Recently, Acurate neo2 (ACN2; Boston Scientific, US) and Sapien-3 series (Edwards Lifesciences, US) were compared in the IDE trial failing to demonstrate non-inferiority of ACN2. The Myval series (MyV), an alternative balloon-expandable device, demonstrated non-inferiority compared to Sapien-3 and Evolut (Medtronic, US) in the LANDMARK trial. However, no direct comparison exists between ACN2 and MyV.

We aimed to compare mid-term clinical and hemodynamic outcomes of the ACN2 and MyV transcatheter heart valves.

This multicenter retrospective analysis included patients implanted with ACN2 and MyV series devices. The primary objective was to assess 1-year mortality and stroke rates. Secondary outcomes included technical success, mortality, stroke, residual aortic regurgitation (AR), mean aortic gradients, and new permanent pacemaker implantation (PPI) rates up to 4 years. A matched comparison adjusting for clinical and anatomical characteristics was performed and echocardiograms were centrally analyzed.

A total of 545 patients (ACN2: 144; MyV: 401) from nine institutions were included. Matched technical success rates were 87.6% and 94.4%, p = 0.180 (90.3% for ACN2 and 97% for MyV; p < 0.001 in unmatched). In-hospital matched PPI rates were 10.1% for ACN2 and 9% for MyV. At 4 years, matched residual ≥ moderate AR rates were similar (ACN2: 15.8% vs. MyV: 21.1%, p = 0.706), though ACN2 showed better mean aortic gradients (9.2 ± 4.2 vs. 13.1 ± 5.4, p = 0.001) and effective orifice area. Unmatched mortality + stroke rates were comparable but lower for ACN2 after matching (3.4% vs. 15.7%, p = 0.005). Importantly, cardiovascular mortality (3.4% for ACN2 and 5.6% for MyV, p = 0.720) and valve-related deaths were comparable.

ACN2 showed superior long-term hemodynamics and lower matched 4-year mortality and stroke rates, though cardiovascular mortality and valve-related deaths were comparable.

Ischemic stroke (IS), a major global health concern, is associated with aging-related clonal hematopoiesis of indeterminate potential (CHIP), though their mechanistic connection remains unclear. This study explores the causal CHIP-IS relationship, key genetic drivers, and potential therapies.

Genetic markers for CHIP were selected as instrumental variables and analyzed through bidirectional two-sample Mendelian randomization (MR) using GWAS data from IS cohorts. Functional annotation of significant loci was performed via FUMA, while transcriptomic datasets from GEO underwent differential expression analysis, weighted gene co-expression network construction, and machine learning-driven biomarker discovery. Protein-protein interaction networks and single-cell RNA sequencing (scRNA-seq) were employed to elucidate cellular mechanisms.

MR analysis revealed a significant causal association between CHIP and cardioembolic stroke (CES) risk (OR = 70.15, 95% CI = 2.03-2428.52, p = 0.02). PARP1 and CD3G emerged as hub genes connecting CHIP to IS pathogenesis, validated through multi-omics integration. Fourteen feature genes were identified, and potential therapeutic drugs targeting this pathway were discovered. scRNA-seq analysis further demonstrated downregulation of CD3G in T cells post-IS, disrupting immune cell communication and differentiation.

This study provides robust genetic evidence for CHIP-mediated predisposition to CES and identifies PARP1 and CD3G as critical therapeutic targets. The integration of machine learning and single-cell genomics offers novel insights into immune dysregulation in IS, paving the way for precision prevention strategies in CHIP patients.

Editor's note: This is the next installment in a series on electrocardiogram (ECG) interpretation. Nurses in all settings should know the basics, as medications and physiological changes can cause cardiac arrhythmias. Each article will start with a brief case scenario and an ECG strip and then take you step by step through analyzing the heart rhythm.

This article reports a child with cardioaciocutaneous syndrome (CFCS) caused by a rare microdeletion of chromosome 19p13.3, and a literature review is conducted. The child had unusual facies, short stature, delayed mental and motor development, macrocephaly, and cardiac abnormalities. Whole-exome sequencing identified a 1 040 kb heterozygous deletion in the 19p13.3 region of the child, which was rated as a "pathogenic variant". This is the first case of CFCS caused by a loss-of-function mutation reported in China, which enriches the genotype characteristics of CFCS. It is imperative to enhance the understanding of CFCS in children. Early identification based on its clinical manifestations should be pursued, and genetic testing should be performed to facilitate diagnosis.

The heart-brain axis hypothesis suggests a bidirectional connection between the brain and the heart with relevant implications in health and disease. Cardiovascular diseases have been empirically linked to an increased risk of neurological diseases. However, it remains unclear to what extent different cardiovascular diseases affect brain health quantitatively across subjects and if that is associated with the extent the heart is affected by a disease. Therefore, this study aims to explore how cardiovascular diseases affect biological ageing of the brain and heart by quantifying the brain age gap (BAG) and the heart age gap (HAG) and relating the two to each other.

This study used data from UK Biobank participants with available T1-weighted brain magnetic resonance imaging (MRI) scans, cardiac MRI-derived features, as well as pulse wave analysis cardiac measurements. This dataset included 7,500 healthy females and 6,684 healthy males. The data from healthy subjects was used to train biological brain age prediction machine learning models. For BAG computation, a convolutional neural network was trained based on the MRI data, while a CatBoost model was trained for HAG analyses based on the tabulated cardiac features. Individuals with cardiovascular diseases (F = 2,304, M = 2,925) in the UK Biobank were categorized using Phecodes and split based on sex and used to calculate the HAG and BAG for further analyses.

