International Journal of Cardiology

PurposeObstructive sleep apnea (OSA) is a common comorbidity in heart failure (HF) patients with prevalence increasing as HF severity worsens. While CPAP/BiPAP has been shown to reduce disease burden and mortality in the general HF population, it is unclear whether these benefits extend to patients with left ventricular assist devices (LVADs). We sought to determine whether OSA affects long-term survival in newly implanted LVAD patients and whether CPAP/BiPAP treatment confers mortality benefits. MethodsThis single-center retrospective study included patients who underwent LVAD implantation between January 2007 and February 2022. Recipients were stratified by OSA status (OSA vs No-OSA), and those with OSA were further categorized based on CPAP/BiPAP compliance. Comparative statistics and Kaplan-Meier survival analyses were performed, with log-rank tests used to compare groups and assess survival differences. A Cox proportional hazards model was conducted to evaluate the association between risk factors and survival among patients with OSA and No-OSA. ResultsBefore LVAD implantation, patients with OSA had higher body mass index, hypertension, and a higher rate of implantable cardioverter-defibrillator placement than those without OSA. OSA was not associated with increased postoperative complications. Although survival did not differ significantly between OSA and No-OSA patients (p=0.33), CPAP/BiPAP-compliant OSA patients had significantly better survival than noncompliant patients (p=0.0099). ConclusionsLVAD patients with OSA who consistently use CPAP/BiPAP have better survival than those who do not. CPAP/BiPAP is a simple, low-risk treatment that can reduce mortality in this population. Therefore, increased perioperative screening for OSA should be considered for patients receiving LVADs. Multicenter studies are needed to confirm our findings further.

Abstract Aims: While traditional anthropometric indices are established cardiovascular predictors, their prognostic value for incident infective endocarditis (IE) remains undefined. Methods: We included 386,859 participants (mean age 57.0 years; 52.9% female) from the UK Biobank between 2006 and 2010 with standardized baseline data on BMI, waist circumference (WC), waist-to-height ratio (WhtR), and the triglyceride-glucose (TyG) index.Multivariable Cox proportional hazard models with restricted cubic splines were used to estimate the hazard ratio (HR) of these indices, adjusting for demographic and clinical risk factors. Results: Over 16.87 median years (25th, 16.02; 75th, 17.60 percentile) of follow-up, there were a total of 1,124 incident IE events. During the follow-up period, 38,342 total deaths were recorded, of which 8,524 were cardiovascular disease (CVD)-related.Overall, compared to individuals with normal weight and baseline metabolic indices, those in the fourth quartile of WC, WHtR, and TyG index exhibited the highest risk of incident IE. Compared to other metabolic indices, WC (HR = 1.53, 95% CI 1.23?1.90,P < 0.001) and WHtR (HR = 1.46, 95% CI 1.20?1.78,P < 0.001) demonstrated higher relative increases in risk associated with IE. Furthermore, the risk of IE was significantly elevated among the younger population with abdominal obesity and concomitant diabetes. However, no significant increase in IE risk was observed among participants with pre-existing valvular heart disease (P = 0.796). Conclusion: Compared with BMI, higher WC and WHtR were robustly associated with increased risk of IE, even after adjusting for traditional risk factors. Furthermore, the risk of IE was markedly elevated among younger individuals with abdominal obesity and diabetes.

Introduction: Spontaneous coronary artery dissection (SCAD) is frequently accompanied by persistent symptoms of unknown pathogenesis after the index event. Autonomic dysfunction is a plausible mechanism for these but has not been systematically characterized. We quantified antecedent and contemporary autonomic symptoms in survivors of SCAD and examined their associations with cardiac and extra-cardiac symptoms and health-related quality of life. Methods: This cross-sectional study recruited 227 volunteers from multiple countries with a self-reported history of SCAD. Participants completed validated patient-reported measures, including the Composite Autonomic Symptom Score-31 (COMPASS-31), Anxiety Sensitivity Index-3 (ASI-3), and EuroQol-5 Dimension-5L (EQ-5D-5L). They also completed an internally derived retrospective autonomic predisposition score assessing symptoms during adolescence and early adulthood. Results: Participants were predominantly female (97.8%), median age 53 (47-58) years, and were surveyed a median of 3 (1-5) years after their index SCAD event. 21.6% reported SCAD recurrence. Moderate autonomic symptom burden (COMPASS-31 20) was present in 56.4% and severe burden (40) in 16.3%. History of antecedent autonomic symptoms was the strongest independent predictor of contemporary autonomic symptom burden after adjustment for demographic and clinical covariates (=0.514; P <0.001). Greater autonomic symptom burden independently predicted lower EQ-5D health utility (=0.150; P=0.029) and was associated with the ASI-3 physical concerns (=0.232; P <0.001), but not social concerns domain. Autonomic symptoms were not associated with SCAD recurrence. Conclusion: Symptoms of autonomic dysregulation are common in survivors of SCAD and are associated with reduced quality of life. Their association with antecedent dysautonomic features during adolescence and early adulthood suggests a longstanding predisposition, the significance of which warrants further evaluation.

