Central illustration. Coloured bars in the left panel show the impact of age and ethnicity on an individual\'s lifetime ASCVD risk mediated by cumulative exposure to LDL-C. Even younger individuals with a greater cumulative exposure to LDL-C, despite their age, may have a higher overall risk compared to older individuals with a lower cumulative exposure to LDL-C.Image, graphical abstract.

UNASSIGNED: Studies have shown that both home-based cardiac rehabilitation (HBCR) and center-based cardiac rehabilitation (CBCR) exhibit comparable efficacy in reducing mortality during short-term follow-up periods of up to 12 months. However, research on sex- and race-specific outcomes associated with HBCR is limited. This study examines all-cause mortality and hospital readmission among patients referred to HBCR, with stratification by sex and race.
UNASSIGNED: This Kaiser Permanente Southern California (KPSC) retrospective cohort study followed 6,868 patients from HBCR referral until death, disenrollment, or December 31, 2021. There were 3,835 HBCR graduates, 722 non-graduates, and 2,311 non-enrolled patients. Cox models were used to estimate hazard ratios (HR) and 95 % confidence intervals (CI) comparing 1) HBCR graduates vs. non-enrolled, and 2) HBCR graduates vs. non-graduates, stratified by sex and race. Differential outcomes among strata were analyzed using Kaplan-Meier curves.
UNASSIGNED: Among the 6,868 patients referred to HBCR, 4693 (68.3 %) were male, 2,175 (31.7 %) female, 870 (12.7 %) Asian/Pacific Islander, 731 (10.6 %) African American, 1,612 (23.6 %) Hispanic/Latino, and 3,646 non-Hispanic White (53.1 %). Over a mean follow-up period of 2.28 years, HBCR graduates, compared to patients who did not enroll in HBCR, had overall significantly lower risks of all-cause mortality and hospitalization. These results remained significant with stratification by sex and race. Compared to HBCR non-graduates, HBCR graduates overall had significantly lower risks of all-cause mortality and hospitalization. In the same comparison, mortality risk was significantly reduced for male and White patients; risk of hospital readmission was significantly reduced in both sexes, African American, and White patients. Among HBCR graduates, no significant differences in all-cause mortality or hospital readmission were observed across sexes and races.
UNASSIGNED: HBCR participation is associated with reduction of all-cause mortality and hospital readmission rates across sexes and races. Notably, we observed benefits at varying levels of engagement, which suggests that even partial completion of HBCR is associated with risk reduction. Among HBCR graduates, we found similar outcomes across sexes and races, which suggests that the program can be effective among diverse patient groups.

OBJECTIVE: Most prediction models for coronary artery disease (CAD) compile biomedical and behavioural risk factors, using linear multivariate models. This study explored the potential of integrating positive psychosocial factors (PPFs), including happiness, satisfaction with life, and social support, into conventional and machine learning-based CAD prediction models.
METHODS: We included UK Biobank participants without CAD at baseline. First, we estimated associations of individual PPFs with subsequent acute myocardial infarction (AMI) and chronic ischaemic heart disease (CIHD) using logistic regression. Then, we compared the performances of logistic regression and eXtreme Gradient Boosting (XGBoost) prediction models when adding PPFs as predictors to the Framingham Risk Score (FRS).
RESULTS: Based on a sample size between 160,226 and 441,419 of UK Biobank participants, happiness, satisfaction with health and life, and participation in social activities were linked to lower AMI and CIHD risk (all p-for-trend ≤ 0.04), while social support was not. In a validation sample, adding PPFs to the FRS using logistic regression and XGBoost prediction models improved neither AMI (AUC change: 0.02% and 0.90%, respectively) nor CIHD (AUC change: -1.10% and -0.88%, respectively) prediction.
CONCLUSIONS: PPFs were individually linked to CAD risk, in line with previous studies, and as reflected by the new European Society of Cardiology guidelines on cardiovascular disease prevention. However, including available PPFs in CAD-prediction models did not improve prediction compared to the FRS alone. Future studies should explore whether PPFs may act as CAD-risk modifiers, especially if the individual\'s risk is close to a decision threshold.
Positive psychosocial factors like happiness, satisfaction with health and life, social support and social activities can aid in successfully managing life\'s challenges, stress and disease. Consequently, they may help lower the risk and progression of cardiovascular disease. The study confirmed that positive psychosocial factors were associated with lower risks of myocardial infarction and chronic ischaemic heart disease. These findings underscore the role of positive psychosocial factors as risk modifiers for coronary artery disease, as recom-mended by the 2021 ESC Guidelines on cardiovascular disease prevention. This means that the individual risk of getting a coronary artery disease can be shifted to the next lower risk category by higher levels of happiness, satisfaction with health and life, and social support.

