Artificial intelligence (AI) tools such as large language models are increasingly used in clinical decision support, yet their reliability in vascular medicine remains uncertain. This study evaluated the accuracy and guideline concordance of ChatGPT-5 in vascular disease management.

Seventy open-ended clinical questions were derived from five major national and international vascular guidelines. Responses generated by ChatGPT-5 were independently assessed by five cardiovascular surgeons using a five-point Likert scale. Inter-rater agreement was analyzed using the free-marginal multirater kappa statistic.

ChatGPT-5 achieved a mean score of 4.74±0.27, showing strong consistency with evidence-based recommendations. Forty questions (57%) received perfect agreement, and inter-rater reliability was moderate (κ=0.50; 95% CI: 0.37-0.64).

ChatGPT-5 produced guideline-aligned and clinically sound responses in vascular disease scenarios. While promising as a supportive clinical tool, broader datasets and real-world validations are needed to ensure clinical translatability.

Acute myocardial infarction (AMI) is a leading global cause of death with a sudden onset, which necessitates rapid and accurate diagnosis for effective treatment. However, existing detection methods for emergency scenarios (e.g., ambulances) suffer from limited sensitivity and high cost, hindering their widespread application. To address this unmet clinical need, we developed a rapid and highly sensitive immunoassay platform based on surface-enhanced resonance Raman scattering (SERRS) for the quantitative detection of cardiac troponin T (cTnT), the gold-standard biomarker for AMI. This platform exhibits several advances. First, an antibody-oriented engineering strategy combined with core-shell SERRS nanotag synthesis fully exposes the antibody Fab regions to improve antigen-binding efficiency while reducing the nanotag cost by up to 75%. Meanwhile, selection of the resonance Raman reporter IR-808, which matches the 785 nm laser excitation wavelength, significantly enhances the detection signal intensity and sensitivity. Integrating these advantages with the classic sandwich immunoassay structure, the assay achieves a remarkable limit of detection of 0.24 pg/mL within only 7 min. Furthermore, systematic optimization of the incubation buffer (including pH value, surfactants, and blocking agents) effectively minimizes nonspecific adsorption, enabling 100% accurate differentiation between cTnT-positive and negative human serum samples. Collectively, this sensitive, rapid, and cost-effective platform demonstrates great potential for AMI point-of-care testing and prognosis monitoring.

Cardiovascular disease (CVD) remains the leading cause of mortality. New biomarkers are needed to improve CVD risk prediction. Several studies have reported associations between surfactant protein D (SP-D), an innate immune system component, and CVD; however, general population studies remain scarce. The main aim of this study was to investigate the association between SP-D and CVD events incidence in the Spanish general adult population.

Socio-demographic, lifestyle (including smoking status) and clinical data from 1707 participants of the di@bet.es cohort without previous CVD events were collected and analysed. CVD events (including both morbidity and mortality) were reported at baseline and after 7.5 years of follow-up. SP-D serum levels were measured by ELISA and categorized in quartiles.

SP-D categories are associated with CVD events incidence, independently from other strong risk factors such as cardiovascular risk scores (SCORE2 and SCORE2-OP), BMI, hs-CRP, or eGFR. Although SP-D has been linked to smoking, SP-D categories predicted CVD events incidence even among non-smokers. The addition of SP-D to multivariate models improved performance in the assessment, predicting 83% of the events with a specificity of 74% and a sensitivity of 84% in the overall population.

SP-D may be considered as a promising biomarker of CVD events in combination with other well established factors in clinical practice.

The heart is the most energy-demanding organ in the body and has a dynamically adaptable metabolic state. Under normal conditions, the adult heart primarily relies on mitochondrial oxidative phosphorylation for ATP generation, whereas glycolysis supplies a minor portion of the energy. However, under pathological conditions, glycolysis is increased, and mitochondrial oxidative phosphorylation is reduced. Hexokinase 2 (HK2) is the first rate-limiting enzyme in the glycolytic pathway in cardiomyocytes. Accumulating evidence in recent years has indicated that HK2 confers protection to the heart under pathological conditions. In this review, we summarize the roles of HK2 in cardiac ischemia/hypoxia, hypertrophy, and regeneration, focusing on its functions and the molecular mechanisms underlying these processes. Additionally, we discuss the application of pharmacologically targeting HK2 in pathological models and explore the potential value and future research directions of targeting the HK2-mitochondrial association. These findings provide new insights for harnessing HK2 to improve cardiac protection and design effective therapeutic strategies.

