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Background: Acute myocardial infarction (AMI) represents a significant component of cardiovascular disease (CVD) mortality among the young and middle-aged populations of the United States (US). Research Question: To analyze the long-term trends and the impact of the COVID-19 pandemic on AMI-related mortality among the young and middle-aged populations of the US. Methods: Data from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER) multiple causes of death database were used to analyze death certificates from 1999 to 2023 for AMI-related deaths among the young and middle-aged population (aged 25-64) of the US. Age-adjusted mortality rates (AAMRs) per 100,000 people and associated annual percent changes (APCs) and average APC (AAPCs) were analyzed using Joinpoint regression analysis. Mortality trends were stratified by sex, race/ethnicity, and census region. Results: From 1999 to 2023, there were 970,454 AMI-related deaths among U.S. adults aged 25-64 years. The annual number of AMI-related deaths decreased from 44,040 in 1999 to 31,522 in 2023. The overall AAMR per 100,000 decreased from 31.02 deaths (95% CI, 30.73 to 31.31) in 1999 to 15.29 (95% CI, 15.11 to 15.46) in 2023 (AAPC -2.92%, 95% CI -3.22 to -2.75). The AAMR per 100,000 declined at a faster rate from 31.02 in 1999 to 19.57 in 2010 (1999-2010, APC -4.26), followed by a slower rate from 19.57 in 2010 to 16.67 in 2019 (2010-2019, APC -1.41), The declining trend was disrupted by a transient increase during the COVID-19 pandemic, with a peak AAMR of 19.73 (95% CI, 19.53 to 19.93) in 2021 (2019-2021, APC 8.52). The declining trend resumed from 2021 to 2023, with AAMR decreasing to the lowest levels of 15.29 in 2023 (2021-2023, APC -12.58). Heterogeneity across demographic and regional groups has narrowed during these 25 years. However, they are still prevalent, with men ( figure 1 ), non-Hispanic (NH) Black or African American, NH American Indian or Alaska Native ( figure 2 ), and the residents of the Southern United States ( figure 3 ) having higher mortality rates. Conclusion: Over the past 25 years, AMI-related mortality has declined in the young and middle-aged population of the US, although rates spiked during the COVID-19 pandemic before resuming their decline in 2022. While disparities among demographic and regional groups have narrowed, they still exist, necessitating comprehensive efforts to improve cardiovascular health outcomes.

Introduction: Elevated lipoprotein(a) [Lp(a)] levels (≥30 mg/dL or ≥50 mg/dL) have been associated with increased risk of cardiovascular diseases (CVD), including myocardial infarction and aortic stenosis. However, its association with all-cause mortality (ACM) in the setting of primary prevention remains unclear, with conflicting evidence regarding the cutoff associated with increased mortality risk. Objective: To assess the association between elevated Lp(a) and risk of ACM in the context of primary prevention. Methods: In this retrospective cohort study, we included adult patients (≥18 years old) who had at least one measurement of Lp(a) at any of the three Mayo Clinic sites between 2007 and 2024, with no history of CVDs (i.e., coronary artery disease, ischemic stroke/transient ischemic attack, or peripheral arterial disease) at the time of Lp(a) measurement. Lp(a) levels were categorized based on the following percentiles: ≤50th percentile (≤11.6 mg/dL), 50th to 80th percentiles (11.6–46.6 mg/dL), 80th to 90th percentiles (46.6–75 mg/dL), 90th to 95th percentiles (75–100 mg/dL), and >95th percentile (>100 mg/dL). Survival probabilities up to 15 years were compared across Lp(a) percentile categories using the Kaplan–Meier estimator and log-rank test. Additionally, univariable and multivariable Cox regression analyses were conducted to adjust for potential CV confounders and to quantify this association. Results: A total of 42,770 patients (median age: 53 years and 54% males) were included. We found no significant difference in survival probabilities between the Lp(a) categories based on the overall log-rank test (p=0.12; Figure 1A ). In the univariable analysis, only patients with Lp(a) >95th percentile (>100 mg/dL) had a statistically significant higher risk of ACM [hazard ratio (HR): 1.37; 95%CI: 1.07–1.74; p=0.012], compared to patients with Lp(a) <50th percentile (<11.6 mg/dL). Similarly, after adjusting for potential CV risk factors, only those with Lp(a) >95th percentile (>100 mg/dL) showed a significantly higher risk of ACM (adjusted HR: 1.37; 95%CI: 1.07–1.75; p=0.012, Figure 1B ). Conclusion: In the setting of primary prevention, only very high Lp(a) levels (≥100 mg/dL) were independently associated with increased risk of ACM, suggesting that higher Lp(a) thresholds may be more relevant for identifying individuals at increased risk of ACM than the conventional ≥50 mg/dL cutoff.