Heart failure (HF) is a major cause of mortality and morbidity in the United States that carries substantial healthcare costs. Multiple risk prediction models and strategies have been developed over the past 30 years with the aim of identifying those at high risk of developing HF and of implementing preventive therapies effectively. This review highlights recent developments in HF risk prediction tools including emerging risk factors, innovative risk prediction models, and novel screening strategies from artificial intelligence to biomarkers. These developments allow more accurate prediction, but their impact on clinical outcomes remains to be investigated. Implementation of these risk models in clinical practice is a considerable challenge, but HF risk prediction tools offer a promising opportunity to improve outcomes while maintaining value.

Purpose: Epidemiological studies have shown an association between coronary artery disease (CAD) and osteoporosis. We studied the prevalence of CAD among postmenopausal women with osteoporosis. Factors that were significantly associated with CAD were also assessed. Methods: This was a cross-sectional study conducted over a period of 2 years. Consecutive postmenopausal women aged ≥50 years were recruited. The details of an underlying CAD were obtained. Bone biochemical parameters, bone mineral density and body composition were assessed. Results: A total of 370 postmenopausal women with mean (standard deviation [SD]) ages of 61.6 (6.2) and 60.1 (6.0) years and a body mass index of 25.3 (14.1) kg/m2 were recruited. Among them, 110 of 370 patients (29.7%) had an underlying CAD and 222 of 370 (60%) had osteoporosis at either the femoral neck or lumbar spine (LS). The odds of CAD among those with osteoporosis were 3.5 (95% confidence interval [CI]: 2.1-5.9). An LS T-score of ≤-2.2 had a sensitivity of 80% and a specificity of 45% in predicting CAD (area under the curve, AUC: 0.736; 95% CI: 0.677-0.795; p<0.001). A femoral neck T-score of ≤-1.9 had a sensitivity of 80% and a specificity of 60% in predicting CAD (AUC: 0.748; 95% CI: 0.696-0.800; p<0.001). On a logistic regression analysis after adjusting for various clinical parameters, femoral neck osteoporosis had the highest odds of CAD. Conclusion: The prevalence of CAD was higher among postmenopausal women with osteoporosis. Femoral neck osteoporosis conferred the highest odds of CAD after adjustment for other clinical factors.

Pulmonary hypertension (PH) is rarely a cause of syncope. We highlight an unusual presentation of pulmonary hypertension where management was a veritable challenge. We present a case report of a 35-year-old female with a history of stage 2 hypertension, polycystic ovarian syndrome, and obesity who presented to the hospital with a six-month history of progressive shortness of breath, lower extremity swelling, and recurrent syncope. Further evaluation with transthoracic echocardiography showed features consistent with severe pulmonary hypertension. This untreated severe pulmonary hypertension culminated in cardiogenic shock due to right ventricular (RV) failure. Successful care in this patient population entails preventing the acute downward spiral of decompensated right ventricular failure.

