Aortic stiffness increases ventricular afterload and limits exercise capacity in heart failure (HF), but its dynamic response to exercise remains insufficiently defined. This study aimed to evaluate exercise-induced changes in aortic stiffness and their association with functional capacity in patients with early-stage HF. Heart-rate recovery (HRR) was assessed as secondary parameter.

This prospective study enrolled 42 compensated HF patients (ejection fraction <45%) in sinus rhythm. Aortic diameters were measured 3 cm above the aortic valve using M-mode echocardiography to calculate the Stiffness Index (SI), Peterson's Elastic Modulus (Ep), and Aortic Distensibility (D). All patients underwent a symptom-limited treadmill test using the modified Bruce protocol. HRR was defined as the difference between peak heart rate and heart rate at 1 min of recovery. Echocardiographic measurements were repeated within 60 s after exercise.

Aortic stiffness increased significantly after exercise [SI: 5.05 (4.18-6.30) to 6.03 (4.59-7.79); p < 0.001], while distensibility decreased [2.64 to 1.90 ×10 - 6 cm2·dyn-1; p < 0.001]. Patients with NYHA class II had higher SI and Ep and lower D at rest and post- exercise than NYHA class I patients (all p < 0.001). NYHA class was the only independent predictor of post-exercise stiffness (β = 3.32; 95% CI 1.33-5.30; p = 0.002). Exercise capacity was significantly lower in NYHA II patients (7.0 vs 10.1 METs; p < 0.001). HRR showed no significant association with aortic stiffness or exercise capacity.

In early-stage HF, increased resting and exercise-induced aortic stiffness is strongly associated with reduced functional capacity, indicating early impairment of vascular compliance reserve during physiological stress.

The mortality following cardiac surgery remains high. The neutrophil-to-high-density lipoprotein cholesterol ratio (NHR) is a marker that reflects both inflammation and metabolic status, and it has shown promise in predicting outcomes across various diseases. However, the association of NHR with the outcomes in cardiac sur gery patients has not been fully validated.

This retrospective cohort study analyzed data from the MIMIC-Ⅳ database, including 2784 patients who underwent cardiac surgery. Patients were categorized into three groups (Q1, Q2, Q3) based on the NHR value. The primary outcome was 90-day all-cause mortality. The secondary outcomes included 180-day and 360-day all-cause mortality. Kaplan-Meier survival analysis, Cox proportional hazards regression, and restricted cubic spline (RCS) analysis were employed to assess the relationship between NHR and all-cause mortality.

A total of 2784 patients (73.10% male) were enrolled. Higher NHR index levels were associated with an increased risk of 90-day,180-day, and 360-day all-cause mortality as shown by Kaplan-Meier curves. Cox proportional hazards analysis showed that the elevated NHR index was significantly related to all-cause death. Additionally, restricted cubic spline (RCS) analysis confirmed a linear positive relationship between NHR and all-cause mortality.

NHR is significantly associated with all-cause mortality in patients undergoing cardiac surgery. As a simple and cost-effective measure, NHR can support clinicians in the early identification of high-risk patients and guide personalized postoperative management strategies. To confirm its clinical utility and improve postoperative risk assessment and patient care, further large-scale, multicenter retrospective cohort studies are needed.

Metabolomics has emerged as a powerful discipline for capturing dynamic biochemical states and linking molecular processes to human health, disease, and biotechnology. This chapter explores the evolution of metabolomics from early profiling efforts to its current integration with advanced analytical platforms, computational biology, and precision medicine. We highlight how targeted and untargeted metabolomic strategies have advanced biomarker discovery, clarified disease mechanisms, and informed the development of personalized therapies in cancer, cardiovascular disease, diabetes, and other conditions. The role of pharmacometabolomics in refining drug response predictions and guiding therapeutic decisions is also examined. Beyond biomedicine, metabolomics drives innovation in biotechnology, synthetic biology, and bio-based production, while emerging tools such as single-cell metabolomics and machine learning continue to expand its scope. By directly tracing metabolic fluxes and engineering new pathways, metabolomics is becoming a practical engine for designing microbes, optimizing bioprocesses, and accelerating drug discovery.

