Ex vivo cardiac simulators are an ideal solution to the rising burden of cardiovascular disease by leveraging native tissue to replicate patient hemodynamics with high fidelity. Their continued evolution necessitates a review of the technology’s development and analysis of simulator use in pre-operative planning, surgical training, and medical device development. Artificial intelligence and multi-organ couplings are discussed in relation to overcoming existing limitations and shaping the field of personalized medicine.
Optical coherence tomography (OCT) enables high-resolution in vivo assessment of coronary atherosclerosis, identifying vulnerable plaque features linked to progression and adverse cardiovascular events across stable and acute coronary syndromes. OCT-defined high-risk morphology may add information beyond physiology, particularly in diabetes, multivessel disease, and post-ACS residual lesions. However, these findings remain risk markers, not standalone treatment indications. Advances in automation, AI, and hybrid imaging may support clinical translation.
Heart rate variability (HRV) has well-documented associations with cardiometabolic disease. However, HRV is also affected by a wide range of other factors. We hypothesized that the presence of specific passive context or external structured conditions to the collection of physiologic data might enhance the information content of these data. To test this, we analyzed HRV (specifically SDNN) collected during different contexts (“perturbations”) using data from the Apple Heart and Movement Study (AHMS). We measured HRV’s association with seven cardiometabolic diseases using the area under the receiver operating characteristic curve (AUROC). We first examined the effect of two passive perturbations that controlled for circadian variation. We then explored the effect of an active perturbation, specifically a mindful-breathing session (mindful HRV). While the passive perturbations did not result in significant increases in information content for any cardiometabolic phenotypes, mindful HRV added discriminant information for all seven cardiometabolic diseases (difference in AUROC 0.026-0.180 compared with non-mindful HRV). After adjusting for age, sex, and BMI, the advantage of mindful HRV remained significant for five diseases. Active perturbations, enhanced the signal for cardiometabolic status and emphasize the utility of real-time triggers for adding information content to ambient recording using wearables. (ClinicalTrials.gov Identifier: NCT04198194, 2019/12/13, Apple Heart & Movement Study).
This review integrates epidemiological, mechanistic and clinical evidence demonstrating that patients with periodontitis carry higher risks of cardiovascular events than healthy individuals. Literature from major databases was analyzed narratively. Findings indicate higher risks of myocardial infarction, stroke, and atrial fibrillation driven by systemic inflammation, endothelial dysfunction, vascular invasion, oral-gut-vascular, and epigenetic pathways. Biomarkers show diagnostic potential, while therapy improves surrogate outcomes but not hard endpoints. The review integrates evidence to inform risk stratification and prevention strategies.
We aimed to investigate if reinforcement learning (RL) can detect clinical practice variations and if transfer learning (TL) can mitigate resulting distribution shifts across patient sexes and sites. Using data from over 41,000 patients with obstructive coronary artery disease (CAD) in Alberta, Canada from 2009 to 2019, we conducted three experiments: 1) evaluate physician behavior policies across stratified groups using off-policy evaluation (OPE); 2) develop and evaluate RL policies using conservative Q-learning and OPE for each group; and 3) apply TL to improve RL performance on target groups. Female patients had significantly lower expected rewards under their own physician policies compared to males. Applying the physician policies learned from male patients improved rewards for females but remained lower than those for males. RL policies outperformed physician policies. TL with only 10% of target group data effectively mitigated distribution shifts. Residual confounding warrants further research to validate our findings.
