaxic injections of viral vectors and retrograde tracing, optogenetic stimulation and OT biosensors in the ischemic HF model. We found that most of OTergic innervation of the central amygdala (CeA) originated from the hypothalamic supraoptic nucleus (SON). While no differences in the numbers of SON→CeA OTertic neurons (or their OT content) was observed between sham and HF rats, we did observe a blunted content and release of OT from axonal terminals within the CeA. Moreover, we report downregulation of neuronal and astrocytic OT receptors, and impaired OTR-driven GABAergic synaptic activity within the CeA microcircuit of rats with HF.

Conclusions

Our study provides first evidence that HF rats display various perturbations in the hypothalamus-to-amygdala OTergic circuit, and lays the foundation for future translational studies targeting either the OT system or GABAergic amygdala GABA microcircuit to ameliorate depression or mood impairments in rats or patients with chronic HF.

Health-related quality of life and its influencing factors among people with heart failure in Ethiopia: using the revised Wilson and Cleary model

Heart failure is a challenging public health problem associated with poor health-related quality of life (HRQoL). Data on the quality of life of people with heart failure are limited in Ethiopia. This study aimed to assess the HRQoL and its influencing factors in people with heart failure in Ethiopia. A hospital-based, cross-sectional study design was conducted in the cardiac outpatient clinics of two tertiary-level hospitals in Addis Ababa, Ethiopia. Data were collected from people with heart failure who met the inclusion criteria using an interviewer-administered questionnaire. The HRQoL was measured using the Minnesota Living with Heart Failure Questionnaire (MLHFQ). A multiple linear regression model was fitted to identify factors that influenced HRQoL. All statistical analyses were conducted using STATA version 17 software. A total of 383 people with heart failure participated in the study. The mean age of the participants was 55 years. The MLHFQ score was 48.03±19.73, and 54% of participants had poor HRQoL. Multiple linear regression analysis revealed that age (β= 0.12, 95% CI 0.11, 0.28), diabetes mellitus comorbidity (β= 4.47, 95% CI 1.41, 7.54), social support score (β= - 1.48, 95% CI - 1.93, - 1.03), and depression score (β = 1.74, 95% CI 1.52, 1.96) were significant factors influencing overall HRQoL (p < 0.05). This study found that people in Ethiopia with heart failure had poor HRQoL, influenced by several factors. The findings can help health professionals identify appropriate interventions to improve the HRQoL of people with heart failure.

The relevance of competing risk adjustment in cardiovascular risk prediction models for clinical practice

BACKGROUND

Many models developed for predicting the risk of cardiovascular disease (CVD) are adjusted for the competing risk of non-CVD mortality, which has been suggested to reduce potential overestimation of cumulative incidence in populations where the risk of competing events is high. The objective was to evaluate and illustrate the clinical impact of competing risk adjustment when deriving a CVD prediction model in a high-risk population.

METHODS AND RESULTS

Individuals with established atherosclerotic CVD were included from the Utrecht Cardiovascular Cohort-Secondary Manifestations of ARTerial disease (UCC-SMART). In 8355 individuals, followed for a median of 8.2 years (IQR 4.2-12.5), two similar prediction models for the estimation of 10-year residual CVD risk were derived: with competing risk adjustment using a Fine and Gray model and without competing risk adjustment using a Cox proportional hazards model. On average, predictions were higher from the Cox model. The Cox model predictions overestimated the cumulative incidence [predicted-observed ratio 1.14 (95% CI 1.09-1.20)], which was most apparent in the highest risk quartiles and in older persons. Discrimination of both models was similar. When determining treatment eligibility on thresholds of predicted risks, more individuals would be treated based on the Cox model predictions. If, for example, individuals with a predicted risk > 20% were considered eligible for treatment, 34% of the population would be treated according to the Fine and Gray model predictions and 44% according to the Cox model predictions.

INTERPRETATION

Individual predictions from the model unadjusted for competing risks were higher, reflecting the different interpretations of both models. For models aiming to accurately predict absolute risks, especially in high-risk populations, competing risk adjustment must be considered.