This study aimed to validate the analytical performance of high-sensitivity cardiac troponin I (hs-cTnI) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) assays, and to establish age- and sex-specific reference intervals (RIs) using a large multicenter Chinese cohort.

hs-cTnI and NT-proBNP were measured on a fully automated chemiluminescence platform (Maglumi X8, Snibe, China). Analytical performance was validated following Clinical and Laboratory Standards Institute guidelines. Sex- and age-specific RIs for hs-cTnI (n=2,323) and NT-proBNP (n=2,333) were determined nonparametrically from IFCC-compliant cohorts across six Chinese provinces.

Analytical validation confirmed high sensitivity, specificity, satisfactory linearity, and strong interference resistance of hs-cTnI and NT-proBNP. hs-cTnI demonstrated 3.19 % total imprecision near 99th percentile URLs and >99.5 % detectable rates (>LoD) in healthy individuals, meeting third-generation hs-cTn criteria. RIs were established stratified by age and sex. In plasma, RIs of hs-cTnI were 11.97 ng/L for males and 11.61 ng/L for females, while 97.5th percentile URLs of NT-proBNP were 145.00 ng/L overall, 113.63 ng/L for males, and 160.75 ng/L for females. Elevated hs-cTnI levels were observed in residents of Ningxia and in women with central obesity.

The Snibe hs-cTnI assay fulfills IFCC high-sensitivity criteria. Age- and sex-specific RIs of hs-cTnI and NT-proBNP were established from a large multicenter Chinese cohort, confirming their essential role in accurate cardiovascular risk stratification.

Several observational and genetic studies have found an association between high urate serum levels and hypertension, heart failure, and cardiovascular mortality. Bempedoic acid is a recently approved hypocholesterolemic agent acting by inhibiting the ATP citrate lyase and thus the hepatic cholesterol biosynthesis. Despite its optimal safety profile, a minor and reversible increase of serum uric acid levels has been observed. This effect is due to the inhibition by bempedoic acid of organic anion transporters 2 and 3 (OAT2 and OAT3) which mediate the renal excretion of urate.

The increased levels of uric acid were associated with higher incidence of gout and could potentially have a negative effect on cardiovascular diseases. However, any adverse urate effect seems not to be clinically dominant for at least two reasons: 1) the extent of cardiovascular events reduction with bempedoic acid was similar to the one achieved with statins for a given magnitude of LDL-C lowering; 2) bempedoic acid was not associated with increased incidence of hypertension and heart failure, cardiovascular diseases strictly associated with hyperuricemia. Finally, uric acid lowering agents have not consistently demonstrated cardiovascular benefit in randomized clinical trials, and other drugs increasing, to the same extent, uric acid plasma levels, i.e. thiazide diuretic, do not increase cardiovascular risk.

Thus, the iatrogenic increase of plasma uric acid levels by the inhibition of OAT does not appear to have a clinically relevant negative impact on cardiovascular diseases.

Cardiovascular disease (CVD) remains the leading cause of global mortality, with pathophysiological alterations such as heart failure with preserved ejection fraction, diabetic cardiomyopathy, and atherosclerotic cardiomyopathy representing major risk factors. Semaglutide, a novel long-acting glucagon-like peptide-1 receptor agonist, has demonstrated substantial efficacy in glycemic control and weight reduction. Since 2016, accumulating evidence has highlighted its promising cardiovascular benefits, establishing semaglutide as a strong therapeutic candidate for CVD. This review synthesizes evidence since 2016 to elucidate semaglutide's cardiovascular outcomes, underlying mechanisms, and emerging frontiers, employing bibliometric analytical approaches such as burst detection mapping and cluster timeline analysis of references and keywords. Research on semaglutide in CVD has advanced rapidly, with mechanistic insights ​including improvements in insulin resistance, anti-inflammatory activity, and anti-atherosclerotic effects, as well as novel associations with ferroptosis inhibition. Clinical evidence across diverse patient subgroups indicates that future implementation will require ​precision-based regimen design. Moreover, although oral semaglutide alleviates injection-related discomfort, its ​gastrointestinal tolerability remains a concern. Furthermore, the potential reduction in lean mass requires further validation. Overall, this review aims to broaden the clinical application of semaglutide and highlight novel therapeutic avenues for patients with cardiovascular disease.

