Citations

Coronary microvascular dysfunction (CMD) has emerged as a crucial contributor to cardiovascular morbidity and mortality, particularly in patients with ischemia and non-obstructive coronary arteries (INOCA). The condition arises from a complex interplay of structural and functional abnormalities within the small coronary vessels, driven by underlying molecular mechanisms including endothelial nitric oxide synthase (eNOS) uncoupling, oxidative stress, and chronic inflammation. Lipid metabolism plays a central role in this pathology, especially in the setting of elevated low-density lipoprotein cholesterol (LDL-C). Furthermore, the protective capacity of high-density lipoprotein (HDL) is increasingly understood to depend on its functionality rather than absolute levels, as it can become dysfunctional and pro-inflammatory in pathological states. Emerging evidence has identified lipoprotein(a) [Lp(a)] and triglyceride-rich lipoproteins as significant, independent contributors to microvascular injury. Comprehensive clinical assessment of microvascular dysfunction therefore requires integration of advanced lipid profiling, including apolipoprotein B (ApoB), [Lp(a)], and the triglyceride-glucose (TyG) index with invasive and non-invasive measures of coronary flow reserve to more precisely stratify risk. In this narrative review, we synthesize current observational, mechanistic, and early interventional data linking diverse lipid phenotypes to coronary microvascular dysfunction. We propose a concept of lipid-driven CMD endotypes, such as ApoB-/particle overload, dysfunctional HDL, Lp(a)-mediated risk, and metabolic/TyG-high states, and map these to a practical, mechanism-informed management framework. While intensive LDL-C lowering with high-intensity statins and combination therapy remains guideline-directed care for high-risk patients, evidence for dedicated microvascular benefit from newer lipid and cardiometabolic agents is still largely hypothesis-generating. A personalized approach that aligns lipid phenotyping, CMD endotyping, and existing guideline-based therapies may help refine risk assessment and inform future trials.

Abstract Background Accurate assessment of left ventricular outflow tract (LVOT) gradients is critical for hypertrophic cardiomyopathy (HCM) management, yet Doppler-based measurements are technically demanding and require expertise. Objective To develop a multi-view deep learning model capable of classifying LVOT obstruction (> 20mmHg) using routine 2D echocardiographic windows without reliance on Doppler imaging. Methods We trained and externally validated a cross-attention-based video-to-video fusion framework that integrated EchoPrime-derived video representations from three standard transthoracic echocardiographic views to classify LVOT gradients. Results Training was performed on a derivation cohort (N = 1833) from a tertiary care system in the United States, with model performance evaluated on an internal held-out test set (N = 275) and a Korean external validation cohort (N = 46). Single-view baselines showed limited discrimination (external AUROCs 0.47–0.70). Conversely, domain-specific foundational model (EchoPrime) achieved superior single-view performance (AUROCs 0.75–0.80 internal; 0.79–0.83 external), highlighting the importance of echo-specific pretraining and temporal modeling. The proposed multi-view fusion further enhanced predictive performance, with the late fusion model reaching an AUROC of 0.84 on the external cohort with significant population-shift. Conclusions These results suggest LVOT physiology is encoded in routine 2D imaging and can be leveraged for clinically relevant gradient classification without Doppler input- proposed AI-guided strategy demonstrates substantial cost savings compared with the screen-all approach. By integrating complementary spatial-temporal information across multiple views, our approach generalizes robustly across populations and may enable real-time decision support, extend LVOT assessment to portable or resource-limited settings, and complement Doppler-based evaluation for longitudinal HCM management.