Clinical studies have shown that aortic arch pulse-wave velocity (PWV_aa), a measure of local aortic stiffness, is a strong independent predictor of subsequent white matter hyperintensity volume and white matter integrity, both associated with cognitive decline, elevated stroke risk, vascular dementia, and neurodegenerative diseases. Total arterial compliance (TAC), a measure of global arterial stiffness, has been recognized as a marker of preclinical vascular disease. This study introduces a smartphone-based method for the noninvasive measurement of PWV_aa and TAC using carotid pressure waveforms acquired via smartphone.

This method uses intrinsic frequency analysis of smartphone-acquired (iPhone) carotid pressure waveforms to assess PWV_aa and TAC. The method was trained, validated, and blind-tested on a cohort of 132 participants aged 20 to 90 years, including both healthy individuals and those with cardiovascular disease, all of whom underwent cardiac magnetic resonance imaging, tonometry, and iPhone waveform measurements.

In the blind test set, our method achieved Pearson correlations of 0.81 and 0.80 for PWV_aa and TAC, with biases of -0.20 m/s and -0.06 mL/mm Hg and limits of agreement of -4.09 to 3.68 m/s and -0.52 to 0.40 mL/mm Hg, respectively. In the heart failure population, correlations were 0.81 for both, with a PWV_aa a bias of -1.07 m/s and TAC bias of -0.06 mL/mm Hg.

Our smartphone-based method enables accurate assessment of local and global arterial stiffness metrics (PWV_aa and TAC). It offers easy-to-use monitoring of vascular aging and arterial health, with important implications for identifying patients at higher risk of neurodegenerative and cardiovascular diseases.

URL: clinicaltrials.org; Unique Identifier: NCT02240979.

Obesity prevalence in the United States has surged dramatically, yet comprehensive analysis of cardiovascular mortality patterns among adults with obesity remains lacking.

We analyzed CDC WONDER Multiple Cause of Death data for adults aged ≥ 25 years in the United States (1999-2023), identifying deaths where cardiovascular disease was the underlying cause and obesity was a contributing cause. Age-adjusted mortality rates (AAMR) per 100,000 population were calculated. Joinpoint regression analysis identified temporal trends stratified by sex, age, race/ethnicity, and geographic region.

Among 363,203 cardiovascular deaths, AAMR tripled from 3.40 to 10.34 per 100,000 (average annual percent change [AAPC]: +4.88%). Three distinct phases emerged: steady increase (1999-2018), pandemic acceleration (2018-2021, 12.22% annual increase), and recent decline (2021-2023). Men had higher mortality than women (12.69 vs. 8.06 per 100,000 in 2023). The 75-84 years group showed the steepest increase (AAPC: +5.66%). Non-Hispanic Black adults maintained the highest AAMR (18.30 per 100,000 in 2023). The South transformed from lowest to highest regional burden (AAPC: +5.52%). The disease spectrum shifted toward atherosclerotic and hypertensive conditions.

Cardiovascular mortality among US adults with obesity tripled over 25 years, with widening disparities across demographic and geographic groups, necessitating equitable public health interventions targeting high-risk populations.

This study aims to develop a prediction model to identify individuals at risk of hypertensive disorders of pregnancy (HDPs), including gestational hypertension and preeclampsia, by integrating epigenetic biomarkers and clinical factors in the first trimester of pregnancy.

A 2-stage nested case-control study, matched by age and body mass index, was conducted with 618 pregnant women in China, with peripheral blood samples collected in the first trimester to evaluate the average methylation levels of differentially methylated regions (DMRs) between controls and HDP cases. In stage 1 (discovery set), 24 controls and 27 cases were used to identify the differential DMRs. In stage 2, 294 controls and 273 cases were used to validate the previously identified DMRs. DMRs selected from the intersectional results of lasso regression, XGBoost, random forest, and Shapley Additive Explanations models were further combined with women's clinical risk factors to construct prediction models using logistic regression.

