BACKGROUND:Patients with low gradient severe aortic stenosis (AS) are clinically challenging cohort requiring additional imaging modalities to secure diagnosis of severe AS. We aimed to assess whether resting aortic valve area (AVA) can determine hemodynamic severity of AS in patients with high trans-valvular flow rate (TFR). METHODS AND RESULTS:This was a retrospective single centre analysis of consecutive patients undergoing dobutamine stress echo (DSE) for AS work-up. A standard protocol for low-dose DSE was performed and data on resting as well as stress echocardiographic parameters were prospectively entered in a dedicated database. The accuracy of resting aortic valve area was assessed at various TFR. Of 201 patients in this study, the mean age was 78 ± 8 years, and 69% were male. True severe aortic stenosis was identified in 102 (50.7%) of patients. Unlike indexed stroke volume and left ventricle ejection fraction (LVEF), TFR was an independent predictor of true severe AS, even after adjustment for mean gradient and AVA [odds ratio (OR) 0.86, 95%CI (0.74-1.00), P = 0.044]. Receiver-operator characteristics (ROC) analysis using resting aortic valve area demonstrated an area under the curve (AUC) of 0.91, 95% CI 0.82-0.99, P < 0.001 in patients with TFR ≥220 ml/s. A TFR of ≥220 ml/s, with a resting AVA <1.0 cm2 had a 100% positive predictive value for true severe AS. CONCLUSIONS:TFR is an easily applied echo measurement. In situations with discordant echo data, TFR ≥220 ml/s supports the diagnosis of severe aortic stenosis and negates the need for further diagnostic imaging.
BACKGROUND:Obesity-related heart failure with preserved ejection fraction (HFpEF) is characterized by concentric remodeling, diastolic dysfunction, and systemic inflammation. Tirzepatide, a dual GIP/GLP-1 receptor agonist, produces substantial weight loss, but real-world echocardiographic evidence of cardiac reverse remodeling remains limited, particularly in prospective cohorts. METHODS:We conducted a prospective, single-center, longitudinal observational cohort study of 50 adults with obesity-related HFpEF (LVEF ≥50%, BMI ≥30 kg/m2) initiating tirzepatide in routine care. Co-primary endpoints were changes in left ventricular (LV) mass and the E/e' ratio from baseline to ≈6 months. Multiplicity was controlled via hierarchical gate-keeping with Benjamini-Hochberg false discovery rate (FDR) correction. RESULTS:Over a median follow-up of 5.8 months, mean LV mass decreased by -12.4 g (95% CI -15.4 to -9.4; q < 0.001; SRM -1.16) and E/e' improved by -1.45 (95% CI -1.85 to -1.11; q < 0.001; SRM -1.08). KCCQ score increased by +13.1 points (q < 0.001), 6-min walk distance by +43 m (q < 0.001), and BMI decreased by -5.8 kg/m2 (q < 0.001). NT-proBNP, hs-CRP, and hs-TnT all declined significantly (all q < 0.01). NYHA class improved in 30 patients (60%) with none worsening (p < 0.001). CONCLUSIONS:In real-world practice, tirzepatide use was associated with reverse cardiac remodeling, improved diastolic function, and better health status in obesity-related HFpEF. These findings complement randomized trial evidence and support further evaluation of incretin-based therapy in obesity-related HFpEF.
