Cardiovascular Disease In Patients Research Articles

Abstract 4123540: Cardiovascular Health and Cancer Incidence and Mortality: NHANES-III and -Continuous study

Background: Cancer and cardiovascular disease (CVD) are the leading causes of death worldwide. Limited evidence is available regarding the relationship between CVD, cardiovascular risk factors (CVRF), and cancer mortality; and how CVRF further modify that relationship. Methods: The first part included 438 and 2100 CVD patients aged 65+ from NHANES-III and Continuous (1999-2016) datasets, respectively. Competing risk models with subdistribution hazards ratio (aHR) were used to identify risk factors for cancer incidence. The second part included 44,591 adult individuals from NHANES-Continuous merged with Medicare and National Death Index mortality data until the end of 2018. We included individuals with no history of cancer at baseline. We used competing risk modeling to test the relationship between CVD at baseline and cancer mortality. We also conducted a comprehensive risk factor analysis. Results: In the first part (Figure), females in NHANES-III had lower cancer risk (aHR 0.39, P=0.001) compared to males. Poor physical activity was associated with increased cancer risk in both datasets (aHR 2.59 in NHANES-III, aHR 1.59 in Continuous). In NHANES-Continuous, age (aHR 1.07, P<0.001) and current smoking (aHR 2.55, P=0.001) showed a significant association with developing cancer. No other factors investigated showed significant associations. In the second analysis (Table), the included sample size represented 1,738,423,317 individuals (52% females, 67% non-Hispanic Whites, and 9% Hispanics). Competing risk modeling showed a significantly higher risk of cancer mortality in individuals with CVD (aHR 1.37, 95% CI 1.07-1.76, P=0.01) after adjusting for age, sex, and race/ethnicity. Notably, cancer mortality increased with aging (aHR 1.08, 95%CI 1.05-1.11, P<0.0001), current smoking status (aHR 6.78, 95%CI 3.43-13.42, P<0.0001), and obesity (aHR 2.32, 95%CI 1.13-4.79, P=0.02). Finally, a significant interaction (P=0.034) was found where those with CVD and obesity showed higher cancer mortality than those with normal BMI (aHR, 95%CI 1.03-2.91, P=0.04). Conclusions: Our study highlights the close relationship between cardiovascular health and cancer, including among CVD patients. Our findings suggest that physical activity and obesity may play a significant role in cancer incidence and mortality among the general population and CVD patients. These findings emphasize the need for more proactive approach in the management of shared risk factors for CVD and cancer.

Transient Ischemic Attack and Mild Stroke Participant Perspectives on Barriers and Enablers to Participation in Cardiovascular Rehabilitation

Background Exercise-based cardiac rehabilitation reduces the risk factors and recurrence of cardiovascular disease in patients with coronary heart disease. Despite similar risk factors, people with transient ischemic attack (TIA) and mild stroke do not attend cardiac rehabilitation. Cardiovascular rehabilitation (CVR), including TIA, stroke, and coronary heart disease, could be a solution for increasing participation. Perspectives from TIA and stroke survivors on barriers and enablers to participation in CVR are limited, and implementation strategies for CVR are currently unknown. Objectives We sought to determine (1) What were the perspectives of participants with TIA and mild stroke on barriers and enablers to uptake, engagement, and participation in CVR? and (2) What implementation strategies may influence people with TIA and mild stroke to participate in CVR? Methods In-depth semistructured interviews were conducted with CVR participants. Inductive thematic analysis was completed before deductively mapping themes to implementation frameworks, the Capability, Opportunity, Motivation, and Behavior Model and Theoretical Domains Framework. Results Twenty participants aged 73 ± 11 years were interviewed. Most were men, stroke survivors, tertiary educated, and retired. Six themes were generated to explain the barriers and enablers to CVR participation. Themes and subthemes mapped to 8 Theoretical Domains Framework domains and 5 Capability, Opportunity, Motivation, and Behavior constructs. Prioritizing participants' physical and social opportunities, reflective motivation, and physical and psychological capabilities may improve their participation in CVR. Conclusions Barriers and enablers to CVR participation were similar to those in the coronary heart disease population. Increasing access and availability of CVR for people with TIA and mild stroke should be prioritized for future implementation.

Abstract 4136280: Inflammation and Cancer Mortality among CVD Individuals: NHANES-Continuous study