BACKGROUND: There have been limited studies examining age-dependent associations between physical inactivity and cardiovascular disease (CVD). We aimed to clarify the age-dependent relationship of physical inactivity with incident CVD.
METHODS: We analyzed 1,097,424 participants, aged 18 to 105 years, without histories of CVD, enrolled in the DeSC database (median age, 63 years; 46.4% men). We categorized participants into the following 4 groups based on age: ≤ 44 years (n = 203,835); 45 to 64 years (n = 403,619); 65 to 79 years (n = 437,236); and ≥ 80 years (n = 52,734). We used 3 physical inactivity components gained from the self-reported questionnaire during a health checkup. The outcomes were composite CVD events including myocardial infarction, stroke, heart failure, and each CVD event.
RESULTS: During a mean follow-up of 3.2 ± 1.9 years, 81,649 CVD events were observed. The hazard ratios of 3 physical inactivity components for CVD events increased with age category (P for interaction < 0.001). For example, the hazard ratio (95% confidence interval) of physical inactivity defined as not doing light sweaty exercise for 30 minutes at least twice a week for incident CVD in the groups aged ≤ 44 years, 45 to 64 years, 65 to 79 years, and ≥ 80 years were 0.97 (0.88-1.05), 1.08 (1.05-1.12), 1.12 (1.10-1.15), and 1.17 (1.12-1.21), respectively (P for interaction < 0.001). This association was consistent across subtypes of CVD including heart failure, myocardial infarction, and stroke.
CONCLUSIONS: The association of physical inactivity with a higher risk of developing CVD increased with age. Preventive efforts for physical activity optimization may be more valuable in older people.

This comprehensive review explores the various scenarios of atherosclerosis, a systemic and chronic arterial disease that underlies most cardiovascular disorders. Starting from an overview of its insidious development, often asymptomatic until it reaches advanced stages, the review delves into the pathophysiological evolution of atherosclerotic lesions, highlighting the central role of inflammation. Insights into clinical manifestations, including heart attacks and strokes, highlight the disease\'s significant burden on global health. Emphasis is placed on carotid atherosclerosis, clarifying its epidemiology, clinical implications, and association with cognitive decline. Prevention strategies, lifestyle modifications, risk factor management, and nuanced antithrombotic treatment considerations are critical to managing cardiovascular complications, thus addressing a crucial aspect of cardiovascular health.

BACKGROUND: Cardiovascular imaging results offer valuable information that can guide health decisions, but their impact on medication use and adherence is unclear. This systematic review and meta-analysis aimed to determine the downstream impact of cardiovascular imaging results on medication use and adherence.
METHODS: Searches were conducted across databases, including MEDLINE, PsychINFO, EMBASE, and relevant references up to 2024. Data were extracted from studies comparing outcomes for individuals with diseased versus normal arteries and trials comparing outcomes for individuals who were provided imaging results versus those with no access to imaging results and analysed in 2023 and 2024. Pooled odds ratios (ORs) for outcomes were calculated.
RESULTS: The analysis included 29 studies with 24 contributing data points. Initiation (OR:2.77;95% CI:1.82-4.20) and continuation (OR:2.06;95% CI:1.28-3.30) of lipid-lowering medications (LLMs), antihypertensives (OR:2.02;95% CI:1.76-2.33), and antiplatelets (OR:2.47;95% CI:1.68-3.64) were significantly higher in individuals with diseased arteries. The proportion of individuals on LLM increased by 2.7-fold in those with diseased arteries and 1.5-fold in those with normal arteries post-screening. The proportion on LLM increased by 4.2 times in the imaging group and 2.2 times in the \"no imaging group\" post-screening. There was a significant increase in LLM initiation (OR:2.37;95% CI: 1.17-4.79) in the imaging group, but medication continuation did not significantly differ between the imaging and \"no imaging group\".
CONCLUSIONS: Cardiovascular imaging results can prompt initiation of medications, particularly lipid-lowering medications, reflecting a proactive response to identified risk factors. However, evidence regarding medication continuation is mixed, and further research is required.

Improved upstream primary prevention of cardiovascular disease (CVD) would enable more individuals to lead lives free of CVD. However, there remain limitations in the current provision of CVD primary prevention, where artificial intelligence (AI) may help to fill the gaps. Using the data informatics capabilities at the National University Health System (NUHS), Singapore, empowered by the Endeavour AI system, and combined large language model (LLM) tools, our team has created a real-time dashboard able to capture and showcase information on cardiovascular risk factors at both individual and geographical level- CardioSight. Further insights such as medication records and data on area-level socioeconomic determinants allow a whole-of-systems approach to promote healthcare delivery, while also allowing for outcomes to be tracked effectively. These are paired with interventions, such as the CHronic diseAse Management Program (CHAMP), to coordinate preventive cardiology care at a pilot stage within our university health system. AI tools in synergy allow the identification of at-risk patients and actionable steps to mitigate their health risks, thereby closing the gap between risk identification and effective patient care management in a novel CVD prevention workflow.