AIMS:To develop a cardiovascular disease (CVD) risk prediction model with improved accuracy and interpretability by integrating diverse risk factors and applying Automated Machine Learning (AutoML), thereby enhancing clinical utility over conventional models. METHODS:This is a prospective cohort study. Data were obtained from the Multi-Ethnic Study of Atherosclerosis (MESA), including baseline and fifth follow-up visits, comprising 4713 participants. Exercise and dietary data were harmonized via Metabolic Equivalent of Task (MET) and Healthy Eating Index-2015 (HEI-2015), respectively. Predictor selection was performed using the Boruta algorithm alongside Random Forest (RF) error rate cross-validation. Logistic regression, four traditional machine learning algorithms, and H2O AutoML were each applied for model training and evaluation. Finally, the best-performing model was further interpreted using SHapley Additive exPlanations (SHAP). RESULTS:A total of 21 predictors were selected, including age, sex, and Total Cholesterol (TC). Among the evaluated models, H2O AutoML outperformed other methods with an accuracy of 0.864, specificity of 0.892, precision of 0.610, F1 score of 0.670, and a Youden index of 0.635, achieving the highest AUC of 0.882 (0.846-0.918). SHAP analysis revealed the relative importance of predictors, with age, TC and Digit Symbol Score (DSS) ranking highest. CONCLUSIONS:This study developed an AutoML-based CVD risk prediction model with superior discrimination and calibration, providing clinicians a practical tool for risk stratification. By enabling personalized prevention and early identification of high-risk individuals, this model has the potential to reduce CVD burden at the population level. Notably, DSS exhibited high importance and may represent a candidate risk marker.
BACKGROUND:Coronary vulnerable plaques are closely associated with acute coronary events, and non-invasive diagnostic biomarkers are urgently needed due to the invasiveness of VH-IVUS. This study aimed to explore the value of sASGR1, Cathepsin V, and SII in identifying vulnerable plaques. METHODS:Based on coronary angiography and VH-IVUS, the 175 hospitalized patients admitted to the cardiology department were classified into a non-coronary heart disease (CHD) group and a CHD group (including a stable plaque group and a vulnerable plaque group). Baseline clinical, laboratory, CTSV, sASGR1, and SII data were compared among the groups. Multivariate logistic regression was used to screen independent predictors for vulnerable plaques, and ROC curves and the Hosmer-Lemeshow test were applied to assess diagnostic efficacy and model calibration. RESULTS:CTSV, sASGR1, and SII were significantly higher in the CHD group than in the non-CHD group (all p < 0.05). Univariate analysis in CHD patients showed that triglycerides, LDL-C, neutrophil count, monocyte count, CTSV, sASGR1, and inflammatory markers (SII, MHR, NHR) were significantly associated with vulnerable plaques (all p < 0.05). Multivariate logistic regression revealed that CTSV, sASGR1, and SII were independent risk factors for vulnerable plaques. The ROC curve revealed that the novel model (CTSV, sASGR1, and SII) yielded an AUC of 0.751 (95% CI: 0.665-0.837, P < 0.001), exhibiting superior diagnostic performance compared to any single indicator. Hosmer-Lemeshow test verified satisfactory model calibration (P = 0.941). CONCLUSION:CTSV, sASGR1, and SII are independent risk factors for coronary vulnerable plaques. Their combination achieves favorable diagnostic efficacy to facilitate risk stratification among CHD patients.
BACKGROUND:We aimed to probe the European Society of Cardiology (ESC) guideline recommended electrocardiographic (ECG) criteria for degree of under detection of left ventricular hypertrophy (LVH) across clinically relevant subgroups in a contemporary general population and if ECG-threshold recalibration could promote diagnostic equity. METHODS:We studied participants in the Copenhagen General Population Study. Cardiac computed tomography (CT) was used to define CT-LVH, and ECG-LVH was defined according to ESC guideline: Sokolow-Lyon, Cornell voltage, or Sokolow-aVL criteria. Diagnostic performance was assessed using Poisson regression across subgroups defined by age above 60 years, sex, overweight (BMI ≥ 25 kg/m2), hypertension, diabetes mellitus, obstructive pulmonary disease, and physical activity. ECG-thresholds were recalibrated to 95% specificity while maximizing sensitivity across all subgroups with disparities in both measures. Recalibration was performed in 50% of the population and validation in the remaining 50%. RESULTS AND CONCLUSIONS:We studied 9392 participants with median age of 60 years, of whom 58% were women. By CT 839 (9%) had CT-LVH. The guideline ECG-LVH definition had overall 20% sensitivity and 96% specificity. Sensitivity was lower in women than men (15% versus 26%; P < 0.001) and individuals with overweight compared to normal weight (16% versus 23%; P = 0.005). The recalibrated ECG-thresholds provided overall 36% sensitivity and 91% specificity in the validation cohort with consistent sensitivity and specificity across subgroups. The new recalibrated ECG criteria promoted diagnostic equity in LVH detection across sex and BMI subgroups, increasing overall sensitivity at a slight specificity cost.