Background: Both cancer and cardiovascular disease (CVD) are the leading causes of death worldwide. While previous research showed a relationship between CVD and cancer incidence, limited evidence is available regarding the relationship between inflammation and cancer mortality in CVD patients. Methods: A prospective cohort study using data from the continuous National Health and Nutrition Examination Survey (NHANES) (1999-2016) merged with Medicare and National Death Index (NDI) mortality data until December 31, 2018. We included CVD individuals with no history of cancer at baseline to investigate the relationship between inflammatory markers, including Neutrophil-to-Lymphocyte ratio (NLR), as the main exposure and cancer mortality as the main outcome. Results: We included 4,089 adult individuals representing 127,809,316 individuals (47% females, 72% non-Hispanic Whites, and 5% Hispanics). The risk factor analysis (Table) using the competing risk modeling showed that while inflammatory markers did not show significant associations with cancer mortality in the overall analysis, upon stratification by race/ethnicity, NH-Blacks showed higher cancer mortality with higher WBC count (aHR 5.61, 95% CI 1.66-18.91, p=0.007) and NLR (aHR 2.97, 95% CI 1.19-7.42, p=0.02), but lower cancer mortality with higher neutrophil (aHR 0.08, 95% CI 0.01-0.60, p=0.02) and lymphocyte (aHR 0.34, 95% CI 0.15-0.80, p=0.02) counts. Notably, our NH-Blacks showed lower neutrophils at baseline than others which could be explained by a phenomenon called “Benign Ethnic Neutropenia -BEN-” that still brings more complexity when interpreting NLR. Conclusions: Our study highlights the close relationship between cardiovascular health, inflammation, and cancer mortality. The findings also suggest that race/ethnicity may play a significant role in the relationship between inflammation and cancer mortality among individuals with CVD. Yet, further research is still needed to underpin the biological pathways influencing this relationship.

Abstract 4137820: Extreme heat and cardiovascular disease in a changing climate: An urgent need for risk management and health research

Background: Extreme heat can trigger or exacerbate cardiovascular disease (CVD) through ischemia or thrombosis, and its deleterious impacts are inclined to worsen as increased heat exposure and heightened vulnerability from climate change interacted with natural and social environment. Research Questions: Previous studies have primarily focused on quantifying the increased risk of CVD due to heat exposure, while lacking a comprehensive understanding of the association, underlying mechanisms, and vulnerability in CVD patients. Consequently, there is a scarcity of clinical and public health interventions aimed at preventing the convergence of extreme heat exposure and the risk of CVD within the context of climate change. Methods: We conducted a systematic search in PubMed, Embase, and Web of Science from inception to December, 2023, and we retrieved articles which assessed the effects of extreme heat or climate change on CVD. Results: In this review, we outline the existing evidence on the epidemiology and pathophysiological mechanisms that elucidate how extreme heat affects the risk of CVD. Extreme heat is associated with increased risks for CVD morbidity and mortality, where older persons, low socioeconomic status, pre-existing medical conditions, and unfavorable living environments confer greater susceptibility to heat. The adverse effects of extreme heat on cardiovascular system involved a wide range of complex mechanisms between different organs and regulatory pathways (Figure 1). Additionally, we identify the factors that contribute to the vulnerability of CVD patients to heat exposure. The discrepancy in heat-related risk can be attributed to individual susceptibility, sociocultural factors, population temperature adaptations, and environmental factors. Future climate change is projected to exacerbate the burden of extreme heat, particularly due to the interaction of air pollution, population aging, and urbanization (Figure 2). Conclusions: Addressing extreme heat should be within the framework of the prevention of CVD. Health professionals and scientists are responsible for mitigating the cardiovascular effects mediated by extreme heat, with an emphasis on engaging in risk management tactics and health research to implement preventive strategies. As CVD is a climate sensitive disease, evidence-based interventions during heat extremes are urgently needed to cope with the cardiovascular risks associated with the inevitable trajectory of climate change.

Abstract 4113047: Discovering novel biomarkers and predicting cardiovascular disease using AI/ML techniques for precision medicine

Personalized interventions are deemed vital given the intricate characteristics, advancement, inherent genetic composition, and diversity of cardiovascular diseases (CVDs). The appropriate utilization of artificial intelligence (AI) and machine learning (ML) methodologies can yield novel understandings of CVDs, enabling improved personalized treatments through predictive analysis and deep phenotyping. In this study, we proposed and employed a novel approach combining traditional statistics and a nexus of cutting-edge AI/ML techniques to identify significant biomarkers for our predictive engine by analyzing the complete transcriptome of CVD patients (Figure 1). After robust gene expression data pre-processing, we utilized three statistical tests to assess the differences in transcriptomic expression and clinical characteristics between healthy individuals and CVD patients. Next, a classifier assigned rankings to transcriptomic features based on their relation to the case-control variable. The top ten percent of commonly observed significant biomarkers were evaluated using four unique ML classifiers. After optimizing hyperparameters, the ensembled models, which were implemented using a soft voting classifier, accurately differentiated between patients and healthy individuals. We have uncovered 18 transcriptomic biomarkers that are highly significant in the CVD population that were used to predict disease with up to 96% accuracy (Figure 2). Additionally, we cross-validated our results with clinical records collected from patients in our cohort (Figure 3). The identified biomarkers served as potential indicators for early detection of CVDs. With its successful implementation, our newly developed predictive engine provides a valuable framework for identifying patients with CVDs based on their biomarker profiles.