Atherosclerotic cardiovascular diseases, with peripheral artery disease (PAD) and coronary artery disease (CAD) being the most common, are leading causes of morbidity and mortality. Although PAD and CAD have nearly equivalent prevalences, PAD disproportionately affects low resourced and historically marginalized populations and is predominately cared for by surgeons with a growing interest in the PAD pathology by cardiologists. We hypothesize PAD is understudied with fewer and lower quality clinical trials (CTs) than CAD.

We conducted a cross-sectional study and queried the ClinicalTrials.gov database for PAD and CAD entries (2000-2024) and abstracted the structured CT characteristic data available. Our primary outcome was the number of CT entries/year with trends compared CAD and PAD using linear regression. Secondary outcomes included CT design components compared using descriptive statistics.

Of the 7805 CTs included, most were CAD entries (n = 6278 [79.4%]). CAD CT entries/year were 4x that of PAD (beta-coefficient [95% confidence interval]: 3.9 [3.5-4.2], P < 0.001). Overall, CTs most commonly evaluated treatments (67.3%), but diagnostic (4.5% versus 10.8%, P < 0.001) or prevention (5.9% versus 11.1%, P < 0.001) evaluations were more common in CAD trials. Fewer PAD CTs evaluated efficacy or effectiveness: PAD CTs were more commonly phase I (6.9% versus 3.9%, P < 0.001) and single-arm interventions (31.8% versus 20.1%; P < 0.001). PAD CT also utilized fewer bias reducing methods: less randomization (64.5% versus 77.4%; P < 0.001), less blinding (43.2% versus 46.9%; P = 0.006), and more industry funding (35.6% versus 20.6%; P < 0.001). Among completed CTs, PAD CTs enrolled fewer participants/CT (median: 50 [interquartile range: 20-123] versus 92 [38-269]; P < 0.001).

Atherosclerotic cardiovascular disease CTs have increased over time, with CAD having 4-fold more entries than PAD. Further, PAD CT methods less frequently evaluated treatment efficacy or effectiveness and had less rigorous design. Focused efforts targeting quality PAD CT development are needed.

Cardiovascular (CV) diseases are the leading cause of mortality in patients with systemic lupus erythematosus (SLE). While traditional risk factors inadequately assess CV risk, SLE-specific determinants remain elusive. We have conducted a study of CV outcomes in a cohort of SLE patients, aiming to facilitate individualized risk assessment.

The LESLY cohort comprised patients diagnosed with SLE at the University Hospital of Lyon between January 2002 and August 2020. CV events (CVE) were defined as myocardial ischemia or stroke. Complete-case multivariable analyses identified predictors of CV risk, among baseline SLE characteristics and traditional CV factors. The identified predictors were subsequently employed to develop machine learning models estimating CV risk in patients with SLE. The dataset was partitioned into training (80%, n = 699) and validation (20%, n = 175) sets.

CVE occurred in 55 LESLY patients (6.3%), including 27 acute coronary syndromes and 25 ischemic strokes, over a mean follow-up of 8.8 ± 5.2 years. Antiphospholipid antibodies (HR = 3.51 [1.91-6.43], p < 0.001) and inaugural skin involvement (HR = 2.69 [1.25-5.77], p = 0.011) were the most potent predictors of CVE occurrence. Finally, an Elastic Net Penalized Cox model accurately predicted individualized CV risks in an internal validation cohort (C-index 0.791 [95% CI: 0.674-0.906]; Brier score 6.4% [95% CI: 3.7-9.8%]).