AIMS:To investigate the association between serial high-sensitivity cardiac troponin-T (hs-TnT) concentrations and subsequent heart failure in individuals presenting with suspected acute coronary syndrome (ACS). METHODS AND RESULTS:Utilizing Danish nationwide registries, we identified individuals without known heart failure who underwent serial hs-TnT assessment for suspected ACS between 2012 and 2019. Individuals were categorized based on the hs-TnT concentration patterns from the first to the second measurement (normal, rising, persistently elevated, or falling), the extent of hs-TnT concentration change (≤20%, >20 to 50%, or > 50%), and quartiles of peak hs-TnT levels (≤9 ng/l, 10-19 ng/l, 20-263 ng/l, and ≥ 264 ng/l). Standardized absolute and relative risks of incident hospitalization or outpatient contact for heart failure were computed using cause-specific multivariable Cox regression with average treatment effect modeling. Of 26,835 individuals, 38.8% received a discharge diagnosis of myocardial infarction, 5.1% of unstable angina, and 56.1% of suspected myocardial infarction or chest pain. Within the initial 30 days, 1122/26,835 (4.2%) persons received a heart failure diagnosis, with an additional 707/25,085 (2.8%) diagnosed between days 31-365. Subjects with two normal hs-TnT values exhibited the lowest standardized absolute risk (0-30 days: 0.3%; 31-365 days: 0.4%), while those with persistently elevated concentrations demonstrated the highest risk (0-30 days: 6.6%; 31-365 days: 4.3%). Heart failure risk also exhibited a significant, positive association with peak hs-TnT concentration. CONCLUSIONS:In individuals presenting with suspected ACS, persistent hs-TnT elevation was associated with the highest risk of subsequent heart failure. A dose-response association was observed between peak hs-TnT concentrations and incident heart failure.
AIMS:Pre-participation cardiovascular screening (PPS) is essential for preventing SCD in athletes, yet ECG interpretation requires expertise and remains resource-intensive. We aimed to evaluate the feasibility and diagnostic performance of a deep learning (DL) model for analysis of clinical data and resting 12‑lead ECG obtained during routine PPS in competitive athletes. METHODS:In this prospective single center observational study, competitive athletes aged 18 to 60 years and undergoing routine PPS were enrolled. PPS included medical history, physical examination, resting and exercise ECG. Athletes were classified as fit or not fit for competitive sports according to clinical evaluation. Resting ECG and clinical variables were analyzed using a multimodal DL architecture. Model performance was assessed using stratified 10-fold cross-validation against PPS clinical classification. RESULTS:A total of 526 athletes were enrolled (72% male, median age of 27 years (IQR: 20-41); 166 (32%) had a negative PPS result. The test setting (10-fold cross-validation), the model achieved moderate discrimination with an accuracy of 0.64 ± 0.08, SE 0.68 ± 0.15, SP 0.61 ± 0.17, F1-score 0.72 ± 0.1, PPV 0.80 ± 0.07, NPV 0.48 ± 0.12, AUC 0.72(0.66-0.78). Training performances reached accuracy of 0.70 ± 0.06, SE 0.73 ± 0.12, SP 0.67 ± 0.14, F1-score 0.77 ± 0.07, AUC 0.79 (0.74-0.83. CONCLUSION:Automated DL-based analysis of 12‑lead ECG during PPS is feasible and showed encouraging diagnostic performance in competitive athletes. Although wider experience and external validation is required, AI-assisted multimodal ECG interpretation may represent a useful adjunct to physician assessment for cardiovascular risk stratification in sport screening programs.