Abstract 4140191: ChREBP Drives Brown Adipocyte Differentiation and Lipid Utilization for Excess Energy Expenditure

Introduction: Although several anti-obesity drugs have become recently available, they reduce patients’ appetite, which might worsen cardiovascular disease (CVD) prognosis by malnutrition/cachexia. Brown adipose tissue (BAT) oxidizes glucose and lipids for thermogenesis, a process that requires excess energy expenditure provided by uncoupling protein 1 (UCP1) + cells. Recently, critical roles of BAT in cardio-protection have been discovered. Taken together, boosting BAT activity can be a novel anti-obesity treatment suitable for CVD patients. In this study, we aimed to establish anti-obesity strategy by manipulation of the glucose-sensing lipid-storage transcription factor, ChREBP, with unexpected function of boosting lipid utilization in BAT. Methods and Results: Through mouse/human single-cell/nucleus RNA sequencing analyses, we identified ChREBP as specifically expressed in highly thermogenic UCP1 + brown adipocytes ( Fig.A ). To investigate the role of ChREBP in BAT formation, we generated human brown adipocyte-like model from induced pluripotent stem cells (iPSC-BAT, Fig.B ). The iPSC-BAT exhibited high UCP1 and ChREBP expression, multi-locular lipid droplets, and vigorous oxygen consumption. Knocking down ChREBP strongly blocked iPSC-BAT differentiation ( Fig.C ) and impaired lipid utilization ( Fig.D ). Consistently, in vitro deletion of ChREBP in mouse BAT progenitors impeded differentiation, lipid droplet accumulation, and oxygen consumption ( Fig.E-F ). In vivo, BAT-specific deletion of all ChREBP isoforms reduced lipid accumulation and BAT characteristics. Conversely, using a new mouse model for Cre-mediated ChREBPβ overexpression, we showed that ChREBPβ overexpression in BAT (Chβ BATOX) increased BAT cellularity and activated lipogenic machineries, with paradoxical decreased lipid content, suggesting excessively activated lipid consumption in BAT ( Fig.G ). More importantly, Chβ BATOX maintained UCP1 expression and reduced fat volume ( Fig.H ) even after strongly inhibiting BAT activity. Conclusion: In summary, ChREBP is essential for BAT development and thermogenic capacity by affecting lipid utilization. Our results suggest that ChREBPβ activation may be a novel anti-obesity avenue for CVD patients.

Risk of Cardiovascular Disease in Patients With Classical Hodgkin Lymphoma: A Danish Nationwide Register-Based Cohort Study.

Risk of cardiovascular disease (CVD) in patients with classical Hodgkin lymphoma (cHL) undergoing contemporary treatment is unclear. cHL patients ≥ 18 years at diagnosis treated with doxorubicin-containing chemotherapy between 2000 and 2022 were matched 1:5 with comparators on birth year, sex, and Charlson Comorbidity Index at time of matching (score of 0 or ≥ 1). Cause-specific cumulative incidence of a composite of CVDs with corresponding 95% confidence intervals (CIs) were computed with death and lymphoma relapse as competing events (i.e., by censoring individuals at such occurrences) using the Aalen-Johansen estimator. A total of 1905 patients and 9525 comparators with a median follow-up of 10 years (interquartile range, [IQR]: 5.9-17.4). Median age was 39 years (IQR: 27-56), median cumulative doxorubicin dose was 250 mg/m2 (IQR: 200-300). The CVD cumulative incidences were 4.7% (95% CI: 3.6-5.7) for patients versus 2.6% (95% CI: 2.3-2.9) for comparators at 5 years, 8.9% (95% CI: 7.2-10.5) versus 5.5% (95% CI: 4.9-6.0) at 10 years, and 17.0% (95% CI: 14.1-19.9) versus 8.2% (95% CI: 7.4-9.0) at 15 years. CVD remains a substantial effect after contemporary treatment for cHL, suggesting that awareness of symptoms and a low threshold for referral to diagnostic examination are still important measures during survivorship.

Association of serum uric acid with all-cause and cardiovascular mortality in cardiovascular disease patients

The relationship between serum uric acid (SUA) and mortality in patients with cardiovascular disease (CVD) remains controversial. We aimed to explore the relationship between SUA and all-cause mortality (ACM) and cardiovascular mortality (CVM) in adult patients with CVD. This cohort study included 3977 patients with CVD from the National Health and Nutrition Examination Survey (2005–2018). Death outcomes were determined by linking National Death Index (NDI) records through December 31, 2019. We explored the association of SUA with mortality using weighted Cox proportional hazards regression models, subgroup analysis, Kaplan-Meier survival curves, weighted restricted cubic spline (RCS) models, and weighted threshold effect analysis among patients with CVD. During a median follow-up of 68 months (interquartile range, 34–110 months), 1,360 (34.2%) of the 3,977 patients with cardiovascular disease died, of which 536 (13.5%) died of cardiovascular deaths and 824 (20.7%) died of non-cardiovascular deaths. In a multivariable-adjusted model (Model 3), the risk of ACM (HR 1.38, 95% CI 1.16–1.64) and the risk of CVM (HR 1.39, 95% CI 1.04–1.86) for participants in the SUA Q4 group were significantly higher. In patients with CVD, RCS regression analysis revealed a nonlinear association (p < 0.001 for all nonlinearities) between SUA, ACM, and CVM in the overall population and in men. Subgroup analysis showed a nonlinear association between ACM and CVM with SUA in patients with CVD combined with chronic kidney disease (CKD), with thresholds of 5.49 and 5.64, respectively. Time-dependent ROC curves indicated areas under the curve of 0.61, 0.60, 0.58, and 0.55 for 1-, 3-, 5-, and 10-year survival for ACM and 0.69, 0.61, 0.59, and 0.56 for CVM, respectively. We demonstrate that SUA is an independent prognostic factor for the risk of ACM and CVM in patients with CVD, supporting a U-shaped association between SUA and mortality, with thresholds of 5.49 and 5.64, respectively. In patients with CVD combined with CKD, the association of the ACM and the CVM with SUA remains nonlinear.