This study corroborates the primacy of CVD in SLE, underscoring the predictive roles of inaugural skin involvement and antiphospholipid antibodies. These findings enabled the development of an exploratory risk stratification model that may inform clinical decision-making for cardiovascular risk management in SLE, pending external validation.

ChatGPT is a cost-effective artificial intelligence (AI) tool designed to facilitate virtual interactions with humans, and its application in healthcare is expanding. However, research on ChatGPT's effectiveness in public healthcare, particularly for cardiac patients, is still limited. This study aims to evaluate ChatGPT's potential in managing cardiovascular health for patients with acute or chronic cardiac conditions.

We analyzed real medical records from 'The Cardiovascular Care' program, affiliated with a university outpatient clinic. ChatGPT's performance was evaluated in terms of its ability to analyze clinical cases, propose diagnoses, and recommend appropriate actions. We also assessed whether ChatGPT's accuracy and errors varied depending on disease severity, rarity, mortality risk, and urgency.

When compared to physicians' records, ChatGPT provided correct responses in 43% of diagnostic hypotheses, 5% of recommended supplementary exams, and 10% of laboratory tests. It showed significant accuracy and discernment in diagnosing conditions influenced by factors such as severity, rarity, risk of death, and urgency. However, this discernment did not extend to recommendations for supplementary exams and laboratory tests. Interestingly, while ChatGPT's responses in these areas were often only partially accurate, they tended to be more detailed, sometimes unnecessarily so, than those provided by physicians. Diagnostic hypotheses from multiple models, including ChatGPT Health, DeepSeek, Gemini Pro, Perplexity AI, and ESC Chat, were also evaluated. Performance varied across models, with ChatGPT demonstrating the highest diagnostic accuracy among those assessed, despite still producing incorrect outputs.

Although ChatGPT demonstrates some diagnostic capability, its overall reliability remains questionable, with performance at times approaching random chance. Caution is advised when considering its use in clinical decision-making.

To explore the experiences of Emergency Department nurses when caring for patients presenting to the Emergency Department with mental health issues.

Qualitative descriptive study.

Ten nurses with experience caring for mental health patients participated in face-to-face, semi-structured interviews. Nurses were recruited if they were employed at a single tertiary Emergency Department in the Northern Territory, Australia. Interviews were audio-recorded, transcribed, and analysed using thematic analysis. The COREQ checklist guided reporting.

The four key themes were: systemic factors; emotional impact and staff culture; influence of communication; education and training. Systemic factors, such as overcrowding, staff shortages, long stays, and unsuitable Emergency Department environments, restricted therapeutic care and increased patient distress. The emotional impact of caring for mental health patients, combined with reactive workplace culture and stigma, contributed to moral distress and burnout. Clear communication and teamwork supported care, while limited mental health education left nurses underprepared and reliant on informal learning. Participants emphasised the need for clear protocols, targeted training, and structured support to enhance patient outcomes, nurse confidence, and well-being.

Emergency Department nurses face systemic, cultural, and educational barriers that compromise patient care while contributing to stress, fatigue, and burnout. Addressing these challenges through integrated care pathways, targeted education, and staff support is essential to improve patient outcomes and sustain the nursing workforce.

Data from this study identifies there is an urgent need to implement practical strategies to reduce challenges for nurses in caring for patients presenting to the ED with mental health issues.

This study revealed that systemic pressures, emotional fatigue, and limited training hinder effective care. This research can inform hospital leaders, policymakers, and educators to improve support, training, and care pathways within ED settings.

The authors have adhered to the COnsolidated criteria for REporting Qualitative research (COREQ).

No patient or public contribution was made.