Background: Immune checkpoint inhibitors (ICIs) have transformed cancer therapy but may increase thrombotic risk through immune-mediated inflammation. While venous thromboembolism is a known complication in cancer, real-world data quantifying the incidence of pulmonary embolism (PE) and deep venous thrombosis (DVT) specifically in ICI-treated patients remain limited. Methods: We conducted a retrospective cohort study of cancer patients treated with ICIs at a tertiary institution from 2011 to 2022. Electronic health records were reviewed to identify cases of PE and DVT, along with baseline characteristics and clinical outcomes at one-year follow-up. Rates of PE and DVT were compared to those reported in the literature. Time-dependent Cox regression analyses were performed to assess associations of PE and DVT with one-year all-cause mortality and heart failure (HF), defined as a new diagnosis and/or HF exacerbation/hospitalization. Results: Among patients treated with ICI, the incidence of PE and DVT was 10.6% and 8.3%, respectively. These rates are higher than those reported in several prior studies, where PE incidence in patients treated with ICI typically ranged from 3% to 6% and DVT incidence from 3% to 5%. A history of valve disease, lung cancer, and treatment with pembrolizumab or durvalumab were more frequently observed among patients with PE, whereas pembrolizumab use was most prevalent among those who developed DVT. In time-dependent Cox regression analyses, PE was significantly associated with increased one-year all-cause mortality (HR: 2.62, 95% CI: 2.12–3.23, p < 0.001) and showed a trend toward increased HF (HR: 1.63, 95% CI: 0.96–2.75, p = 0.070). Similarly, DVT was also associated with significantly higher one-year all-cause mortality (HR: 2.63, 95% CI: 2.10–3.31, p < 0.001) and a significantly greater risk of HF (HR: 1.80, 95% CI: 1.03–3.15, p = 0.040). Conclusion: In this real-world cohort study, PE and DVT were more frequent than previously recognized in ICI-treated cancer patients and were associated with significantly increased risks of all-cause mortality and heart failure. Conditions such as valve disease, lung cancer, and specific ICI therapies (e.g., pembrolizumab or durvalumab) may help identify patients at higher thrombotic risk. These findings underscore the importance of vigilant thrombotic risk assessment and may support the need for proactive monitoring or prevention strategies in high-risk patients receiving ICI therapy.

Background: Arrhythmogenic and dilated cardiomyopathies (ACM/DCM) are associated with adverse cardiovascular outcomes, including sudden death. Artificial intelligence (AI)-enabled electrocardiographic aging algorithms estimate biological age from 12-lead tracings and predict cardiovascular outcomes in the general population. However, their utility in genetic ACM/DCM has not been studied. Methods: Retrospective review of 1,045 genotype-positive ACM/DCM patients was used to identify those with a pathogenic/likely pathogenic variant in ClinGen-classified definitive/strong evidence ACM/DCM-susceptibility genes. Following exclusion of patients without a baseline ECG for analysis (e.g. paced rhythms), the AI-ECG age gap (AI-EAG) was calculated by subtracting chronological from AI-ECG age. Genes were grouped into functional categories: desmosomal ( PKP2, DSP, DSG2, DSC2, JUP ), nuclear envelope ( LMNA ), sarcomeric ( TTN, MYH7, TNNT2 ), cytoskeleton/Z-disc ( FLNC, DES, DMD, BAG3 ), and regulatory/ion channel ( PLN, RBM20, SCN5A ). Cardiac MRI data included left ventricular structure, function, and late gadolinium enhancement (LGE) presence and pattern. Mann-Whitney U was used for group comparisons; results are shown as median (IQR). Results: Overall, 824 patients (52.8% male; median age of 40.7 years, IQR 26.5–53.4; and median AI-EAG of 7.49 years, IQR 0.43–15.26) were included. DES variant-positive patients had the highest (19.98 years, IQR 9.66–23.21) and BAG3 variant-positive patients the lowest (–0.95 years, IQR -6.05–7.61) AI-EAGs. Among gene groups, nuclear envelope had the highest (15.12 years, IQR 6.79–25.17) and sarcomeric the lowest (5.75 years, IQR -0.69-14.01) AI-EAGs. Cardiac MRI was available for 538/824 (65%) of which 233/538 (43.3%) had LGE. No significant difference in AI-EAG was observed between LGE-positive and -negative patients (6.99 vs. 7.94 years; p=0.831). However, several LGE patterns were associated with significantly higher AI-EAGs: subepicardial (9.88 vs. 6.84; p=0.004), transmural (13.83 vs. 7.25; p=0.012), apical (12.89 vs. 7.17; p=0.002), and septal (8.91 vs. 7.19; p=0.016). Conclusion: AI-EAG varies by gene and functional group, possibly reflecting gene-specific myocardial remodeling. While certain LGE patterns were linked to increased biological aging, overall LGE status was not. These findings suggest AI-EAG may capture disease activity that is distinct from LGE and could serve as a complementary, non-invasive biomarker in genetic ACM/DCM.