Background: Progression of transthyretin (TTR) amyloid cardiomyopathy (ATTR-CM) can lead to worsening congestion requiring diuretic intensification (DI), heart failure (HF)-related hospitalizations (HFH), and death. Tafamidis was the only approved ATTR-CM therapy in the US from 2019 until the 2024 approval of acoramidis, which achieves near-complete ([&ge;]90%) TTR stabilization. As head-to-head trials are lacking, real-world comparative effectiveness (CE) data are needed to guide treatment selection. Objective: To evaluate real-world CE of acoramidis versus tafamidis in newly treated patients with ATTR-CM. Methods: Retrospective study using Komodo Healthcare Map (R) US claims data tokenized to Claritas. Patients newly initiating acoramidis or tafamidis between 12/11/2024 and 04/30/2025 with [&ge;]1 prescription claim (first defined as index date) and [&ge;]6 months of continuous enrollment preindex date were included and followed until disenrollment, death, treatment switch, or study end date (07/31/2025). Outcomes included DI (initiation or dose-equivalent escalation of oral loop diuretics, parenteral loop diuretic use, or addition of thiazide-like diuretic) and a composite of DI, HFH (inpatient admission with a HF-related ICD-10-CM diagnosis code in any position), and mortality. Propensity score weighting balanced baseline characteristics, disease severity, comorbidity burden, and baseline medication use. Time-to-event outcomes were assessed using weighted Cox proportional hazards models. Results: After weighting, acoramidis (n=170) and tafamidis (weighted sample size=448) patients were comparable at baseline (mean age, 78.6 vs 78.7 years; male, 80.0% vs 80.2%) with mean follow-up of 139 and 143 days, respectively. DI cumulative incidence curves separated early and remained divergent, with acoramidis significantly reducing the hazard of DI events by 43% compared with tafamidis (11.8% vs 20.5%; HR, 0.57; 95% CI, 0.35-0.92; P=0.021). Acoramidis also had a significantly lower risk of composite events, with a 34% reduction in hazard compared with tafamidis (17.6% vs 26.4%; HR, 0.66; 95% CI, 0.44-0.99; P=0.046). Conclusions: In this first real-world CE study of newly treated patients, acoramidis had significantly lower risk of DI events and composite events of DI, HFH, and mortality than tafamidis, potentially supporting improved clinical stability with acoramidis initiation. Additional evaluation with longer follow-up, larger cohorts, and/or prospective clinical outcomes is warranted.

Introduction: Accurate stratification of hard atherosclerotic cardiovascular disease (ASCVD) risk remains challenging despite advances in prevention. Liver function biomarkers (LFBs), particularly gamma - glutamyl transferase (GGT), have been linked to cardiovascular outcomes, yet their contribution to hard ASCVD risk prediction is not well defined. Methods: This study analyzed data from the National Health and Nutrition Examination Survey (NHANES, 2005 - 2018) to assess cross - sectional associations between LFBs and 10 - year hard ASCVD risk estimated by the ACC/AHA Pooled Cohort Equations. Multivariable regression, restricted cubic splines, and mediation analyses were applied to examine independent and dose - response relationships. External validation was performed in the China Health and Retirement Longitudinal Study (CHARLS) and NHANES using machine learning models (CoxBoost, Naive Bayes and Random Forest). Results: Among 5,731 NHANES participants, GGT showed an independent linear association with hard ASCVD risk (P - trend = 0.003), partly mediated by systolic blood pressure (44.8%), HbA1c (19.0%), and high density lipoprotein cholesterol (13.4%). Machine learning (ML) models incorporating GGT, alkaline phosphatase (ALP), and globulin alongside traditional risk factors improved predictive accuracy, with Naive Bayes achieving an AUC of 0.751 in NHANES validation. Conclusions: GGT is an independent and biologically plausible biomarker of hard ASCVD risk, acting through cardiometabolic pathways. Incorporating LFBs into risk prediction models, particularly with machine learning, enhances risk stratification and may facilitate early identification of high - risk individuals.