Prognostic value of peripheral endothelial function on major adverse cardiovascular events above traditional risk factors

AIMS

This study aims to identify whether adding peripheral microvascular dysfunction (PMED), a marker of atherosclerosis to established risk scores has an incremental prognostic value for major adverse cardiovascular events (MACE).

METHODS AND RESULTS

This is a retrospective study of patients who underwent measuring peripheral arterial tonometry from 2006 to 2020. The optimal cut-off value of the reactive hyperaemia index (RHI) that had maximal prognostic value associated with MACE was calculated. Peripheral microvascular endothelial dysfunction was defined as the RHI lower than the cut-off. Traditional cardiovascular risk factors such as age, sex, congestive heart failure, hypertension, diabetes, stroke, and vascular disease were determined to calculate the CHA2DS2-Vasc score. The outcome was MACE defined as myocardial infarction, heart failure hospitalization, cerebrovascular events, and all-cause mortality. A total of 1460 patients were enrolled (average age 51.4 ± 13.6, 64.1% female). The optimal cut-off value of the RHI was 1.83 in the overall population and in females and males was 1.61 and 1.8, respectively. The risk of MACE during 7 [interquartile range (IQR): 5,11] years of follow-up was 11.2%. Kaplan-Meier analysis showed that lower RHI is associated with worse MACE-free survival (P < 0.001). Multivariate Cox proportional hazard analysis, controlling for classic cardiovascular risk factors or risk scores such as CHA2DS2-Vasc and Framingham risk score revealed that PMED is an independent predictor of MACE.

CONCLUSION

Peripheral microvascular dysfunction predicts cardiovascular events. Non-invasive assessment of peripheral endothelial function may be useful in early detection and improving the stratification of high-risk patients for cardiovascular events.

LAY SUMMARY

KEY FINDINGS

A homologous and heterogeneous multi-view inter-patient adaptive network for arrhythmia detection

BACKGROUND AND OBJECTIVE

Electrocardiogram (ECG) is a widely used diagnostic tool for arrhythmia assessment in clinical practice. However, current arrhythmia detection algorithms rely heavily on signal-based data, while cardiologists often use image-based data. This discrepancy, combined with individual differences in physiological signals, poses challenges for accurate arrhythmia detection. To address these challenges and improve arrhythmia detection performance, we propose a homologous and heterogeneous multi-view inter-patient adaptive network.

METHODS

We designed a multi-view representation learning module to capture dynamic and morphological characteristics from ECG signals and electrocardiographic images. Expert knowledge was also elicited to gain internally-invariant characteristics of each category. Finally, we designed a new loss function that aligns the embedding of the source and target domains in the feature space to minimize the negative effects of individual differences.

RESULTS

Experiments on the MIT-BIH arrhythmia database demonstrate that our proposed method outperforms state-of-the-art baselines in terms of accuracy, positive predictive value, sensitivity and F1-score. These results indicate the effectiveness of our method in accurately detecting arrhythmias.

CONCLUSIONS

Our homologous and heterogeneous multi-view inter-patient adaptive network successfully addresses the challenges of utilizing both ECG signal and electrocardiographic image data for arrhythmia detection and overcoming individual differences in physiological signals. Our proposed method has the potential to improve early diagnosis and treatment outcomes of arrhythmias in clinical practice.

Estimated risk of cardiovascular events and long-term complications: The projected future of diabetes patients in Delhi from the DEDICOM-II survey

PROBLEM

Despite high prevalence and ethnic susceptibility, limited published estimates are available on long term complication risks among known diabetes patients in India. Hence, we undertook evaluation of the cardiovascular risk of known diabetes patients from Delhi.

METHODS

The community-survey was conducted using a probability-proportionate-to-size(systematic) 2-stage cluster design. Thirty areas were selected for a house-to-house survey to recruit 25 to 30 subjects (known diabetes ≥1 year; 35-65 years of age) per area. Scores from the UKPDS 2.1, UKPDS 2.0, Framingham, ASCVD, WHO, NHS and SCORE studies were used for 10-year risk calculation.