Background In low-gradient severe aortic stenosis (AS), reduced left ventricular ejection fraction (LVEF <50%) is practically used to define low flow and prompt dobutamine stress echocardiography to discern pseudo-severe AS. In patients with preserved LVEF, stroke volume index (SVI) <35 mL/m² is typically used. However, both are volume-based surrogates. Transaortic flow rate (TAFR), calculated as stroke volume divided by left ventricular ejection time, may better reflect true flow. Nonetheless, comparative data between TAFR and established metrics remain limited. We aimed to evaluate the prognostic value of TAFR in symptomatic low-gradient severe AS. Methods We retrospectively identified patients with low-gradient severe AS (AVA ≤1 cm 2 and peak velocity (Vmax) <4 m/s or mean gradient (MG) <40 mm Hg) who underwent transcatheter aortic valve replacement at Mayo Clinic sites (2017–2023). The primary outcome was 1-year all-cause mortality. Survival was assessed using Kaplan-Meier and Cox proportional hazards models. Results Among 475 patients included (mean age 85±8 years; 49% women), 242 (51%) had TAFR <220 mL/s, 165 (35%) had EF <50%, and 221 (47%) had SVI <35 mL/m 2 . Low TAFR was significantly associated with higher 1-year mortality even after stratifying by EF or SVI. In multivariate analysis, TAFR was an independent predictor of mortality (HR 2.38; 95% CI 1.19 to 4.76, p=0.014) after adjusting for reduced LVEF, low SVI, gender, chronic kidney disease and mitral and tricuspid regurgitation. Conclusions In patients with symptomatic low-gradient severe AS, low TAFR, not SVI or LVEF, is independently associated with mortality and may offer more accurate measure of flow state for clinical staging.

ABSTRACT Electrocardiography (ECG) is a critical diagnostic tool for identifying cardiac conditions. While standard lead positions are widely used to ensure diagnostic accuracy, alternative lead placements have been developed to address specific clinical scenarios. These alternative configurations can overcome physical or technical challenges, enhance rhythm assessment, improve signal quality, and provide greater specificity for certain conditions, ultimately enabling more personalized diagnostic strategies. This paper examines the clinical significance of alternative ECG lead positions, highlighting their advantages, limitations, and potential applications in various clinical settings.

Abstract Aims Obesity is linked with worse outcomes in hypertrophic cardiomyopathy (HCM). While both bariatric surgery (BS) and GLP-1 receptor agonists (GLP-1RA) promote weight loss and may improve cardiometabolic risk, their comparative outcomes in HCM remain unclear. Methods and results Adults with HCM and body mass index (BMI) ≥ 30 kg/m were divided into two cohorts: (i) GLP-1 RA users who never had BS, and (ii) BS patients who never received GLP-1 RA. Propensity score matching (1:1) was performed to balance demographics, comorbidities, and medications. Outcomes over 24 months include all-cause mortality, acute heart failure (HF) hospitalization, arrhythmias, change in BMI, and cardiovascular symptoms. Hazard ratios with 95% confidence intervals were estimated using Cox models. Of 5002 patients, 955 were included in each matched cohort after matching (mean age 54 ± 13 years, 70% female, BMI 40.0 kg/m). GLP-1 RA was associated with a significantly lower observed rate of all-cause mortality compared with BS (2.0% vs. 4.4%; HR 0.46; 95% CI 0.27–0.80; P = 0.004) and HF hospitalization (8.7% vs. 14.0%; HR 0.60; 95% CI 0.46–0.79; P &lt; 0.001). Similarly, GLP-1 RA use was associated with a lower incidence of composite cardiovascular outcomes (10.7% vs. 17.2%; HR 0.60; 95% CI 0.47–0.77; P &lt; 0.001). Rates of arrhythmia and cardiovascular symptoms were comparable between the two groups. BMI reduction was greater after bariatric surgery (−4.0 vs. −2.6 kg/m; P &lt; 0.001). Conclusion In obese patients with HCM, GLP-1 RA therapy was associated with lower all-cause mortality and fewer HF events compared with BS. Future studies are warranted to confirm our findings.