Multimodal AI/ML for discovering novel biomarkers and predicting disease using multi-omics profiles of patients with cardiovascular diseases

Cardiovascular diseases (CVDs) are complex, multifactorial conditions that require personalized assessment and treatment. Advancements in multi-omics technologies, namely RNA sequencing and whole-genome sequencing, have provided translational researchers with a comprehensive view of the human genome. The efficient synthesis and analysis of this data through integrated approach that characterizes genetic variants alongside expression patterns linked to emerging phenotypes, can reveal novel biomarkers and enable the segmentation of patient populations based on personalized risk factors. In this study, we present a cutting-edge methodology rooted in the integration of traditional bioinformatics, classical statistics, and multimodal machine learning techniques. Our approach has the potential to uncover the intricate mechanisms underlying CVD, enabling patient-specific risk and response profiling. We sourced transcriptomic expression data and single nucleotide polymorphisms (SNPs) from both CVD patients and healthy controls. By integrating these multi-omics datasets with clinical demographic information, we generated patient-specific profiles. Utilizing a robust feature selection approach, we identified a signature of 27 transcriptomic features and SNPs that are effective predictors of CVD. Differential expression analysis, combined with minimum redundancy maximum relevance feature selection, highlighted biomarkers that explain the disease phenotype. This approach prioritizes both biological relevance and efficiency in machine learning. We employed Combination Annotation Dependent Depletion scores and allele frequencies to identify variants with pathogenic characteristics in CVD patients. Classification models trained on this signature demonstrated high-accuracy predictions for CVD. The best performing of these models was an XGBoost classifier optimized via Bayesian hyperparameter tuning, which was able to correctly classify all patients in our test dataset. Using SHapley Additive exPlanations, we created risk assessments for patients, offering further contextualization of these predictions in a clinical setting. Across the cohort, RPL36AP37 and HBA1 were scored as the most important biomarkers for predicting CVDs. A comprehensive literature review revealed that a substantial portion of the diagnostic biomarkers identified have previously been associated with CVD. The framework we propose in this study is unbiased and generalizable to other diseases and disorders.

Association of neutrophil-percentage-to-albumin ratio with mortality in cardiovascular disease patients complicating abnormal glucose metabolism

Abstract Background Cardiovascular disease (CVD) patients complicated with abnormal glucose metabolism are at especially higher risk of cardiovascular mortality. Therefore, it is critical to identify and manage CVD patients complicated with abnormal glucose metabolism at higher risk of mortality to improve the overall prognosis of such population. Evidence regarding neutrophil-percentage-to-albumin ratio (NPAR) and survival outcomes in CVD patients complicated with abnormal glucose metabolism remains scarce. Purpose To prospectively evaluate the association of NPAR with cardiovascular and all-cause mortality in CVD patients complicating abnormal glucose metabolism. Methods This study included 3,897 CVD patients with diabetes or pre-diabetes from the National Health and Nutrition Examination Survey (NHANES, 1999-2018). Mortality status was determined by access to NHANES public-use linked mortality files. Multivariate Cox proportional hazards regression analysis, threshold effect analysis, and stratified analysis were performed to examine the association of NPAR with cardiovascular and all-cause mortality. The prognostic value of NPAR was further assessed by time-dependent receiver operating characteristic (ROC) curve analysis. Results During a median follow-up period of 76 months, there were 703 cardiovascular deaths and 1,727 all-cause deaths. After adjusting for confounders, NPAR was positively nonlinear associated with cardiovascular and all-cause mortality. Furthermore, the thresholds of NPAR were identified for cardiovascular and all-cause mortality as 14.10 and 14.49, respectively. When the NPAR exceeded the thresholds, a 1-unit increase of NPAR was associated with a 16% and 18% greater hazard ratio (HR) for cardiovascular (HR = 1.16, 95% confidence interval (CI) = 1.08–1.23, P &amp;lt; 0.001) and all-cause mortality (HR = 1.18, 95% CI = 1.13–1.22, P &amp;lt; 0.001), respectively. The time-dependent ROC curve analysis showed that the NPAR had moderate prognostic value and outperformed the neutrophil-to-lymphocyte ratio for predicting short-term survival outcomes. Conclusions The NPAR is a superior predictor of survival outcomes in CVD patients complicated with abnormal glucose metabolism. The thresholds of 14.10 and 14.49 for cardiovascular and all-cause mortality, respectively.