Background. Patients with heart failure and reduced ejection fraction (HFrEF) commonly show signs of systemic inflammation. Interleukin-1 (IL-1) is a pro-inflammatory cytokine, known to modulate cardiac function. We aimed to determine the effects of treatment with anakinra, recombinant IL-1 receptor antagonist (IL-1Ra), on plasma IL-1Ra levels. Methods. We measured IL-1Ra levels at baseline and longest available follow-up to 24 weeks in 63 patients (44 males, 40 self-identified Black-Americans) with recent hospitalization for HFrEF, and systemic inflammation (C reactive protein [CRP] levels >2 mg/L) who were assigned to anakinra (N=42 [66.7%]) or placebo (N=21 [33.3%]) as part of the REDHART2 clinical trial (NCT0014686). Cardiorespiratory fitness was measured as peak oxygen consumption (peak VO2). Results. Baseline plasma IL-1Ra levels were 380 pg/ml (290 to 1046). On-treatment IL-1Ra levels were significantly higher in the patients treated with anakinra vs placebo (3,994 pg/ml [3,372 to 5,000] vs 492 pg/ml [304 to 1370], P<0.001). The longest available follow-up was 6 weeks in 10 patients (15.9%), 12 weeks in 12 patients (19%) and 24 weeks in 41 patients (65.1%). On-treatment IL-1Ra levels and interval change in IL-1Ra showed a modest inverse correlation with on-treatment CRP levels (R=-0.269, P=0.033 and R=-0.355, P=0.004, respectively) and no statistically significant correlations with peak VO2 values (P>0.05). Conclusions. Patients with recently decompensated HFrEF and systemic inflammation treated with recombinant IL-1Ra, anakinra, have a significant several-fold increase in plasma IL-1Ra levels. On-treatment IL-1Ra levels however show only a modest correlation with CRP levels and not with peak VO2.

Backgound: Accurate assessment of diastolic function and left ventricular (LV) filling pressure is central to heart failure diagnosis and risk stratification. Contemporary guideline algorithms rely on complex parameters that are not consistently available in routine clinical practice. Objective: To compare the diagnostic and prognostic performance of the 2016 American Society of Echocardiography/European Association of Cardiovascular Imaging (ASE/EACVI) and 2025 ASE guidelines with a deep learning model based on routinely acquired echocardiographic variables. Methods: This study evaluated the guideline-based algorithms and a deep learning model in participants from the Atherosclerosis Risk in Communities (ARIC) cohort (n=5450) for prognostication and two invasive hemodynamic validation cohorts from the United States (n=83) and Japan (n=130) for detection of elevated left ventricular filling pressure. Results: In the ARIC cohort, the deep learning model demonstrated superior prognostic performance compared with the 2016 and 2025 guidelines (C-index: 0.676 vs. 0.638 and 0.602, respectively; both p<0.001). Similar findings were observed among participants with preserved ejection fraction (C-index: 0.660 vs. 0.628 and 0.590; both p<0.001), with improved performance compared with the H2FPEF score (C-index: 0.660 vs. 0.607; p<0.001). In the US hemodynamic validation cohort, the deep learning model showed higher diagnostic performance than the 2025 guidelines (AUC: 0.879 vs. 0.822; p=0.041) and similar performance compared with the 2016 guidelines (AUC: 0.879 vs. 0.812; p=0.138). In the Japanese hemodynamic validation cohort, the deep learning model outperformed both guidelines (AUC: 0.816 vs. 0.634 and 0.694; both p<0.05). Conclusions: A deep learning model leveraging routinely available echocardiographic parameters demonstrated improved diagnostic and prognostic performance compared with contemporary guideline-based approaches, potentially offering a scalable alternative for assessing diastolic function and left ventricular filling pressures.