BACKGROUND:Percutaneous atrial septal defect (ASD) closure is an established alternative to surgical repair for patients with secundum ASD, offering minimally invasive treatment with high procedural success rates. Despite its widespread adoption, clinically significant complications such as device embolization and erosion may occur. Our Survey aims at providing a comprehensive, multicenter perspective on the incidence, features, and management strategies for these complications, in order to improve procedural outcomes and patient safety through collaborative data collection. METHODS:This is an international, multicenter survey collecting retrospective data from 30 centers performing transcatheter ASD closures between 2011 and 2021. Participating institutions contributed anonymous aggregate data on patient demographics, procedural details, and clinical outcomes, focusing on the incidence, anatomical and procedural risk factors, and management of device embolization or erosion. RESULTS:A total of 30 institutions participated, providing data on 13.155 procedures of transcatheter closure of ASD, with 40% of them in children. Amplatzer device was used in 58% of cases, with balloon sizing performed routinely in 62% of institutions, mainly with stop flow technique. A total of 17 erosions (0.13%) were reported, of which 10 in children (incidence 0.19%) and 7 in adults (incidence 0.09%). Surgical repair was performed in all these cases, one patient died. Embolizations were reported in 91 cases (incidence 0.7%), with 60% of them in children. Most (80%) occurred within 24 h. Surgical retrieval was carried out in 29% of cases. Irrespective of management, no fatal complications occurred. CONCLUSIONS:Complications such as embolization and erosion after transcatheter ASD closure in children and adults are exceedingly rare but still present in clinical practice and require careful monitoring for prompt recognition and timely intervention, in order to obtain favorable outcomes.
BACKGROUND:There is little information regarding the characteristics of patients with myocardial infarction with non-obstructive coronary arteries (MINOCA) in terms of coronary endothelial function and prognosis, as compared to patients with angina and non-obstructive coronaries (ANOCA). We assessed differences in clinical profile, endothelial function and prognosis between patients undergoing acetylcholine (ACH) testing for MINOCA or ANOCA. METHODS:We combined two cohorts of patients undergoing ACH testing - ENDOCOR (multicentre; 2015-2023) and FISIOTON (single-centre; 2018-2024) - totalling 723 patients. Endothelial dysfunction was defined as any epicardial vasoconstriction to ACH or endothelium-dependent coronary flow reserve ≤1.5. RESULTS:MINOCA was diagnosed in 68 (9.4%) patients. Endothelial dysfunction was found in 57.4%, epicardial spasm in 7.05% and microvascular spasm in 1.94%, without differences between MINOCA and ANOCA. In multivariable regression, MINOCA was independently associated with resting chest pain (OR 3.63, 95% CI: 1.84-7.66), previous MI (OR 2.91, 95% CI: 1.29-6.30) and active smoking (OR 2.15, 95% CI: 1.04-4.30). Over a median follow-up of 3.0 years, major adverse cardiovascular events (MACE) occurred in 7.5% of patients. MINOCA (HR 2.81, 95% CI: 1.40-5.67, p = 0.004), endothelial dysfunction (HR 2.59, 95% CI: 1.29-5.21, p = 0.008) and male sex (HR 2.01, 95% CI: 1.13-3.58, p = 0.017) were independently associated with MACE. Patients with MINOCA and endothelial dysfunction had the highest event rate (19.4%). CONCLUSIONS:In patients with non-obstructive coronary arteries undergoing ACH testing, endothelial dysfunction and a MINOCA presentation were independently associated with adverse events, whereas classical spasm endotypes were not.