RESULTS

We enrolled 843 subjects of which 800 consented for blood sampling. The mean age of the subjects was 53.0(52.1-54.0) years, the mean duration since diagnosis was 7.1(6.7-7.5) years, with 49.8 % women. 61.8 % were hypertensive, 81.5 % were dyslipidaemic and 53.3 % had poor glycaemic control. Although variable, risk engines estimates were consensual in projecting a high ten-year Coronary-Heart-Disease risk of 10-16 %, a stroke risk of 3.7-5.0 %, and a 5.0-5.7% risk of cardiovascular fatality. These risks were 1.5-3 times the 'risk at target levels' suggesting mitigability. Only 9.3 %, 16.0 %, and 30.0 % were taking aspirin, lipid lowering drugs and antihypertensives respectively.

CONCLUSION

The study highlights the impending impact of, and the scope for improvement in the cardiovascular risk profile of diabetes patients in Delhi, including the use of cardioprotective medications. It strengthens the case for developing and testing potential interventions for improvement.

Anti-thrombotic poly(AAm-co-NaAMPS)-xanthan hydrogel-expanded polytetrafluoroethylene (ePTFE) vascular grafts with enhanced endothelialization and hemocompatibility properties

Cardiovascular diseases (CVDs) are the leading cause of death among all non-communicable diseases globally. Although expanded polytetrafluoroethylene (ePTFE) has been widely used for larger-diameter vascular graft transplantation, the persistent thrombus formation and intimal hyperplasia of small-diameter vascular grafts (SDVGs) made of ePTFE to treat severe CVDs remain the biggest challenges due to lack of biocompatibility and endothelium. In this study, bi-layered poly(acrylamide-co-2-Acrylamido-2-methyl-1-propanesulfonic acid sodium)-xanthan hydrogel-ePTFE (poly(AAm-co-NaAMPS)-xanthan hydrogel-ePTFE) vascular grafts capable of promoting endothelialization and prohibiting thrombosis were synthesized and fabricated. While the external ePTFE layer of the vascular grafts provided the mechanical stability, the inner hydrogel layer offered much-needed cytocompatibility, hemocompatibility, and endothelialization functions. The interface morphology between the inner hydrogel layer and the outer ePTFE layer was observed by scanning electron microscope (SEM), which revealed that the hydrogel was well attached to the porous ePTFE through mechanical interlocking. Among all the hydrogel compositions tested with cell culture using human umbilical vein endothelial cells (HUVECs), the hydrogel with the molar ratio of 40:60 (NaAMPS/AAm) composition (i.e., Hydrogel 40:60) exhibited the best endothelialization function, as it produced the largest endothelialization area that was three times more than of that of plain ePTFE on day 14, maintained the highest average cell viability, and had the best cell morphology. Hydrogel 40:60 also showed excellent hemocompatibility, prolonged activated partial thromboplastin time (aPTT), and good mechanical properties. Overall, bi-layered poly(AAm-co-NaAMPS)-xanthan hydrogel-ePTFE vascular grafts with the Hydrogel 40:60 composition could potentially solve the critical challenge of thrombus formation in vascular graft transplantation applications.

CaMKII, 'jack of all trades' in inflammation during cardiac ischemia/reperfusion injury

Myocardial infarction and revascularization cause cardiac ischemia/reperfusion (I/R) injury featuring cardiomyocyte death and inflammation. The Ca2+/calmodulin dependent protein kinase II (CaMKII) family are serine/ threonine protein kinases that are involved in I/R injury. CaMKII exists in four different isoforms, α, β, γ, and δ. In the heart, CaMKII-δ is the predominant isoform，with multiple splicing variants, such as δB, δC and δ9. During I/R, elevated intracellular Ca2+ concentrations and reactive oxygen species activate CaMKII. In this review, we summarized the regulation and function of CaMKII in multiple cell types including cardiomyocytes, endothelial cells, and macrophages during I/R. We conclude that CaMKII mediates inflammation in the microenvironment of the myocardium, resulting in cell dysfunction, elevated inflammation, and cell death. However, different CaMKII-δ variants exhibit distinct or even opposite functions. Therefore, reagents/approaches that selectively target specific CaMKII isoforms and variants are needed for evaluating and counteracting the exact role of CaMKII in I/R injury and developing effective treatments against I/R injury.