Sex specific differences in stroke are recognized. Whether differences in incident stroke risk persists in recent periods needs further elucidation to aid public health preventive efforts. Aim: To determine long-term sex specific trends in stroke and stroke risk factors at different epochs among Framingham Heart Study participants. Methods: We examined age-adjusted 10-year stroke incidence using Cox regression in women and men in five epochs: 1962-1969 (epoch 1, reference), 1971-1976 (epoch 2), 1987-1991 (epoch 3), 1998-2005 (epoch 4), 2015-2021 (epoch 5). We compared stroke incidence by sex across epochs, estimated decade-wise linear trends overall and by sex. We compared risk factors in successive epochs to the first, and estimated sex-specific trends in risk factors. Interactions between baseline risk factors with epoch and trends were assessed by sex. Secondary analyses were repeated in participants <60 years old. Results: Incident stroke occurred in 4.5% (178/3996) in epoch 1, 3.9% (227/5786) in epoch 2, 3.9% (199/5137) in epoch 3, 2.7% (207/7642) in epoch 4, 2.2% (119/5534) in epoch 5. Men had higher risk of incident stroke in each epoch with significant difference in epochs 2 (HR 1.41, 95% CI [1.08, 1.84]) and 4 (HR 1.46, 95% CI [1.11, 1.91]) overall, and in epoch 4 (HR 2.13, 95% CI [1.17, 3.87]) among those <60 years. Stroke incidence declined by 16% per decade in men (HR 0.84, 95% CI [0.79, 0.89]) and 19% per decade in women (HR 0.81, 95% CI [0.76, 0.86]). Among those <60 years, stroke incidence declined by 22% per decade in women (HR 0.78, 95% CI [0.67, 0.95]). Hypertension declined by 8% per decade in women only ([OR] 0.92, 95% CI [0.90, 0.94]), while Atrial fibrillation and diabetes increased in both. Conclusion: Stroke incidence continues to decline in recent periods for women and men. Among participants <60 years, decline was observed only in women, possibly related to decline in hypertension in women.

Introduction: Smoking cessation after acute coronary syndrome (ACS) is a Class I recommendation, yet prescription pharmacotherapy use remains low and its real-world cardiovascular effectiveness when added to nicotine replacement therapy (NRT) is poorly characterized. Methods: We conducted a retrospective cohort study using the TriNetX US Collaborative Network (67 healthcare organizations). Adults hospitalized with ACS who received NRT within one month, serving as a proxy for active smoking status, were identified. Two co-primary propensity-matched (1:1, 50 covariates, caliper 0.10 SD) comparisons evaluated bupropion + NRT and varenicline + NRT individually versus NRT alone; a supportive analysis evaluated combined pharmacotherapy versus NRT alone. All-cause mortality was the primary endpoint. Secondary outcomes included MACE, heart failure exacerbations, major bleeding, TIA/stroke, emergency rehospitalizations, and cardiac rehabilitation utilization, assessed at 6 months and 1 year via Kaplan-Meier analysis. Hazard ratios (HRs) greater than 1.0 indicate higher hazard in the NRT-only group. Results: After matching, the combined analysis comprised 8,574 pairs, the bupropion analysis 4,654 pairs, and the varenicline analysis 2,126 pairs. At 1 year, the combined pharmacotherapy group had significantly lower all-cause mortality (HR 1.26, 95% CI 1.16-1.37), MACE (HR 1.16, 95% CI 1.12-1.21), heart failure exacerbations (HR 1.16, 95% CI 1.08-1.25), major bleeding (HR 1.18, 95% CI 1.08-1.28), and greater cardiac rehabilitation utilization (HR 0.82, 95% CI 0.74-0.92; all p < 0.001). TIA/stroke did not differ significantly. Six-month results were consistent. Both varenicline and bupropion individually showed lower mortality and MACE. A urinary tract infection falsification endpoint showed no between-group differences, supporting matching validity. The pharmacotherapy group had higher rates of new-onset depression, driven predominantly by bupropion recipients. Conclusions: In this propensity-matched real-world analysis, adding prescription smoking cessation pharmacotherapy to NRT after ACS was associated with lower mortality and fewer adverse cardiovascular events, supporting broader integration into post-ACS care pathways.

Aims: Assessment of treatment response in HFrEF has largely relied on left ventricular (LV)-centric parameters, yet the left atrium (LA) plays a central role in modulating LV filling and reflects the cumulative hemodynamic burden. Whether discordant recovery between LV and LA function carries distinct prognostic implications in patients treated with ARNI-based therapy remains unknown. Methods and results: From the multicenter STRATS-HF-ARNI registry, 1,182 patients with HFrEF who underwent serial echocardiography at baseline and one-year follow-up were included. Patients were classified into four strain recovery phenotypes according to the direction of change in LVGLS and LASr at one year: Group A, concordant recovery (57.4%); Group B, discordant atrial non-recovery (11.2%); Group C, discordant ventricular non-recovery (15.6%); and Group D, concordant non-recovery (16.0%). Clinical outcomes included all-cause mortality, cardiovascular mortality, and HF hospitalization. Despite achieving LV functional improvement, Group B exhibited persistent LASr deterioration, accompanied by less favorable hemodynamic trajectories compared with Group A. On multivariable Cox regression, Group B was associated with significantly higher risks of all-cause mortality (adjusted hazard ratio [aHR] 3.53, 95% confidence interval [CI] 1.60-7.79) and cardiovascular mortality (aHR 5.68, 95% CI 1.91-16.92), comparable to Group D. Group C demonstrated higher HF hospitalization risk (aHR 2.25, 95% CI 1.31-3.86). The adverse prognostic impact of discordant atrial non-recovery was consistently observed across subgroups stratified by baseline LVGLS and LASr levels. Conclusion: In HFrEF patients treated with ARNI-based therapy, persistent LA dysfunction despite LV functional improvement identifies a high-risk phenotype comparable to concordant non-recovery. These findings suggest that concurrent assessment of LV and LA strain may provide incremental prognostic value beyond LV-centric metrics alone.