In stage 1, 52 differential DMRs were identified with a false-positive rate <0.05. In stage 2, 12 differential DMRs were consistently observed, and 3 DMRs located in the CTSA, HMGB1, and miR1908/FADS2 genes were selected to construct a prediction model for HDPs. After combining the selected DMRs with clinical factors, the model achieved an area under the curve of 0.863 (95% CI, 0.826-0.901) in the training set and 0.757 (95% CI, 0.686-0.828) in the test set.

Findings of this study offer potential opportunities to identify high-risk patients with HDP in early pregnancy through DMRs identified in peripheral blood and provide new insights into the epigenetic cause of HDP.

Obesity has long been identified as a noteworthy risk factor for cardiovascular diseases, including aortic stenosis. Nevertheless, an unexplained phenomenon known as the obesity paradox has arisen in the context of transcatheter aortic valve implantation (TAVI), inquiring conventional beliefs. The obesity paradox refers to better clinical outcomes observed in obese individuals undergoing TAVI. These include reduced all-cause mortality, lower rates of procedural complications, and improved long-term survival rates compared to their lean counterparts. Several theories have been proposed to explain the obesity paradox in TAVI. One of the most popular is the adipose tissue-mediated cardioprotective effect hypothesis. It is known that adipose tissue could offer both protective and harmful effects on the cardiovascular system. These effects can be linked to the adipose tissue's distribution, extension, and intrinsic biological characteristics. Obesity has been associated with adipose tissue malfunction, leading to proinflammatory and deleterious effects on the cardiovascular system. As opposed to what is believed, it is suggested that a healthy obese phenotype might be facilitated by exercise, leading to outstanding cardiovascular benefits. A healthy obese phenotype is also associated with a secretome profile that has unique adipose tissue features like adequate fat storage and formation of lipid droplets, a significant capacity for adipogenesis, minimal extracellular matrix fibrosis, potential for angiogenesis, adipocyte browning, and limited infiltration or activation of macrophages. This article is presented as a specialized narrative review, synthesizing current evidence on the relationship between obesity and outcomes in patients undergoing TAVI.

Valve-sparing root replacement (VSRR) prevents prosthesis-related complications in aortic root aneurysms but lacks objective feasibility criteria. Cusp prolapse frequently coexists with aortic root aneurysms, but its effect on VSRR outcomes remains unclear. We characterized prolapse mechanisms using three-dimensional (3D) transesophageal echocardiography (TEE) and examined the correlation between imaging features and surgical success as well as midterm outcomes.

This retrospective cohort study analyzed the data of 203 consecutive patients considered for VSRR. Cusp prolapse was diagnosed and mechanistically classified using quantitative 3D TEE analysis. The intraoperative findings confirmed regurgitation mechanisms. The outcomes compared the native valve preservation rates, postoperative echocardiographic results, mortality, regurgitation recurrence, and reintervention between prolapse and non-prolapse groups over a median 41-month follow-up period.

Among the 203 patients (mean age 48.0±13.7 years), 70 (34.5%) exhibited cusp prolapse. The predominant mechanism was disproportionate free margin (FM) elongation (64.3%). Surgical success was significantly lower in the prolapse group than the non-prolapse group (50.0% vs. 86.5%; P<0.001). Among the patients with cusp prolapse, prolapse mechanisms other than FM elongation, compared with FM elongation, were independently associated with unsuccessful VSRR [odds ratio (OR) =12.44; 95% confidence interval (CI): 3.42-45.24; P<0.001]. In addition, a reduced minimum geometric height was also independently associated with unsuccessful VSRR (OR =0.70; 95% CI: 0.50-0.97; P=0.035). There were no significant differences in the midterm outcomes between the prolapse and non-prolapse groups in terms of the echocardiographic parameters (P=0.373), mortality (P=0.581), regurgitation recurrence (P=0.769), or reintervention rates (P=0.580).

Cusp prolapse-driven by heterogeneous mechanisms-is prevalent in tricuspid aortic valve root aneurysms and reduces the likelihood of successful VSRR. Preoperative 3D TEE quantification of cusp pathology can aid in surgical planning. Despite lower preservation rates in prolapse patients, both groups achieved comparable midterm outcomes following judicious patient selection.