Out-of-hospital cardiac arrest in patients with psoriasis

Abstract Background Psoriasis is a complex autoinflammatory disease that has been associated with atherosclerosis, higher risks of cardiovascular diseases, and electrocardiographic changes. Whether these risk factors lead to higher risks of out-of-hospital cardiac arrest (OHCA) is undetermined. Purpose To investigate whether psoriasis is associated with OHCA. Method Using the nationwide Danish Cardiac Arrest Registry, we identified adult (≥18 years) OHCA patients of presumed cardiac cause with and without psoriasis between June 1st 2001 and December 31st 2019. The association of cardiac arrest was estimated using time-varying Cox regression fitted with a nested case-control design where we matched up to five controls per case on age, sex and year of OHCA and 4 comorbidities: ischemic heart disease, congestive heart failure, cardiovascular risk factors, and major extra cardiac organ disease. In subgroup analyses, the main analysis was repeated in patients with severe psoriasis (presence of inpatient hospital contact during the previous year) as compared to mild psoriasis. Results We included 43,967 OHCA cases and matched with 219,772 controls from the general population. The median age was 72 years, 68% were male and 26% had ischemic heart disease, 21% had congestive heart failure, 57% had cardiovascular risk factors, and 33% had extra cardiac organ disease (Table 1). We identified 1,145 (2.6%) cases and 4,971 (2.3%) controls who had psoriasis. Compared with cardiac arrest cases without psoriasis, cases with psoriasis had similar age and sex distribution, prevalence of ischemic heart disease, and congestive heart failure, but a higher prevalence of cardiovascular risk factors, major extra cardiac organ disease and Charlson score distribution. Psoriasis was significantly associated with higher hazard ratios of OHCA: HR 1.16 [95% confidence interval: 1.08 - 1.23] (Figure 1). Compared to no psoriasis, having severe psoriasis was significantly associated with higher hazard of OHCA: HR 1.98 [95% confidence interval: 1.10 - 3.61], while mild psoriasis was not (Figure 1). Conclusion In this nationwide nested case-control study, psoriasis was significantly associated with increased hazard of out-of-hospital cardiac arrest. Furthermore, the association was only significant with severe psoriasis compared to those without psoriasis, while mild psoriasis was not. This study highlights the importance of examining cardiovascular risk factors and prioritizing prevention of cardiovascular disease in patients with psoriasis.Figure 1Table 1

Association between estimated glomerular filtration rate and prognosis in patients with cardiovascular disease with and without sarcopenia

Abstract Background/Introduction A low estimated glomerular filtration rate (eGFR) has been identified as a poor prognostic factor in patients with cardiovascular diseases (CVD). Since serum creatinine, which defines eGFR, is a metabolite of skeletal muscle, low skeletal muscle mass can result in reduced creatinine production and potentially overestimate renal function. This raises concerns about the reliability of eGFR as a prognostic indicator in patients with both CVD and sarcopenia. The impact of this relationship, however, remains uncertain. Purpose This study aimed to explore the association between eGFR and prognosis in patients with CVD, both with and without sarcopenia. Methods We included 2,444 CVD patients (mean age 69.0 ± 13.7 years) who had assessments of eGFR and sarcopenia at discharge. Sarcopenia was diagnosed according to the 2019 Asian Sarcopenia Working Group Diagnostic Criteria. Patients were categorized into sarcopenia and non-sarcopenia groups, each further divided into high eGFR (eGFR ≥60 mL/min/1.73 m²) and low eGFR (eGFR &amp;lt;60 mL/min/1.73 m²) subgroups. Kaplan-Meier curves, log-rank tests, and multivariate Cox regression analyses were employed to compare prognoses between these groups, adjusting for age, sex, BMI, left ventricular ejection fraction (LVEF), history of myocardial infarction (MI), acute coronary syndrome (ACS), heart failure (HF), hypertension (HT), dyslipidaemia (DL), diabetes mellitus (DM), and smoking history. The primary endpoint was a composite of all-cause mortality and rehospitalization. Results Median follow-up was 1.11 (interquartile range [IQR], 0.43–2.32) years for the non-sarcopenia group and 0.94 (IQR, 0.30–2.15) years for the sarcopenia group. Event rates were 24.2% in the non-sarcopenia group and 30.8% in the sarcopenia group. Both Kaplan-Meier and log-rank tests indicated that a low eGFR, regardless of sarcopenia status, was associated with a higher incidence of composite events (p &amp;lt; 0.001). Multivariate Cox regression analysis revealed a significant association between low eGFR and increased risk of composite events in both the non-sarcopenia [hazard ratio (HR): 1.55, 95% confidence interval (CI): 1.44–1.67; p &amp;lt; 0.001] and sarcopenia groups [HR: 1.36, 95% CI: 1.25–1.48; p &amp;lt; 0.001]. Conclusion Low eGFR is associated with poor prognosis in patients with CVD, irrespective of sarcopenia status.