Background: We aimed to identify data-driven FEV1 trajectory phenotypes post-chronic lung allograft dysfunction (CLAD), relate these phenotypes to patient factors and future graft loss, and develop a classification approach for prospective patients. Methods: We studied adult first lung recipients with probable CLAD from two prospective multicenter cohorts: CTOT-20 (n=206) and LTOG (n=1418). FEV1 trajectories over the first nine months post-CLAD were characterized using joint latent class mixed models, jointly modelling time-to-graft loss to account for informative censoring. Models were fit independently in both cohorts and also only among LTOG bilateral recipients. A classification and regression tree (CART) model was derived in LTOG bilateral recipients and applied to CTOT-20 bilateral recipients. Findings: Four distinct early FEV1 trajectory classes were identified in CTOT-20, with large differences in nine month graft loss (72.3%, 31.1%, 2.2%, 0%). In LTOG, similar trajectory patterns were reproduced, with an additional class demonstrating early post-CLAD FEV1 improvement. Among bilateral recipients, trajectory classes showed a clear risk gradient, including a high-risk class with 100% graft loss and a low-risk class with no early graft loss. A CART model incorporating clinical and spirometric variables demonstrated good discrimination in LTOG bilateral recipients (multiclass AUC 0.85) and consistent class assignment and trajectory patterns when applied to CTOT-20. Interpretation: We identified reproducible, clinically meaningful early post-CLAD FEV1 trajectory phenotypes with differential graft loss risk. These phenotypes and a pragmatic classification tool may support risk stratification, trial enrichment, and improved prognostication for patients and clinicians.

Background: Increased epicardial adipose tissue volume (EATV) is a potentially important risk marker for coronary artery disease (CAD) available from cardiac computed tomography (CT) images. Sex-differences and effects of age and body size on EATV have been insufficiently explored, and no reliable reference values exist. Consequently, EATV has yet to find its deserved use in clinical practice. Objectives: To define normal values by sex and age, the best normalization procedure for EATV to neutralize effects of body-size, explore the relationship between normalized EATV and cardiac risk, and propose a clinically meaningful cut-off. Methods: AI-based automated EATV data from the general population (n=25,155) and a clinical cohort (n=2,482) with suspected CAD was normalized to height, BSA and heart volumes. Correlation between EATV and EAT attenuation was tested with Spearman?s rank correlation and linear regression to find the optimal normalization. Normalized EATV was compared to high-risk by SCORE2 and obstructive CAD in the population cohort. A cut-off including 95% of cases with obstructive CAD was defined in the general population and tested in the clinical cohort. Results: EATV varied with sex and age across cohorts. Normalization of EATV to total heart volume (EATVh) was superior by all metrics and neutralized the effects of sex. High-risk by SCORE2 and the prevalence of obstructive CAD increased over quartiles of EATVh in the population cohort, and significantly higher EATVh was seen with obstructive CAD in both cohorts. A cut-off of 0.1 in EATVh had a negative predictive value for obstructive CAD of 97.1% in the general population and 88.9% in the clinical cohort. Conclusions: EATV varies considerably with sex, age and body size. Normalization to heart volume outperformed other procedures, and EATVh is a useful marker of obstructive CAD in both the general population and symptomatic patients.