BACKGROUND:Carotid-femoral pulse wave velocity (PWV) is the gold standard measure of central arterial stiffness and a predictor of cardiovascular events in adults, with growing relevance in pediatric populations. Although PWV increases naturally with age, cardiometabolic risk factors may accelerate this process. This study compared carotid-femoral PWV between non-overweight and overweight/obese adolescents, evaluated its progression from prepubertal age to early adolescence, and identified independent determinants of arterial stiffness. METHODS:This longitudinal study included 118 participants from the Generation XXI cohort (Porto, Portugal) assessed at ages 8-9 and 13-14 years. Carotid-femoral PWV was measured at both time points using a validated portable device. Anthropometric data, office blood pressure, and fasting blood samples for lipid profile, glucose, and insulin were collected. Body mass index (BMI) classification followed World Health Organization references. RESULTS:PWV increased significantly from childhood to adolescence (5.01 ± 0.47 to 6.30 ± 1.05 m/s; p < 0.001). At 13-14 years, overweight/obese adolescents had significantly higher PWV than non-overweight peers. PWV at 13-14 years correlated positively with BMI, BMI z-score, systolic and diastolic blood pressure, and fasting glucose. In adjusted models, PWV at 8-9 years (β = 0.39; p = 0.039) and BMI z-score at 13-14 years (β = 0.33; p < 0.001) remained independent predictors of PWV at 13-14 years. CONCLUSIONS:Arterial stiffness in early adolescence reflects both vascular tracking from childhood and concurrent adiposity. These findings support early vascular screening and weight management interventions during key developmental periods to optimize long-term cardiovascular health.
BACKGROUND:Differentiating obstructive from non-obstructive coronary artery disease (CAD) at the time of acute coronary syndrome (ACS) diagnosis remains challenging, and there is a need for biomarkers that can provide clearer discrimination. AIM:This study aims to assess Tenascin-C's diagnostic utility in predicting significant coronary artery stenosis in individuals with ACS. METHOD:In this prospective single-center observational study, 204 patients with NSTEMI or UAP who underwent invasive coronary angiography were included. Serum Tenascin-C levels were measured within 48 h using ELISA, and patients were classified as having critical (≥70%) or non-critical CAD based on blinded angiographic assessment. The relationship between Tenascin-C, critical stenosis, and GRACE and SYNTAX scores was evaluated using logistic regression, correlation analyses, and ROC curves. RESULTS:Tenascin-C levels demonstrated robust discriminative performance (AUC 0.85) and were considerably greater in patients with critical CAD among the 204 included patients. Tenascin-C was the sole independent predictor of critical stenosis in multivariate analysis. Tenascin-C showed a modest correlation with the GRACE score and a substantial correlation with the SYNTAX score. Tenascin-C maintained a good diagnostic accuracy (AUC 0.87) in individuals with borderline hs-TnT levels (12-52 ng/L). CONCLUSION:Tenascin-C demonstrated greater discriminative ability than hs-TnT for identifying critical coronary stenosis in patients with NSTEMI or UAP, particularly in the borderline troponin range. These findings suggest that Tenascin-C may provide complementary information to current biomarkers and support more precise clinical decision-making.
PURPOSE:Valvular heart failure (VHF) accounts for 1-5% of heart transplant listings. Comparative outcomes relative to other heart failure etiologies remain poorly characterized. This study defines the VHF phenotype and compares waitlist and transplant outcomes to other heart failure recipients. METHODS:This retrospective cohort study uses the UNOS thoracic transplant database to analyze adult, first-time, heart-only listings with a diagnosis of heart disease. Patients were grouped by diagnosis as VHF or non-VHF. The primary outcome was waitlist events; post-transplant survival and outcomes were secondary analyses. Subgroup analysis was performed in the post-2018 allocation era. RESULTS:VHF recipients were older (55.3 vs 54.0 years, P = 0.004), more frequently female (36.1% vs 25.0%, P < 0.001), and had higher rates of prior cardiac surgery (P < 0.001) with greater pulmonary vascular burden. At time of listing, VHF recipients had higher ECMO rates (4.9% vs 2.5%, P < 0.001) and lower VAD use (17.3% vs 31.7%, P < 0.001). VHF diagnosis was not independently associated with transplantation rates (SHR 0.979, P = 0.749) but was associated with a 23% higher rate of waitlist death/too sick to transplant (SHR 1.233, P = 0.005). Post-transplant survival was not significantly different between groups (P = 0.812). Post guideline changes, the waitlist mortality difference was attenuated. CONCLUSION:VHF represents a distinct but transplantable phenotype of heart failure. Although VHF patients faced higher waitlist mortality risk, allocation framework revisions attenuated this difference, and post-transplant survival is comparable to non-VHF recipients. Independent predictors of mortality are patient-level risk factors, supporting early referral and optimization as the primary strategy for outcome improvement in this phenotype.