Variability in benefit from intensive insulin therapy on cardiovascular events in individuals with type 1 diabetes: A post hoc analysis of the DCCT/EDIC study

AIM

To evaluate presence of treatment effect heterogeneity of intensive insulin therapy (INT) on occurrence of major adverse cardiovascular events (MACE) in individuals with type 1 diabetes.

METHODS

In participants from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study, individual treatment effect of INT (≥3 daily insulin injections/insulin pump therapy) versus conventional therapy (once/twice daily insulin) on the risk of MACE was estimated using a penalized Cox regression model including treatment-by-covariate interaction terms.

RESULTS

In 1441 participants, 120 first MACE events were observed and 1279 individuals (89%) were predicted to benefit from INT with regard to MACE risk reduction. The study population was divided into four groups based on predicted treatment effect: one group with no predicted benefit and three tertiles with predicted treatment benefit. The median absolute reduction in 30-year risk of MACE across groups of predicted treatment effect ranged from -0.2% (i.e. risk increase; interquartile range [IQR] -0.1% to -0.3%) in the group with no predicted benefit to 6.6% (i.e. risk reduction; IQR 3.8%-10.9%; number needed to treat 15) in the highest tertile of predicted benefit. The observed benefit of preventing microvascular complications was stable across all subgroups of predicted MACE benefit.

CONCLUSIONS

Although INT reduces the risk of MACE in the majority of individuals with type 1 diabetes, benefit varies substantially. These individual differences in the effect of INT underline the necessity for a better understanding of the individual response to intensive treatment.

Exhaustion and cardiovascular risk factors: the role of vagally-mediated heart rate variability

PURPOSE

Exhaustion symptoms are known to be associated with cardiovascular disease (CVD) risk; however, the underlying mechanisms remain unclear. Autonomic imbalance, as indicated by reductions in vagally-mediated heart rate variability (vmHRV), appears to be a valid candidate for such a biological link, as it has been associated with both exhaustion symptoms and CVD risk and mortality.

METHODS

The present study examined a potential mediation of vmHRV on the association between exhaustion symptoms and self-reported CVD risk factors as well as the age dependency of this mediation in a large, heterogeneous sample of the Dresden Burnout Study (N = 388; 72.9% females; Mage = 42.61, SD = 11.67).

RESULTS

Results indicate that exhaustion symptoms were indirectly associated with CVD risk factors through vmHRV even after adjusting for well-known confounders (i.e., sex, body mass index, depressive symptoms). Moreover, this pattern was significant only among middle-aged (i.e., 54.27 years) and older individuals.

CONCLUSIONS

Our findings add to growing evidence that autonomic imbalance may be a key biological link between exhaustion symptoms and CVD risk in middle-aged and older individuals. Implications for public health are discussed.

Community-based type 2 diabetes care by lay village health workers in rural Lesotho: protocol for a cluster-randomized trial within the ComBaCaL cohort study (ComBaCaL T2D TwiC)

BACKGROUND

Type 2 diabetes (T2D) poses a growing public health burden, especially in low- and middle-income countries (LMICs). Task-shifting to lay village health workers (VHWs) and the use of digital clinical decision support systems (CDSS) are promising approaches to tackle the current T2D care gap in LMICs. However, evidence on the effectiveness of lay worker-led T2D care models, in which VHWs initiate and monitor drug treatment in addition to community-based screening and referral services, is lacking.

METHODS

We are conducting a cluster-randomized trial nested within the Community-Based Chronic Disease Care Lesotho (ComBaCaL) cohort study (NCT05596773) using the trial within cohort (TwiC) design to assess the effectiveness of a VHW-led, CDSS-assisted T2D care model in rural Lesotho. Participants are non-pregnant members of the ComBaCaL cohort study with T2D. The ComBaCaL cohort study is conducted in approximately 100 villages in two rural districts in Lesotho and is managed by trained and supervised VHWs. In intervention villages, VHWs offer a community-based T2D care package including lifestyle counselling, first-line oral antidiabetic, lipid-lowering, and antiplatelet treatment guided by a tablet-based CDSS to participants who are clinically eligible, as well as treatment support to participants who prefer or clinically require facility-based T2D care. In control clusters, all participants will be referred to a health facility for T2D management. The primary endpoint is the mean glycosylated haemoglobin (HbA1c) 12 months after enrolment. Secondary endpoints include the 10-year risk for cardiovascular events estimated using the World Health Organization risk prediction tool.