BACKGROUND Point-of-care (POC) high-sensitivity cardiac troponin (hs-cTn) testing has the potential to expedite decision-making and reduce emergency department (ED) length of stay for patients presenting with possible myocardial infarction (MI) by ensuring that results are consistently available when looked for by clinicians. We assessed the real-life effectiveness and safety of implementing POC hs-cTn testing in the ED. METHODS We conducted a pragmatic, stepped-wedge cluster randomized trial. The control arm was usual care with an accelerated diagnostic pathway utilizing a single-sample rule-out step with a central laboratory hs-cTn assay. The intervention arm used the same pathway with a POC hs-cTnI. The primary effectiveness outcome was ED length of stay assessed using a generalized linear mixed model, and the safety outcome was 30-day MI or cardiac death. RESULTS Six sites participated with 59,980 ED presentations (44,747 individuals, 61{+/-}19 years, 49.5% female) from February 2023 to January 2025, in which 31,392 presentations were during the intervention arm. After adjustment for co-variates associated with length of stay, the intervention reduced length of stay by 13% (95% confidence intervals [CI], 9 to 16%. P<0.001), corresponding to a reduction of 47 minutes (95%CI, 33 to 61 minutes) from a mean length of stay in the control arm of 376 minutes. The 30-day MI or cardiac death rate was similar in the control and intervention arms (0.39% and 0.39% respectively, P=0.54). CONCLUSIONS Implementation of whole-blood hs-cTnI testing at the POC into an accelerated diagnostic pathway was safe and reduced length of stay in the ED compared with laboratory testing.

Background: Chronic conditions such as hypertension can significantly disrupt daily life and emotional wellbeing. The interaction between patients' perceptions, adherence to antihypertensive medication and quality of life (QoL) remains underexplored outside structured clinical settings. Objectives: To capture unprompted patient perspectives and assess whether hypertension affects QoL and to investigate if patient reported experiences are associated with self-reported antihypertensive medication adherence. Methods: Social media listening (SML) study analyzing 86,368 anonymized posts from individuals with hypertension in 12 countries, collected between January 2022 and May 2024. Posts from 11 countries (n=81,368) were analyzed using artificial intelligence-enabled natural language processing. Posts from China (n=5,000) were analyzed separately using a harmonized framework. Quantitative and qualitative methods assessed variations by country, age, and gender, and associations between emotional expression and antihypertensive medication adherence. Results: Across the 11-country core sample, 45% of posts mentioned at least one QoL impact, most commonly worry/anxiety (11%). Impacts varied across countries. Among 8,096 posts with age identified, individuals <40 years reported emotional balance impacts in 28% of posts versus 22% among those aged 40+. Work/Education impacts were mentioned in 17% of posts by those <40 years vs 12% in 40+. Among 7968 posts explicitly referencing adherence, expressed worry was associated with stricter adherence (62% association score), as were structured routines (79% score), home monitoring (77%), dietary changes (77%), and exercise (71%). In contrast, sadness/depression was associated with inconsistent adherence (71%), as were forgetfulness (79%), side effects (73%), and cost/insurance concerns (65%). Conclusions: These results emphasize the importance of the psychological and emotional impact of hypertension, including on adherence to medication regimens, reinforcing the value of a holistic approach to patient care.

Coronary artery disease is a leading cause of morbidity and mortality. Invasive coronary angiography is currently the gold standard in disease diagnosis. Several studies have attempted to use artificial intelligence (AI) to automate their interpretations with varying levels of success. However, most existing studies cannot generate detailed angiographic reports beyond simple classification or segmentation. This study aims to fine-tune and evaluate the performance of a Vision-Language Model (VLM) in coronary angiogram interpretation and report generation. Using twenty-thousand angiogram keyframes of 1987 patients collated across four unique datasets, we finetuned InternVL2-4B model with Low-Rank Adaptor weights that can perform stenosis detection, anatomy labelling, and report generation. The fine-tuned VLM achieved a precision of 0.56, recall of 0.64, and F1-score of 0.60 for stenosis detection. In anatomy segmentation, it attained a weighted precision of 0.50, recall of 0.43, and F1-score of 0.46, with higher scores in major vessel segments. Report generation integrating multiple angiographic projection views yielded an accuracy of 0.42, negative predictive value of 0.58 and specificity of 0.52. This study demonstrates the potential of using VLM to streamline angiogram interpretation to rapidly provide actionable information to guide management, support care in resource-limited settings, and audit the appropriateness of coronary interventions. AUTHOR SUMMARYCoronary artery disease has heavy disease burden worldwide and coronary angiogram is the gold standard imaging for its diagnosis. Interpreting these complex images and producing clinical reports require significant expertise and time. In this study, we fine-tuned and investigated an open-source VLM, InternVL2-4B, to interpret and report coronary angiogram images in key tasks including stenosis detection, anatomy identification, as well as full report generation. We also referenced the fine-tuned InternVL2-4B against state-of-the-art segmentation model, YOLOv8x, which was evaluated on the same test sets. We examined how machine learning metrics like the intersection over union score may not fully capture the clinical accuracy of model predictions and discussed the limitations of relying solely on these metrics for evaluating clinical AI systems. Although the model has not yet achieved expert-level interpretation, our results demonstrate the potential and feasibility of automating the reporting of coronary angiograms. Such systems could potentially assist cardiologists by improving reporting efficiency, highlightning lesions that may require review, and enabling automated calculations of clinical scores such as the SYNTAX score.