BACKGROUND:Evidence regarding the role of N-terminal pro-brain natriuretic peptide (NTproBNP) in chronic coronary syndrome (CCS) remains limited. We aimed to investigate the association between plasma NTproBNP levels and the presence and extent of coronary artery disease (CAD) in a prospective real-world cohort. METHODS:This prospective observational cross-sectional study included 676 consecutive patients (mean age 67 ± 7 years; 20% women) referred for elective coronary angiography for suspected CCS, as part of the BNP-CAD study (ClinicalTrials.govNCT07013344). Patients with conditions known to elevate NTproBNP were excluded. Obstructive CAD was defined as stenosis ≥70% (≥50% for the left main). Prognostically significant CAD was defined as involvement of the left main or proximal LAD artery. RESULTS:Obstructive CAD was identified in 432 patients (64%). NTproBNP levels were significantly higher in patients with obstructive CAD compared to those without (124 vs. 96 pg/mL, p < 0.001) and increased with the number of vessels involved and degree of stenosis. After adjustment for clinical confounders and high-sensitivity troponin T, NT-proBNP remained independently associated with obstructive CAD (OR per 100 pg/mL increase: 1.18; 95% CI: 1.03-1.36; p = 0.021). Prognostically significant CAD was present in 197 patients (46% of those with obstructive CAD) and was associated with higher NT-proBNP levels (133 vs. 107 pg/mL; p = 0.006), although discriminatory performance remained modest (AUC: 0.60; 95% CI: 0.55-0.64). CONCLUSION:NT-proBNP was independently associated with obstructive CAD and correlated with coronary disease burden. However, its modest discriminatory performance precludes its use as a stand-alone diagnostic test for high-risk coronary anatomy.
BACKGROUND:Coronary artery disease (CAD) is the leading cause of death globally and a major contributor to hospital readmission. This study aimed to predict 30-day mortality in patients hospitalized with acute and chronic CAD using a structured machine learning approach with data from multiple centers. METHODS:We conducted a retrospective cohort study using patient data from the Taipei Medical University Clinical Research Database (TMUCRD). Multiple machine learning algorithms were employed to develop predictive models for 30-day mortality. Model performance was evaluated using a stratified fivefold cross-validation approach. Key performance metrics included the area under the curve (AUC), accuracy, sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and F1 score. RESULTS:A total of 23,267 patients (mean age 64.9 years) were included, with 1215 deaths overall (5.2%): 570 (3.7%) in the internal cohort (n = 15,510) and 645 (8.3%) in the external validation cohort (n = 7757, Shuang Ho Hospital). XGBoost achieved the best performance for the overall and acute CAD cohorts (AUROC 0.845 and 0.820, respectively), while logistic regression performed best for chronic CAD (AUROC 0.766). Key predictive features included the Charlson Comorbidity Index, hemoglobin level, emergency room admission status, age, and creatinine level. CONCLUSION:The use of a structured machine learning approach to predict 30-day mortality in patients with acute and chronic CAD demonstrated promising discriminative performance, providing valuable insights that could enhance personalized care and inform clinical decisions.