Effect of a cardiovascular post discharge sms support program on healthcare utilisation - the hearthealth program

Abstract Background Cardiovascular disease (CVD) is a leading cause of mortality worldwide[1]. Targeting modifiable risk factors is key to primary and secondary prevention of CVD but many barriers to good risk factor control exist[2]. SMS message programs have shown to be an efficient modality to deliver information to improve knowledge and risk factor profiles for CVD patients[3]; however, their impact on healthcare utilisation has not been thoroughly examined. The HeartHealth program is a text message post-discharge support program delivered to CVD patients. It comprised regular semi-personalised text messages providing CVD information, advice, and support to patients over a 6-month period. Purpose This study aimed to examine the impact of the Heart Health program on healthcare service utilisation. Methods Patients ≥18 years old who recently attended cardiology clinics or were discharged from a cardiology unit, between April 2020 and April 2022 were invited to the program. We compared healthcare utilisation rates in patients who enrolled into the HeartHealth text program (intervention group) to contemporaneous patients who did not enrol in the program (control group). The primary outcome was the incidence rate of all-cause healthcare utilisation events (composite of ED presentations and/or hospital admissions for any medical cause) in the 6 months post-discharge. The secondary outcomes were incidence rates of CVD events and unplanned CVD events. All analyses were adjusted for demographic and co-morbidity variables. Results 11542 patients were included in analysis (intervention: 4324, control: 7218), mean age 58.8 years, 60.7% were male, and 78.3% with English as their preferred language. HeartHealth Intervention participants had lower rates of the primary outcome of healthcare service events compared to control participants (mean number of events 0.43 intervention vs 0.52 control, adjusted rate ratio [RR], 0.91 [95% CI, 0.83-0.99], p=0.033, Table 1). The intervention was significantly more effective in older patients compared to younger patients (RR, 0.82, [95% CI, 0.72-0.93] in patients aged ≥65 years, compared to patients &amp;lt;65 years, RR, 0.98, [95% CI, 0.87-1.10]; p-value for interaction =0.043, Figure 1). The subset of CVD events and unplanned CVD events were numerically lowering in the intervention group compared to the control, but the risk ratio not statistically significantly different in adjusted models (Table 1). Conclusion This analysis demonstrates that a text message post-discharge support program for CVD patients decreased the need for healthcare service utilisation for all medical causes. Future randomised controlled trials are required to further support these findings.Figure 1:Adjusted interaction analysisTable 1:Adjusted Incidence of events

Biomarker identification and risk assessment of cardiovascular disease based on untargeted metabolomics and machine learning

Cardiovascular disease (CVD) is the leading cause of mortality, disability, and healthcare costs, with a significant impact on the elderly and contributing to premature deaths across various age groups, including those below age 70. Despite decades of transformative discoveries and clinical efforts, the challenges of diagnosis, prevention, and treatment of CVD persist on a massive scale. This study aimed to unravel potential CVD-associated biomarkers and establish a machine learning model for the risk assessment of CVD. Untargeted metabolic assay with ultra-high performance liquid chromatography-tandem mass spectrometry and routine clinical biochemistry test were undertaken on the fasting venous blood specimens from 57 subjects. Four relevant clinical traits and 164 CVD-associated metabolites were identified, especially those related to glycerophospholipid metabolism and biosynthesis of unsaturated fatty acids. The machine learning model achieved from an integrated biomarker panel of palmitic amide, oleic acid, 138-pos (the 138th detected metabolomic feature in positive ion mode), phosphatidylcholine, linoleic acid, age, direct bilirubin, and inorganic phosphate, was able to improve the accuracy of CVD risk assessment up to a high satisfactory value of 0.91. The findings indicate that disorders in the metabolic processes of biological membranes and energy are significantly associated with increased risk of vascular damage in CVD patients. With machine learning methods, the pivotal metabolites and clinical biomarkers offer a promising potential for the efficient risk assessment and diagnosis of CVD.