BackgroundHypertension is the leading modifiable risk factor for ischemic stroke, yet the adequacy of preventative hypertension care in routine clinical practice remains suboptimal. Whether gaps in hypertension management represent missed opportunities for stroke prevention remains unclear. ObjectiveTo evaluate the association between hypertension care delivery and the risk of incident ischemic stroke. MethodsWe conducted a retrospective, matched, nested case-control study among adults with hypertension using electronic health record data from a large regional health system (2010-2024). Patients with a first-ever ischemic stroke were matched 1:2 to controls on age, sex, race and ethnicity, and calendar time. Three care metrics were assessed during follow-up: (1) outpatient visits with blood pressure (BP) measurement per year; (2) number of antihypertensive medication ingredients; and (3) medication intensification score. Conditional logistic regression estimated adjusted odds ratios (aORs). ResultsThe study included 13,476 cases and 26,952 matched controls (N = 40,428). Mean (SD) age was 64.8 (12.2) years, 54.1% were female, and mean follow-up was 2,497 (1,308) days. Cases had fewer BP visits per year (median, 2.50 vs. 3.01; p < 0.001), similar number of medication ingredients (2.00 vs 2.00), and lower treatment intensification scores (-0.211 vs - 0.125). In adjusted models, >5 BP visits per year was associated with lower stroke odds (aOR, 0.55; 95% CI, 0.51-0.59) compared with [&le;]1 visit. Use of 2-3 medication ingredients (vs 0) was also associated with reduced stroke odds (aOR, 0.80; 95% CI, 0.75-0.86), whereas >3 ingredients was not significant. The highest quartile of treatment intensification showed the strongest association (aOR, 0.47; 95% CI, 0.44-0.51). Findings were consistent across subgroup and sensitivity analyses, including strata defined by baseline SBP and follow-up SBP. ConclusionsGreater engagement in hypertension care was associated with lower odds of ischemic stroke, suggesting that gaps in routine management may represent missed opportunities for prevention.

The recently published EHRA/EACVI consensus statement on a standardized bi-atrial regionalization provides new opportunities for consistent regional analyses across patients, imaging modalities and clinical centers. To make this standardized regionalization widely accessible, we developed the open-source software DIVAID, which automatically divides bi-atrial geometries according to the proposed regions, ensuring consistency, reproducibility and operator independence. We evaluated the accuracy of the algorithm by comparing its results to manual expert annotations across 140 geometries from multiple modalities and centers. Veins were automatically clipped correctly in 81% and orifices annotated correctly in 100% of cases. The median (interquartile range; IQR) Dice similarity coefficient (DSC) for left atrial regions was 0.98 (0.96-1.00) for DIVAID-expert and 0.98 (0.94-1.00) for inter-expert comparisons. For right atrial geometries, DSC was higher for DIVAID-expert than for inter-expert comparisons at 0.90 (0.80-0.95) and 0.88 (0.74-0.94), respectively. To assess the accuracy of regional boundaries, we computed the mean average surface distance (MASD) for boundaries derived from automatic or manual annotations. The median (IQR) MASD between DIVAID and experts was 0.17 mm (0.03-0.78) and 1.93 mm (0.65-3.96) in the left and right atrium, respectively. To conclude, DIVAID robustly divides anatomically diverse bi-atrial geometries according to the 15-segment model, while outperforming cardiac experts in both speed and consistency, and demonstrating an accuracy of regional boundaries comparable to the spatial resolution of cardiac imaging modalities. By providing automated, consistent atrial regionalization, DIVAID enables large-scale, standardized regional analyses and data-driven investigation of harmonized, multi-dimensional datasets, which may advance atrial arrhythmia research and personalized treatment strategies.