In 36 sex-specific cardiovascular disease groups, 24 showed significant differences from healthy subjects in the BAG and HAG distributions, whereas no strong correlations between the BAG and HAG distributions within disease groups were found. However, some diseases, such as hypotension and cardiac conduction disorders, showed sex-specific differences.

This study demonstrates that the combined use of HAG and BAG biomarkers provides a more comprehensive understanding of the interplay between cardiovascular and neurological ageing. The significant differences observed in disease groups, while lacking a strong correlation between the BAG and HAG, questions the generalizability of the heart-brain axis theory with respect to age gap biomarkers, suggesting potentially heterogeneous aging processes of the two systems that warrant further investigation in future work.

Regular monitoring and follow-up of patients with metabolic dysfunction-associated fatty liver disease (MAFLD) are of paramount importance in ensuring effective management of the condition. The ALI was assessed as a composite measure reflecting nutritional status and systemic inflammation. It was calculated as body mass index (BMI) (kg/m²) × serum albumin (g/dL)/neutrophil-to-lymphocyte ratio (NLR). Our study aims to find the relationship between advanced lung cancer inflammation index (ALI) levels and the prognosis of patients with MAFLD and to determine the predictive value of ALI in this context.

Multivariate-adjusted Cox regression models were used to analyze the association between ALI and all-cause, cardiovascular, cancer, and diabetes-related mortalities in patients with MAFLD. Kaplan-Meier curves showed the association of ALI with all-cause and cardiovascular mortalities in patients with MAFLD. Follow-up time for this study was calculated from the date of examination to the date of death or to 31 December 2019, and mortality was ascertained using the International Classification of Diseases, 10th Revision codes. Restricted cubic spline (RCS) analysis was conducted to assess the potential non-linear relationship between ALI level and MAFLD prognosis. The predictive ability of ALI was observed using receiver operating characteristic (ROC) curves. Stratified and sensitivity analyses were used to enhance the reliability and robustness.

This study included 2,908 patients with MAFLD from the National Health and Nutrition Examination Survey (NHANES) database between 2003 and 2018. The median follow-up period for the 2,908 participants was 10.3 years, during which 636 deaths occurred. In the Cox regression model, the HRs (95%CIs) for all-cause, cardiovascular, cancer, and diabetes-related mortalities in the last quartile compared to the first quartile of ALI levels were 0.62 (0.44-0.85), 0.25 (0.14-0.45), 0.96 (0.51-1.81), and 0.69 (0.25-1.92), respectively. RCS analysis demonstrated a L-shaped non-linear association between ALI levels and both all-cause and cardiovascular mortalities in participants with MAFLD. Subgroup analyses highlighted population heterogeneity in the relationship between ALI and MAFLD prognosis. ROC curve analysis showed that ALI had strong predictive power for all-cause and cardiovascular mortalities, with area under the curve values of 0.80 (0.77-0.83) and 0.82 (0.74-0.89), respectively.

There was an L-shaped nonlinear association of the protective effect of ALI: when the indicators are below specific thresholds (all-cause mortality 71.48, cardiovascular mortality 68.54), a higher ALI was significantly associated with reduced mortality risks in MAFLD patients; otherwise the protective effect tended to be consistent. ALI exhibits a robust predictive capability for all-cause and cardiovascular mortalities among participants with MAFLD, providing a valuable prognostic tool for optimizing patient management. We recommend early surveillance and management of patients with MAFLD to improve patient survival.

Dyslipidemia, a key modifiable risk factor for cardiovascular diseases, is managed using lipid-lowering therapies. Medication adherence for dyslipidemia treatment is poor across the globe, impacting treatment effectiveness. This highlights the need for scalable strategies, such as mobile app-based behavioral interventions, to enhance adherence to lipid-lowering therapies.

The study assesses the impact of "My A:Care" and "My A:Care Smart Coach" mobile interventions on adherence to dyslipidemia treatment.

This proof-of-concept, open-label, single-center study randomized 150 patients with suboptimal adherence to dyslipidemia treatment into three groups (1:1:1): My A:Care, My A:Care Smart Coach (intervention), and a no-app control group. Participants were monitored over 12 weeks. The primary objective was to assess changes in medication adherence, with secondary outcomes including changes in lipid parameters and beliefs about lipid-lowering medications. The study also explored the association between adherence and app engagement.

At week 12, the Medication Adherence Report with Visual Analog Scale (MARS-5VA) Part 1 scores were modestly, but significantly lower in the control group compared to the intervention groups: Mean (SD); No-App: -0.3 (0.9), Smart Coach: 0.0 (0.7) [p = 0.035], My A:Care-All: 0.0 (0.7) [p = 0.056]. Compared to the control, the intervention groups also showed greater improvements in non-HDL-C levels [% change (SE): My A:Care-All: -5.5% (3.2), Smart Coach: -4.3% (3.7), No-App: -1.8% (3.7)], along with favorable trends in TC, LDL-C, and HDL-C.

This proof-of-concept study suggests that the My A:Care and Smart Coach apps may positively impact adherence to lipid-lowering therapy in patients with dyslipidemia. The positive adherence outcomes and potential benefits in lipid control indicate promising early signals that warrant further investigation in larger, confirmatory studies.

NCT05370703.