Background: Renal dysfunction is a known prognostic factor in advanced heart failure and among patients receiving temporary mechanical circulatory support (tMCS). However, the predictive value of post-Impella creatinine in determining healthcare resource utilization in patients bridged to transplant with Impella 5.5 remains unclear. This study aimed to evaluate the association between post-Impella creatinine and key hospitalization metrics in this population. Methods: We performed a retrospective cohort study of patients who received Impella 5.5 as a bridge-to-transplant between January 2020 and January 2025. Serum creatinine was collected 72 hours after Impella placement. The primary outcome was device-to-discharge time. Secondary outcomes included transplant-to-discharge time, post-transplant ICU length of stay (LOS), and total LOS (admission-discharge). Univariate and multivariable linear regressions were used to examine the association between post-Impella creatinine and each outcome, adjusting for age, gender, BMI, and LVEF. Results: 133 patients were supported with the Impella 5.5 as BTT and were included (median age 58 years (51–65), 82.7% were male, and 71.4% presented with non-ischemic cardiomyopathy. The median BMI was 27.7 (24.3–32.3), LVEF 17% (15–22), and post-Impella creatinine 1.32 mg/dL (0.96–1.71). The median device-to-discharge time was 45 days (29-64), transplant-to-discharge time was 14 days (12–19), ICU LOS post-transplant was 6 days (4–8), and total LOS was 58 days (42–76). Higher post-Impella creatinine was significantly associated with longer device-to-discharge time (β = 6.67, p = 0.004), longer transplant-to-discharge duration (β = 3.42 p = 0.003), longer ICU LOS (β = 2.19, p = 0.007), and longer total LOS (β = 7.24, p = 0.002) on univariate analysis. Post-impella creatinine remained significantly associated with device-to-discharge time in the multivariate model after adjusting for confounders (β = 6.33, p = 0.006). Importantly, this suggests that patients with lower post-Impella creatinine levels may experience shorter hospitalizations and faster recovery trajectories following transplant. Conclusions: Post-Impella creatinine is a significant predictor of prolonged hospitalization in patients supported with Impella 5.5 as a bridge to transplant. These findings emphasize the prognostic importance of early renal function assessment and may guide risk stratification and resource planning in advanced heart failure care.