Abstract Sudden arrhythmic death remains a major clinical risk in ischemic heart disease (IHD), underscoring the need for improved risk stratification. Late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) provides measures of scar burden and heterogeneity, but its incremental prognostic value beyond conventional markers such as left ventricular ejection fraction remains uncertain. We analysed two independent IHD cohorts (Dataset 1: n = 399, 54 events; National Research Ethics Service approvals 07/H0708/83 and 09/H0504/104+5; Dataset 2: n = 424, 50 events; derived from the prospectively registered REVIVED-BCIS2 trial, ISRCTN45979711, registered 20 November 2012)using clinical and LGE-CMR-derived variables to evaluate the contribution of LGE-CMR features, and compare machine learning-based survival modelling approaches. A brute-force feature-selection strategy identified optimal predictor subsets for Cox proportional hazards models, Random Survival Forests, and DeepSurv, evaluated using cross-cohort and pooled validation strategies. Scar entropy consistently emerged as a strong predictor of major arrhythmic events. Non-linear approaches outperformed Cox regression, with DeepSurv demonstrating superior generalization across cohorts and Random Survival Forests showing robust performance in pooled analyses. These findings support scar heterogeneity as an important prognostic marker and suggest that machine-learning survival models may improve arrhythmic risk prediction in patients with IHD.
Remote photoplethysmography (rPPG) can evaluate real-time changes in blood flow volume by capturing facial videos and analyzing the color changes. Although the rPPG technique enables contactless heart rate (HR) monitoring, it remains highly susceptible to ambient lighting variations. Previous studies have demonstrated the critical influence of facial skin detection on the extracted rPPG signals. In this research, we defined 15 facial regions of interest (ROIs) based on anatomical criteria and evaluated their HR measurement performance on two public datasets (BUAA-MIHR and MMPD) using four representative rPPG algorithms (CHROM, LGI, OMIT, and POS). The experimental results confirmed that the glabella, nasal dorsum, and malar regions consistently serve as robust physiological signal sources under complex illumination environments. Furthermore, we revealed the significant advantage of multi-ROI combinations compared to both single-ROI and holistic-face strategies. Our work provides data-supported insights for establishing novel HR measurement pipelines with enhanced accuracy and robustness.
Conflicting data exist about whether race/ethnicity affects risk of atrial fibrillation (AF) but less is known about how race/ethnicity is associated with AF burden in paroxysmal AF. We identified members of Kaiser Permanente Northern and Southern California healthcare systems who underwent 14-day continuous ambulatory electrocardiographic monitoring (ZIO® XT Patch, iRhythm Technologies, Inc.) between October 2011-October 2016 and had paroxysmal AF during monitoring. Self-reported race/ethnicity, other demographics, and stroke risk factors were obtained from electronic health records. Multivariable models evaluated the association of race/ethnicity with log-transformed AF burden (i.e., percentage of analyzable time in AF). Among 1069 adults with paroxysmal AF confirmed on continuous electrocardiographic monitoring, mean age was 69.1 years, with 45% women, 4% Black, 13% Asian/Pacific Islander, and 11% Hispanic. Median AF burden was 4% (IQR:1-13%) and varied by race/ethnicity: White (3.6%), Black (1.4%), Asian/Pacific Islander (5.7%), Hispanic (2.5%). In multivariable analyses, compared to White patients, Black patients had lower AF burden (adjusted relative estimate: -58%, 95%CI:-78% to -21%), while Asian/Pacific Islander patients had higher AF burden (adjusted relative estimate: 57%, 95%CI:7% to 130%). These findings have implications about the utility of extended continuous electrocardiographic monitoring for better understanding AF and for personalizing management across diverse populations.
Abstract The metabolic vulnerability index (MVX) captures metabolic-inflammatory vulnerability, but its joint relevance with Life’s Essential 8 (LE8) for major adverse cardiovascular events (MACE) is unclear. We analyzed 239,135 UK Biobank participants free of baseline MACE. MVX was calculated from six NMR-based biomarkers. LE8 scores were classified as low (<60), moderate (60–79), or high (≥80) cardiovascular health (CVH). Cox models evaluated associations of MVX and LE8 with incident MACE; joint-effect, interaction, counterfactual, and mediation analyses were conducted. Over a median 13.6 years, 17,146 MACE occurred. Higher MVX was associated with higher MACE risk (HR = 1.08, 95% CI: 1.07, 1.10), whereas high CVH was associated with lower risk compared to low CVH (HR = 0.44, 95% CI: 0.41, 0.47). Participants with low CVH and MVX Q4 had the highest risk (HR = 2.84, 95% CI: 2.60, 3.12). Additive interaction was evident for MACE and myocardial infarction. Counterfactual and mediation analyses suggested that better CVH could prevent a substantial proportion of events, partly through lower metabolic vulnerability. Combined MVX and LE8 assessment may improve cardiovascular risk stratification and support targeted prevention.