Impact of agitation status during intensive care on functional outcomes and mortality in patients with cardiovascular disease

Abstract Background Agitation in patients during intensive care is a frequent complication. Several studies have reported that restlessness and agitation are risk factors for prolonged intensive care unit (ICU) stay and poor prognosis. Since patients with cardiovascular disease (CVD) requiring intensive care are ageing and thereby easily affected by responses, including changes in mental status, optimal management of sedation and agitation statuses during ICU stay is considered crucial. However, the influence of different agitation levels during CVD treatment in the ICU on clinical outcomes after ICU discharge is still unclear. Purpose To investigate the associations of the agitation level during ICU stay with mortality after ICU admission and functional outcomes at hospital discharge. Methods We studied 2236 patients (mean age 67.8±0.3 years) who were admitted to the ICU of a university hospital for CVD treatment and whose highest Richmond Agitation-Sedation Scale (RASS) ≥0, measured daily during ICU stay. In addition to clinical characteristics, we investigated the incidence of all-cause mortality during hospitalization and after hospital discharge. We also measured functional outcomes at discharge among 1625 patients, including 6 minutes walk distance (6MWD), Mini-Cog test, and Patient Health Questionnaire-2 (PHQ-2) as physical, cognitive, and mental functions, respectively. In statistical analysis, patients were divided into three groups based on the highest RASS levels during ICU stay in each patient (Calm: RASS=0, Restless: RASS=1, Agitation: RASS≥2). Kaplan-Meier analysis with a log-rank test and the multivariate Cox proportional hazard model were used to clarify whether higher agitation levels were associated with all-cause mortality. Moreover, the differences between the agitation levels and functional outcomes at hospital discharge were compared using the analysis of covariance. Results During the median follow-up of 1.9 years, all-cause death occurred in 280 patients (12.5%), with an incidence rate of 5.57/100 person-years. The Restless and Agitation groups showed higher mortality than the Calm group (P&amp;lt;0.001), and higher agitation levels in the ICU were significantly associated with a higher rate of all-cause mortality (adjusted hazard ratio: 1.37, 95% confidence interval: 1.19–1.57, P&amp;lt;0.001). Furthermore, as compared with the Calm group, the Restless and Agitation groups showed significantly lower levels of 6MWD (all P&amp;lt;0.001) and Mini-cog (P=0.004 and P&amp;lt;0.001, respectively) and a higher PHQ-2 (all P&amp;lt;0.001), even after adjusting for clinical confounders. Conclusions Agitation during ICU stay in CVD patients was associated with low functional outcomes at hospital discharge and high mortality rate after discharge, irrespective of agitation level. Detailed information on the agitation status during intensive care may be an important indicator in developing management and treatment strategies for patients with CVD admitted to ICU.

Prediction of 10-year risk for recurrent atherosclerotic cardiovascular events in a secondary prevention population: Insights from CHART-2 and Suita studies in the Japanese population

Abstract Background Despite the European Society of Cardiology (ESC) guidelines advocating risk prediction models for secondary prevention in established atherosclerotic cardiovascular disease (ASCVD) patients, such models for Japanese individuals remain limited, owing to their comparatively lower ASCVD risk than Western populations. Given this gap, there is a need to develop tailored risk assessment tools for Japanese ASCVD patients to optimize secondary prevention strategies. Purpose Leveraging data from two large-scale, long-term cardiovascular cohorts in Japan, our aim was to develop and externally validate a 10-year risk model predicting recurrent cardiovascular events among patients with established ASCVD. Methods The CHART-2 and Suita studies, large-scale prospective observational multicenter cohort studies in Japan, served as the primary data sources for this investigation. From the CHART-2 study, which comprised 3,560 patients with a history of coronary artery disease or ischemic stroke, we derived our risk model. External validation was conducted using data from the Suita study, which included 445 patients with similar ASCVD backgrounds. The primary outcome of interest was a composite endpoint encompassing cardiovascular death, myocardial infarction, or stroke. Variable selection was performed based on clinically relevant factors previously employed in established risk scores (SMART, REACH, and TRS 2°P risk scores). Logistic regression was utilized for model development, and the predictive performance was assessed using the C-index. Results Over a median follow-up of 10.1 years, the derivation cohort experienced 756 cardiovascular events. Patients in the derivation cohort had an average age of 68.9 ± 10.6 years, with 91% and 24% having a history of coronary artery disease and ischemic stroke, respectively. Using logistic regression, the multivariate model revealed a higher recurrent risk associated with several factors including age, smoking status, systolic blood pressure, diabetes, renal function, number of ASCVD events, atrial fibrillation, lipid levels, left ventricular systolic dysfunction, and statin use. A simple risk score based on these predictors demonstrated a &amp;gt;5-fold gradient of 10-year recurrent risk with a C-index of 0.65 (95% CI 0.63-0.68, Figure). The prediction model was externally validated in the Suita study wit 245 cardiovascular events and a median follow-up of 10.4 years, showing good discriminative ability with a C-index of 0.64 (95% CI 0.60–0.68). Conclusion Our newly developed prediction model offers a valuable tool for identifying individuals at heightened risk of recurrent cardiovascular events over a 10-year period, thereby facilitating more targeted and effective secondary prevention strategies tailored to the unique characteristics of Japanese ASCVD patients.