Background. Liver transplant recipients face high risks of cardiometabolic events after transplant, driven by posttransplant weight gain, diabetes, hypertension, as well as immunosuppression-related side effects. Glucagon-like peptide-1 receptor agonists (GLP1RAs) improve metabolic and cardiorenal outcomes in nontransplant populations, but their role in liver transplant recipients remains understudied. Methods. This retrospective cohort study used TriNetX data (January 2010–December 2023) to compare outcomes in liver transplant recipients prescribed GLP1RAs (semaglutide, dulaglutide, liraglutide) within 1-mo posttransplant (n = 546) versus nonusers (n = 37 153). Propensity score matching (1:1) balanced demographics, comorbidities, and medications (n = 541 per group). Outcomes included mortality, hospitalizations, cardiovascular/renal/respiratory events, and graft outcomes. Results. Over a mean follow-up 838.5 d (SD 291.9) in the GLP1RA cohort and 884.3 d (SD 313.7) in the non-GLP1RA group, GLP1RA use was associated with a 43% lower all-cause mortality (7.0% versus 12.9%; hazard ratio [HR], 0.566; 95% confidence interval [CI], 0.381-0.841) and 39% fewer hospitalizations (60.4% versus 74.5%; HR, 0.613; 95% CI, 0.530-0.710). Acute heart failure (HR, 0.386; 95% CI, 0.285-0.524), renal failure/dialysis (HR, 0.489; 95% CI, 0.413-0.579), and respiratory failure (HR, 0.484; 95% CI, 354-0.662) risks were significantly reduced. No differences were observed in graft failure/rejection, myocardial infarction, stroke, atrial fibrillation/flutter, ventricular tachycardia, or ischemic optic neuropathy. Conclusions. Early GLP1RA initiation in liver transplant recipients was associated with reduced mortality, hospitalizations, respiratory, and cardiorenal complications without compromising graft safety. These findings support GLP1RAs as a promising adjunct therapy, warranting prospective trials to confirm benefits in this high-risk population.

Foundation models, known as the large-scale, pretrained models capable of generalizing across diverse tasks, have significantly advanced the field of medical image analysis. While most early applications focused on 2D modalities, the unique challenges and opportunities associated with volumetric medical imaging have recently attracted growing interest. This study provides a comprehensive overview of the current landscape of foundation models tailored for volumetric medical image analysis, with a focus on CT, MRI, and PET imaging. We examine key components of these models, including 3D architectures, training strategies, and supported modalities. In addition, we highlight their contribution to major clinical tasks such as classification and prediction, segmentation, image registration, quality enhancement, and visual question answering. Critical challenges of these models, including high computational cost, limited and less diverse 3D datasets, and domain adaptation, are discussed alongside the promising solutions and future research directions. By synthesizing recent advances in volumetric foundation models and outlining key technical and clinical challenges, this review provides a thorough roadmap toward the development of scalable, generalizable, and clinically applicable AI systems for volumetric medical images.

BACKGROUND: Pectus deformities are common chest wall abnormalities, with surgical correction recommended for severe cases. Female patients undergoing repair may have a history of breast implants or seek concurrent augmentation. This retrospective study examines clinical implications of pectus repair in patients with breast implants and provides recommendations. STUDY DESIGN: A retrospective review of female patients undergoing pectus repair at Mayo Clinic Arizona (January 1, 2010 to February 1, 2025) was conducted. Outcomes and complications were analyzed in patients with and without breast implants. RESULTS: In total, 456 female patients were included (447 excavatum, 7 arcuatum, and 2 carinatum; median age 32.7). Most patients (78.5%) underwent primary minimally invasive repairs (MIRPE); 6.6% underwent primary hybrid MIRPE, 5.5% underwent redo MIRPE, and 9.4% underwent primary redo open and complex reconstructions. In total, 104 patients (22.8%) had a history of breast implants, with 68 patients having breast implant-related procedures at the time of pectus surgery. At 12 months, the cumulative incidence of infection was significantly higher in patients with implants present at the time of pectus repair than in those without (8.8% vs 1.8%; log rank, p = 0.0015). A 4.9-fold increase in overall infection was seen in patients with indwelling or placed implants during pectus surgery. Deep infections were significantly more common in patients with implants (4.4%) than without (1.0%; p = 0.035). Similarly, superficial infections were more frequent in patients with implants (4.4%) than without (0.8%; p = 0.016). At 30 days, patients with implants had higher rates of infection (p = 0.032), pneumothorax (p = 0.008), and hematoma (p = 0.027), with no significant differences in other complications. CONCLUSIONS: Breast implants at the time of pectus repair were associated with increased risk of postoperative infection, pneumothorax, and hematoma. Removal of implants before pectus repair is recommended with delayed replacement, if desired.

This cohort study examines the association of bruton tyrosine kinase inhibitor therapy in B-cell malignant disease with increased risk of pericardial effusion and cardiovascular outcomes.