Ex vivo heart perfusion (EVHP) has enabled the use of hearts donated after circulatory death (DCD), expanding the donor pool but with persistently higher rates of rejection and graft dysfunction. The molecular consequences of EVHP, however, remain incompletely defined. We quantified 11,083 proteins in perfusate from 20 human DCD hearts undergoing EVHP using an aptamer-based proteomic platform. Among the most strongly upregulated proteins were inflammatory cytokines IL-6 (log₂FC = 3.5, FDR = 8.9 × 10-6), IL-8 (CXCL8; log₂FC = 2.8, FDR = 4.7 × 10-6), and CCL2/MCP-1 (log₂FC = 2.8, FDR = 2.0 × 10-6). Levels of these cytokines correlated strongly with perfusion duration (Spearman ρ = 0.77-0.78, FDR < 5 × 10-5). Pathway analysis demonstrated enrichment of innate immune signaling, including interleukin-1 signaling (normalized enrichment score (NES) = 2.14, adjusted p = 0.0016) and leukocyte chemotaxis pathways. These cytokine findings were validated in an independent human cohort using multiplex immunoassay and reproduced in a swine DCD perfusion model. Together, these data identify a conserved, time-dependent innate immune response during EVHP and suggest that inflammatory activation may represent one mechanism linking prolonged perfusion to graft dysfunction after DCD heart transplantation.
Heart failure with preserved ejection fraction (HFpEF) is a complex condition associated with high morbidity and mortality. This exploratory study aimed to assess the prognostic value of left atrial (LA) stiffness, exercise tolerance, and selected biomarkers in patients with HFpEF. We evaluated LA mechanics using 2D speckle tracking in 43 patients (mean age: 77.2 years) from the OPTIMISE HFpEF study (NCT03617848). Biomarkers such as N-terminal pro-brain-type natriuretic peptide, growth differentiation factor 15, and galectin-3 were measured. Patients also completed a six-minute walk test. Over a mean follow-up of 24.5 months, there were five deaths (11.4%) and 21 all-cause hospitalisations (48.8%). LA stiffness (HR: 1.81; p = 0.028) and N-terminal pro-brain-type natriuretic peptide (HR: 1.01; p = 0.013) were independent mortality predictors. For hospitalisations, six-minute walk distance (HR: 0.99; p = 0.011) and growth differentiation factor 15 (HR: 1.01; p = 0.007) were significant independent predictors. This exploratory analysis indicates that LA stiffness, N-terminal pro-brain-type natriuretic peptide, exercise intolerance, and growth differentiation factor 15 independently predict adverse events in HFpEF. Implementing a comprehensive therapeutic approach, including lifestyle modifications, medical therapy, and, if necessary, more advanced interventions to improve LA mechanics, functional capacity, and clinical biomarkers, may improve outcomes for HFpEF patients.
Paediatric congenital heart disease remains an important contributor to childhood morbidity in The Gambia. Evidence from 2008 to 2022 shows improved detection and reduced in-hospital mortality due to strengthened diagnostics and clinical care. However, late presentation and limited access to definitive cardiac interventions continue to drive adverse outcomes, highlighting the need for enhanced early detection, regional cardiac services, and integrated preventive strategies.
Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality in women, yet remains under-studied and under-recognised. Pregnancy acts as a ‘cardiovascular stress test’, with haemodynamic and hormonal changes that may unmask subclinical disease or precipitate decompensation in those with existing cardiac disease. Pregnancy-related metabolic complications are under-studied risk factors for future CVD. This review explores the complex interplay between pregnancy and CVD.
Breast arterial calcification (BAC), frequently visible on screening mammography, is a potent biomarker for cardiovascular disease risk in women. Unlike atherosclerosis, BAC represents medial arterial calcification characterized by arterial stiffness rather than narrowing. BAC has been linked to myocardial infarction, stroke, and heart failure and may offer a scalable risk stratification tool through AI-driven quantification. Standardizing BAC measurement and reporting is essential to improving long-term clinical outcomes for women.