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

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

Association of 5-times sit-to-stand test with muscle weakness and prognosis in older patients with cardiovascular disease

Abstract Background/Introduction In the elderly with cardiovascular disease (CVD), maintaining muscle strength and physical function is essential for preventing adverse outcomes like falls and hospitalizations. The decline in lower limb strength signals increased morbidity and mortality risks. The 5-times sit-to-stand test (5STS) is a practical method for assessing lower limb strength, yet its predictive value for muscle weakness and prognosis in older CVD patients is underexplored. Purpose This study aims to elucidate the 5STS's role in identifying muscle weakness and its impact on the prognosis of older patients with CVD, offering insights for targeted interventions. Methods We included 3585 patients aged ≥ 65 years with CVD (mean age, 75.8 ± 6.6 years, 64.5% male) who underwent assessment of the 5STS before discharge. Maximal quadriceps isometric strength (QIS) was evaluated as a marker of lower limb strength and expressed relative to body weight (% body weight: BW). The primary outcome was all-cause mortality. We used the area under the curve (AUC) of the receiver operating characteristic (ROC) curve for each sex to calculate the cut-off values of the 5STS for low QIS (male &amp;lt; 45%BW, female &amp;lt; 35%BW), which have been reported to be associated with prognosis. In addition, we performed Kaplan-Meier curves and Cox regression analyses in five groups defined by 5STS time quartile and 5STS inability to assess the prognostic significance of 5STS. Cox regression analysis was performed as a multivariate model including the following variables; age, sex, body mass index, acute coronary syndrome, heart failure, hypertension, diabetes, dyslipidemia, current smoker, prior myocardial infarction, prior heart failure, prior chronic obstructive pulmonary disease, prior dementia, albumin, hemoglobin, estimated glomerular filtration rate, C-reactive protein. Result Over a median follow-up of 2.23 years (interquartile range 0.87-4.52 years), 657 (18.3%) patients died. Kaplan-Meier analysis indicated that both slow 5STS performance and inability to execute the 5STS were significantly linked with poorer prognosis (log-rank p &amp;lt; 0.001, Figure 1). After comprehensive adjustment, the slowest quartile and inability to perform the 5STS were associated with significantly higher mortality rates compared to the fastest quartile (HR 1.34; 95% CI: 1.05-1.72; p = 0.021; HR: 2.28; 95% CI: 1.60-3.24; p &amp;lt; 0.001, Figure 2). The ROC AUC for 5STS in identifying low QIS was 0.75 (95% CI: 0.73-0.77) for males and 0.75 (95% CI: 0.72-0.77) for females, with cut-off times established at 9.71s for males and 9.48s for females. Conclusion The 5STS, assessable in diverse settings without specialized equipment and reflecting key clinical outcomes, could serve as a standard tool for evaluating lower limb function.

Bempedoic Acid, the First-in-Class Oral ATP Citrate Lyase Inhibitor with Hypocholesterolemic Activity: Clinical Pharmacology and Drug–Drug Interactions

Bempedoic acid is a new drug that improves the control of cholesterol levels, either as monotherapy or in combination with existing lipid-lowering therapies, and shows clinical efficacy in cardiovascular disease patients. Thus, patients with comorbidities and under multiple therapies may be eligible for bempedoic acid, thus facing the potential problem of drug–drug interactions (DDIs). Bempedoic acid is a prodrug administered orally at a fixed daily dose of 180 mg. The dicarboxylic acid is enzymatically activated by conjugation with coenzyme A (CoA) to form the pharmacologically active thioester (bempedoic acid–CoA). This process is catalyzed by very-long-chain acyl-CoA synthetase 1 (ACSVL1), expressed almost exclusively at the hepatic level. Bempedoic acid–CoA is a potent and selective inhibitor of ATP citrate lyase (ACL), a key enzyme in the biosynthetic pathway of cholesterol and fatty acids. The drug reduces low-density lipoprotein–cholesterol (LDL-C) (20–25%), non-high-density lipoprotein–cholesterol (HDL-C) (19%), apolipoprotein B (apoB) (15%), and total cholesterol (16%) in patients with hypercholesterolemia or mixed dyslipidemia. The drug has a favorable pharmacokinetics profile. Bempedoic acid and its metabolites are not substrates or inhibitors/inducers of cytochrome P450 (CYP450) involved in drug metabolism. On the other hand, bempedoic acid–glucuronide is a substrate for organic anion transporter 3 (OAT3). Bempedoic acid and its glucuronide are weak inhibitors of the OAT2, OAT3, and organic anion-transporting polypeptide 1B1 (OATP1B1) and 1B3 (OATP1B3). Thus, bempedoic acid could inhibit (perpetrator) the hepatic uptake of OATP1B1/3 substrate drugs and the renal elimination of OAT2 and OAT3 substrates and could suffer (victim) the effect of OAT3 transporter inhibitors, reducing its renal elimination. Based on these pharmacological characteristics, here, we describe the potential DDIs of bempedoic acid with concomitant medications and the possible clinical implications.

Association between coexisting hypertension, dyslipidaemia and elevated C reactive protein with cardiovascular disease and mortality: a cross-sectional and longitudinal analysis in a representative cohort of older US adults

ObjectiveHypertension and dyslipidaemia are established risk factors for cardiovascular disease (CVD) but they are often insufficient on their own to predict CVD. Inflammation also contributes to CVD, but research on...