Abstract Background: Hypertrophic (HCM) and dilated (DCM) cardiomyopathy constitute the principal phenotypes of primary cardiomyopathy, yet both lack sufficient therapeutic options. Integrating genetic insights with detailed cardiac phenotyping offers a promising strategy to prioritize targets and elucidate their mechanisms of action. Methods: We conducted an three-stage analysis. First, drug-target Mendelian randomization (MR) was performed using cis-acting protein (pQTL) and expression (eQTL) quantitative trait loci as genetic instruments for potential drug targets. Second, we examined causal associations between 82 cardiac magnetic resonance (CMR)-derived imaging traits and HCM/DCM risk in a CMR-based MR analysis. Third, mediation MR was employed to quantify the proportion of the genetic effect of prioritized drug targets on cardiomyopathy risk that was mediated through specific CMR phenotypes. Results: Our analyses identified 19 and 13 potential therapeutic targets for HCM and DCM, respectively. CMR-based MR revealed that HCM risk was causally associated with increased right ventricular ejection fraction (RVEF) and greater left ventricular wall thickness, whereas DCM risk was linked to ventricular dilation, impaired myocardial strain, and altered aortic dimensions. Critically, mediation analysis established that these CMR traits served as significant intermediate pathways. The protective effect of ALPK3 on HCM risk was mediated through a reduction in myocardial wall thickness. Conversely, the effects of PDLIM5, HSPA4, and FBXO32 on DCM risk were exerted in part via alterations in aortic dimensions. Conclusion: This integrative genetic and imaging study systematically identify candidate therapeutic targets for HCM and DCM and delineates the specific CMR phenotypes through which they likely exert their causal effects. Our findings advance the understanding of disease pathogenesis and highlight new possibilities for improving the diagnosis and management of cardiomyopathy.

Abstract Objective: To compare the safety and efficacy of bridging intravenous thrombolysis (IVT) plus endovascular thrombectomy (EVT) versus direct EVT in patients with acute ischemic stroke (AIS) due to anterior circulation large vessel occlusion (LVO) treated within the 6- to 24-hour time window. Methods: This is a retrospective analysis of prospective EVT registry from 10 comprehensive stroke centers in China and Singapore between 2019 and 2024. Eligible patients had anterior circulation LVO, underwent EVT within 6-24 hours of onset, had ASPECTS 6, NIHSS 6, and pre-stroke mRS 2. Patients were stratified into bridging IVT + EVT (IVT group) versus direct EVT alone (non-IVT group). Propensity score matching (1:2 ratio) was performed to balance baseline covariates. The primary outcome was 3-month favorable functional outcome (mRS 0-2). Secondary outcomes included successful recanalization (mTICI 2b-3), symptomatic intracranial hemorrhage (sICH), hemorrhagic transformation (HT) and 3-month mortality. In the matched cohort, binary outcomes were compared using the Cochran-Mantel-Haenszel test. Results: Of 772 included patients, 110 (14.2%) received bridging IVT and 662 (85.8%) received direct EVT. After propensity score matching, 202 non-IVT patients were matched to 101 IVT patients, with all covariates well-balanced (absolute SMD <0.10). In the matched cohort, bridging IVT was not associated with a significant difference in 3-month favorable outcome (44.55% vs. 47.03%; common OR 0.91; 95% CI 0.56-1.46), successful recanalization (91.09% vs. 90.10%; OR 1.11; 0.51-2.44), sICH (5.94% vs. 9.41%; OR 0.61; 0.24-1.58), HT (23.76% vs. 23.27%; OR 1.03; 0.57-1.85), or 3-month mortality (15.84% vs. 13.37%; OR 1.22; 0.62-2.37). Conclusion: In this large multicenter propensity score-matched analysis, bridging intravenous thrombolysis before endovascular thrombectomy in the 6- to 24-hour time window was not significantly associated with improved efficacy or increased safety risks compared with direct endovascular therapy alone.

Conflicting evidence on scatter correction (SC) methods plagues quantitative myocardial perfusion SPECT (MPI), hindering standardized clinical protocols. This simulation study, utilizing the SIMIND Monte Carlo program and a highly realistic 4D XCAT phantom, systematically evaluates Dual Energy Window (DEW, with k=0.5) and Triple Energy Window (TEW) SC techniques. We uniquely investigate their performance across various photopeak window widths (2, 4, and 6 keV) and novel overlapped/non overlapped configurations specifically for Tc 99m MPI parameters largely unexplored in realistic cardiac models. Images were reconstructed with OSEM under uncorrected (UC), SC, and combined attenuation and scatter corrected (ACSC) conditions. Quantitative analysis focused on signal to noise ratio (SNR), contrast to noise ratio (CNR), defect contrast, and relative noise to background (RNB). Our findings consistently show ACSC's superior performance in CNR, SNR, and defect contrast, confirming its critical role. Interestingly, SC alone reduced noise but compromised defect contrast relative to UC, highlighting a potential trade-off without attenuation correction. Crucially, this study reveals minimal influence of photopeak window width and overlap configuration on image quality, and no significant difference between DEW and TEW across most metrics. These results provide essential evidence for optimizing quantitative MPI protocols, suggesting that for Tc 99m, the choice between DEW and TEW, and specific window settings, may be less critical than ensuring robust attenuation correction.