DISCUSSION

The trial was launched on May 13, 2023, and has enrolled 226 participants at the date of submission (October 6, 2023). To our knowledge, the trial is the first to assess task-shifting of T2D care to VHWs at the community level, including the prescription of first-line antidiabetic, lipid-lowering, and antiplatelet medication in sub-Saharan Africa, and will thus provide the missing evidence on the effectiveness of such a T2D care model in this setting. The study is operating within the established Lesotho VHW programme. Similar community health worker programmes which exist across sub-Saharan Africa may benefit from the findings.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05743387. Registered on February 24 2023.

Minimal improvement in coronary artery disease risk prediction in Chinese population using polygenic risk scores: evidence from the China Kadoorie Biobank

BACKGROUND

Several studies have reported that polygenic risk scores (PRSs) can enhance risk prediction of coronary artery disease (CAD) in European populations. However, research on this topic is far from sufficient in non-European countries, including China. We aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese population.

METHODS

Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training ( n = 28,490) and testing sets ( n = 72,150). Ten previously developed PRSs were evaluated, and new ones were developed using clumping and thresholding or LDpred method. The PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing set. Genetic risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide polymorphisms. Prediction of the 10-year first CAD events was assessed using hazard ratios (HRs) and measures of model discrimination, calibration, and net reclassification improvement (NRI). Hard CAD (nonfatal I21-I23 and fatal I20-I25) and soft CAD (all fatal or nonfatal I20-I25) were analyzed separately.

RESULTS

In the testing set, 1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 years. The HR per standard deviation of the optimal PRS was 1.26 (95% CI:1.19-1.33) for hard CAD. Based on a traditional CAD risk prediction model containing only non-laboratory-based information, the addition of PRS for hard CAD increased Harrell's C index by 0.001 (-0.001 to 0.003) in women and 0.003 (0.001 to 0.005) in men. Among the different high-risk thresholds ranging from 1% to 10%, the highest categorical NRI was 3.2% (95% CI: 0.4-6.0%) at a high-risk threshold of 10.0% in women. The association of the PRS with soft CAD was much weaker than with hard CAD, leading to minimal or no improvement in the soft CAD model.

CONCLUSIONS

In this Chinese population sample, the current PRSs minimally changed risk discrimination and offered little improvement in risk stratification for soft CAD. Therefore, this may not be suitable for promoting genetic screening in the general Chinese population to improve CAD risk prediction.

Knowledge of Cardiovascular Disease Risk Factors and Its Primary Prevention Practices Among the Saudi Public - A Questionnaire-Based Cross-Sectional Study

Background and Objectives

In response to the aging population and rapid rise of chronic diseases, it is important to understand the knowledge about primary prevention. We aim to explore Saudi adults' knowledge of cardiovascular disease (CVD) risk factors and its primary prevention practices among the Saudi public.

Methods

This is a cross-sectional community-based study, conducted among people living in Saudi Arabia to assess the knowledge of CVD risk factors using a total of 24-item questionnaires divided into two sections using the Likert scale, true /False/I do not know. The data were analyzed using the statistical software SPSS v. 26.0 (SPSS Inc., Chicago, IL, USA).

Results

In this study, the 81.8% of participants (n=296) agreed that high blood pressure was a risk factor for CVD, while more than two-thirds (68.8%; n=249) believed that diabetes was a risk factor for CVD. Furthermore, about the same proportion of respondents ((79.8%; n=289) and (78.7%; n=285)) agreed that physical inactivity and smoking were risk factors for CVD. In addition, the vast majority of them (n=324; 89.5%) believed that regular exercise aids in the prevention of CVD. In contrast, 74.9% (n=271) of individuals agreed that quitting smoking helps prevent CVD. This study indicated that 55.8% (n=202) of respondents had strong knowledge of CVD, while 44.2% (n=160) had inadequate awareness of CVD risk factors and prevention methods. In terms of the association between socio-demographic factors and overall participants' knowledge of CVD risk factors and preventative measures, we discovered that age (p=0.000), gender (p=0.011), educational status (p=0.000), and the presence of chronic disease (p=0.000) were all significantly associated with CVD knowledge score levels.