Acute coronary syndromes (ACS) in women differ from those in men, with age-specific variations in etiology, presentation, and outcomes. Women face distinct risk factors, from autoimmune conditions to pregnancy-associated complications, to microvascular dysfunction. Missed and delayed diagnosis and treatment, and underrepresentation in clinical research compound these risks. This review outlines the evolving mechanisms of ACS in women and calls for tailored, evidence-based strategies to improve diagnosis, prevention, and care.
Recent studies that have analyzed longitudinal data on blood pressure (BP) have led to a rapidly evolving understanding of sex differences in vascular aging phenotypes. We summarized the different BP trajectories in women and in men over the life course, and the accumulating evidence indicating that the effect of exogenous stressors, in conjunction with endogenous factors, impact BP trajectories to a larger extent in women than in men.
Lifetime management of primary mitral regurgitation requires integrating surgical and transcatheter strategies. This review evaluates initial interventions, emphasizing early timing and repair durability, and outlines subsequent reintervention pathways. Synthesizing contemporary evidence, it highlights how a multidisciplinary Heart Team must design the index procedure to preserve future therapeutic options and ensure structured longitudinal care across the patient lifespan.
Clonal haematopoiesis (CH) refers to the clonal expansion of haematopoietic stem cells in the absence of overt haematological malignancy and is common in older individuals. Recent evidence has heralded CH as a novel determinant of cardiovascular disease. This review explores the associations of CH with ischaemic heart disease, heart failure, atrial fibrillation and cardio-oncology, highlighting biases in the literature, exploring effects of mutation and clone size, concluding with clinical implications.
Wearable devices enable electrocardiograms (ECGs) outside traditional healthcare settings. While these devices are usually equipped with single-lead ECGs to monitor rhythm abnormalities, recent studies show utility in detecting myocardial diseases when combined with artificial intelligence (AI). However, the optimal single-lead axis for detecting myocardial diseases beyond rhythm abnormality remains unclear. To address this knowledge gap, we trained models to detect 3 myocardial diseases: left ventricular systolic dysfunction (LVSD), hypertrophic cardiomyopathy (HCM), and cardiac amyloidosis (CA) using single-lead ECGs, systematically synthesized at 10-degree intervals, leveraging the limb leads from 12-lead ECG data. For all 3 diseases, the highest discriminations were observed near the aVR axis and its inverse. The optimal angles were 20° for LVSD (AUROC 0.884 [95% CI: 0.877-0.891]) and HCM (0.911 [0.900-0.922]), and 210° for CA (0.893 [0.888-0.899]). These findings may inform the development of wearable ECG devices with utility beyond rhythm abnormality detection.
Abstract We aim to estimate and compare the cost-effectiveness of statins, berberine, and their combined use for primary cardiovascular disease (CVD) prevention. The Scottish CVD Policy Model was used to predict long-term health and cost outcomes in Scottish adults aged 40 years or older without pre-existing CVD. Intervention and cost inputs were sourced from published literature and health service cost data. The primary outcome measure was the lifetime incremental cost-effectiveness ratio (ICER), evaluated as cost per quality-adjusted life year (QALY) gained. Five strategies were analyzed for individuals with ASSIGN risk scores ≥20% and ≥10%: no intervention, atorvastatin 20 mg/day, berberine 1000 mg/day, simvastatin 20 mg plus berberine 1500 mg/day, and simvastatin 20 mg plus berberine 900 mg/day. All intervention strategies were cost-effective, compared to no intervention, at the threshold of ICER of £20,000 per QALY. Compared to statins, berberine was less cost-effective, but the combined interventions remained cost-effective. Notably, when using drug costs from China (reflecting lower berberine prices), berberine and the combined interventions were preferable to statins alone. Statins, berberine, and combined interventions are all cost-effective options for primary CVD prevention. Berberine could be considered a valuable alternative or complementary therapy, particularly if its price decreases below that of statins.