Conclusion

Saudi adults have adequate knowledge of CVD risk factors and prevention interventions, but more effort is needed to raise continuous awareness to reduce the prevalence of CVD.

Influence of Socioeconomic Gender Inequality on Sex Disparities in Prevention and Outcome of Cardiovascular Disease: Data From a Nationwide Population Cohort in China

Background Knowledge gaps remain in how gender-related socioeconomic inequality affects sex disparities in cardiovascular diseases (CVD) prevention and outcome. Methods and Results Based on a nationwide population cohort, we enrolled 3 737 036 residents aged 35 to 75 years (2014-2021). Age-standardized sex differences and the effect of gender-related socioeconomic inequality (Gender Inequality Index) on sex disparities were explored in 9 CVD prevention indicators. Compared with men, women had seemingly better primary prevention (aspirin usage: relative risk [RR], 1.24 [95% CI, 1.18-1.31] and statin usage: RR, 1.48 [95% CI, 1.39-1.57]); however, women's status became insignificant or even worse when adjusted for metabolic factors. In secondary prevention, the sex disparities in usage of aspirin (RR, 0.65 [95% CI, 0.63-0.68]) and statin (RR, 0.63 [95% CI, 0.61-0.66]) were explicitly larger than disparities in usage of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (RR, 0.88 [95% CI, 0.84-0.91]) or β blockers (RR, 0.67 [95% CI, 0.63-0.71]). Nevertheless, women had better hypertension awareness (RR, 1.09 [95% CI, 1.09-1.10]), similar hypertension control (RR, 1.01 [95% CI, 1.00-1.02]), and lower CVD mortality (hazard ratio, 0.46 [95% CI, 0.45-0.47]). Heterogeneities of sex disparities existed across all subgroups. Significant correlations existed between regional Gender Inequality Index values and sex disparities in usage of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (Spearman correlation coefficient, r=-0.57, P=0.0013), hypertension control (r=-0.62, P=0.0007), and CVD mortality (r=0.45, P=0.014), which remained significant after adjusting for economic factors. Conclusions Notable sex disparities remain in CVD prevention and outcomes, with large subgroup heterogeneities. Gendered socioeconomic factors could reinforce such disparities. A sex-specific perspective factoring in socioeconomic disadvantages could facilitate more targeted prevention policy making.

Women, lipids, and atherosclerotic cardiovascular disease: a call to action from the European Atherosclerosis Society

Cardiovascular disease is the leading cause of death in women and men globally, with most due to atherosclerotic cardiovascular disease (ASCVD). Despite progress during the last 30 years, ASCVD mortality is now increasing, with the fastest relative increase in middle-aged women. Missed or delayed diagnosis and undertreatment do not fully explain this burden of disease. Sex-specific factors, such as hypertensive disorders of pregnancy, premature menopause (especially primary ovarian insufficiency), and polycystic ovary syndrome are also relevant, with good evidence that these are associated with greater cardiovascular risk. This position statement from the European Atherosclerosis Society focuses on these factors, as well as sex-specific effects on lipids, including lipoprotein(a), over the life course in women which impact ASCVD risk. Women are also disproportionately impacted (in relative terms) by diabetes, chronic kidney disease, and auto-immune inflammatory disease. All these effects are compounded by sociocultural components related to gender. This panel stresses the need to identify and treat modifiable cardiovascular risk factors earlier in women, especially for those at risk due to sex-specific conditions, to reduce the unacceptably high burden of ASCVD in women.

Association of Leisure-Time Physical Activity and Mortality Risk in High Cardiovascular Risk Population with and without Left Ventricular Hypertrophy

Background

Increased leisure-time physical activity (LTPA) is linked with decreased mortality risk, while also with increased left ventricular mass, which may induce left ventricular hypertrophy (LVH). We investigated whether LVH modifies the association between higher LTPA and lower mortality risk in population at high cardiovascular risk.

Methods

In a prospective national cohort, we used the left ventricular mass/body surface area (LVM/BSA) method to define LVH. Baseline LTPA was self-reported and divided into: low ( < 500 metabolic equivalent of task [MET]) min/week), moderate (500-1999 MET min/week) and high ( ≥ 2000 MET-min/week). Analyses of the dose-response relationship between LTPA and left ventricular mass were performed using restricted cubic spline regression. A multivariate adjusted Cox proportional hazards regression analysis was used to estimate hazard ratios (HRs).

Results

A total of 163,006 participants (55.3% females, mean [standard deviation] age, 62.4 [7.4] years) were included. During a median of 4.8 years of follow-up, 6586 (4.0%) died from all causes and 3024 (1.9%) from cardiovascular causes. Multivariate adjusted Cox proportional hazards regression analyses revealed that moderate and high LTPA were linked with less cardiovascular and all-cause mortality risk than low LTPA in the absence of LVH. In those with LVH, the association of high (0.83, 0.69-0.99) or moderate (0.72, 0.56-0.91) LTPA with cardiovascular mortality risk persisted. For all-cause mortality risk, this association was only significant in high LTPA (0.73, 0.61-0.86), while marginal in moderate LTPA (0.96, 0.84 to 1.08). Overall, the correlation patterns between LTPA and mortality risk appears distinct between those with LVH and those without LVH; the modification of LVH was not significant regarding mortality risk among the high cardiovascular risk population (all-cause: p-value for interaction = 0.074; cardiovascular cause: p-value for interaction = 0.581), except in females regarding all-cause mortality risk (p-value for interaction = 0.006).

Conclusions

The association between higher LTPA and lower mortality risk was not modified by LVH in high cardiovascular risk population. However, the presence of LVH altered this association in females regarding the all-cause mortality risk.

Ten-Year Risk for Developing Cardiovascular Disease Among Older Adults and Elderly in India: A Secondary Analysis of Wave-1 of Longitudinal Aging Study in India

Background Cardiovascular disease (CVD) risk stratification is recommended by the World Health Organization (WHO) for effective CVD management in primary healthcare settings. Using the 2019 updated WHO CVD risk charts, we estimated the 10-year risk for developing fatal and non-fatal CVD among participants of the Longitudinal Aging Study in India (LASI). Methods We conducted secondary data analysis using the Wave-1 dataset of LASI. Analysis was performed in Stata software (version 14.1; StataCorp LLC, College Station, Texas) after applying sample weights. Ten-year CVD risk was estimated using a non-laboratory-based CVD risk chart. Logistic regression analysis was performed to determine the association between socio-demographic characteristics and 10% or more 10-year CVD risk. Results The weighted prevalence of 10% or more 10-year CVD risk was 24.70% (95% CI: 23.94%-25.47%). Participants who were currently working, living alone, and widowed had 3.63, 1.42, and 1.59 times increased odds of having a high 10-year CVD risk, respectively, after adjusting for other variables. Conclusion About a quarter of older adults and the elderly population in India have a 10-year risk for a fatal or non-fatal cardiovascular event of 10% or more, as estimated using a non-laboratory based chart.

POST-IVUS: A perceptual organisation-aware selective transformer framework for intravascular ultrasound segmentation

Intravascular ultrasound (IVUS) is recommended in guiding coronary intervention. The segmentation of coronary lumen and external elastic membrane (EEM) borders in IVUS images is a key step, but the manual process is time-consuming and error-prone, and suffers from inter-observer variability. In this paper, we propose a novel perceptual organisation-aware selective transformer framework that can achieve accurate and robust segmentation of the vessel walls in IVUS images. In this framework, temporal context-based feature encoders extract efficient motion features of vessels. Then, a perceptual organisation-aware selective transformer module is proposed to extract accurate boundary information, supervised by a dedicated boundary loss. The obtained EEM and lumen segmentation results will be fused in a temporal constraining and fusion module, to determine the most likely correct boundaries with robustness to morphology. Our proposed methods are extensively evaluated in non-selected IVUS sequences, including normal, bifurcated, and calcified vessels with shadow artifacts. The results show that the proposed methods outperform the state-of-the-art, with a Jaccard measure of 0.92 for lumen and 0.94 for EEM on the IVUS 2011 open challenge dataset. This work has been integrated into a software QCU-CMS2 to automatically segment IVUS images in a user-friendly environment.