Introduction: Pulmonary hypertension (PH) is a life-threatening, progressive disease with non-specific symptoms, often leading to delayed diagnosis. Early identification of World Health Organization Group 1 (Pulmonary Arterial Hypertension, PAH) and Group 4 (Chronic Thromboembolic Pulmonary Hypertension, CTEPH) is essential, as effective therapies can improve outcomes. Hypothesis: An electrocardiogram-based AI algorithm for PH detection (ECG-AI PH) may enable earlier diagnosis and reduce healthcare utilization, including hospitalizations and procedures. Methods: Retrospective analysis used a de-identified data platform of >7M clinical records from a multistate integrated health system. Adult precapillary PH patients (mPAP >20 mmHg, PVR >2 WU, PCWP ≤15 mmHg) were identified as PAH or CTEPH based on ICD codes, use of approved therapies, or surgical interventions (for CTEPH) between 2002 and 2024. ECG-AI PH was applied to ECGs within 30 days of diagnostic right heart catheterization, using a 5:1 randomly sampled PH-negative control cohort. Training set patients were excluded. Clinical event frequency was compared between two intervals: from first possible PH symptom (dyspnea, syncope, chest pain, fatigue, lower limb swelling) to diagnosis, and from symptom onset to first positive ECG-AI PH prediction. Results: A total of 1882 PAH and 359 CTEPH patients met inclusion criteria. Of these, 1340 PAH and 258 CTEPH patients had symptom codes prior to diagnosis. Both groups showed prolonged intervals from symptom onset to diagnosis, with multiple diagnostic procedures and hospitalizations (Figure). ECG-AI PH performance evaluation on the test set included 647 PAH and 152 CTEPH patients. ECG-AI PH achieved AUCs of 0.90 and 0.89 for PAH and CTEPH, sensitivities of 80.3% and 76.8%, and specificities of 83.4% and 82.4%. Among those tested, 576 PAH and 95 CTEPH patients had a positive ECG-AI PH prediction after symptom onset but before diagnosis. Compared to the current patient journey, the interval between initial symptoms and a positive output from ECG-AI PH was shorter and had fewer diagnostic tests/visits. Conclusion: ECG-AI PH demonstrated strong performance in detecting PAH and CTEPH. It may reduce diagnostic delays, support earlier PH-focused screening (e.g., echocardiograms evaluating the right heart), enable earlier intervention, and reduce pre-diagnosis healthcare burden, benefitting both patient outcomes and healthcare system efficiency.

Problem Statement: The prognostic value of troponin elevation in septic ICU patients without known history of cardiac disease remains unclear, particularly after accounting for overall illness severity. Background: Minor troponin rises are frequent during sepsis, yet clinicians still lack a clear cut-point that signals danger once cardiac disease is ruled out. We asked whether a modest increase in troponin-T predicts in-hospital death beyond global illness severity. Methods: We studied 1 221 adult first ICU stays labelled “sepsis” in the eICU Collaborative Research Database and removed any case with a cardiac admission diagnosis. Implausible or missing laboratory values were imputed by multiple imputation. Hospital mortality was modelled with logistic regression that included troponin (a continuous and a binary model with threshold > 0.04 ng/mL) together with age, sex, lactate, albumin, BUN, creatinine, intubation status, vasopressor use, dialysis requirement and APACHE-IV predicted mortality. A natural-spline model explored non-linear behavior. Findings were checked in a 1:1 propensity-matched cohort. Results: Overall mortality was 11.7%. Troponin exceeded 0.04 ng/mL in 38% of patients. After adjustment for APACHE-IV probability and other covariates, a troponin level > 0.04 ng/mL was associated with almost twice the odds of death (OR ≈ 1.9), whereas the continuous model suggested only a modest trend (OR ≈ 1.1 per ng/mL). The spline curve rose steeply between 0 and 0.10 ng/mL and flattened thereafter, pinpointing an inflection near 0.05 ng/mL. Matching on all measured confounders confirmed that high-troponin patients had about three-fold greater mortality (OR ≈ 2.8, 1.55-5.05; p<0.001), highlighting that even modest troponin elevation is an independent risk marker for death in septic ICU patients. A bedside heat-map combining troponin, albumin and need for intubation illustrated a simple gradient: risk climbs from 2 % in low-troponin, well-albuminised, non-intubated patients to nearly 7 % when troponin exceeds 0.10 ng/mL in intubated, hypo-albuminemic patients. Conclusions: Even modest troponin elevations (> 0.04 ng/mL) independently predict mortality in sepsis after rigorous adjustment and matching on APACHE-IV physiology, lactate, and organ-support variables. This biologic threshold supports incorporating troponin into bedside triage and future septic cardiomyopathy trials.

Introduction: PH increases RV afterload, often leading to RV systolic and diastolic failure. The metabolic mechanisms underlying RV dysfunction remain poorly understood and are largely unexplored across non-PAH forms of PH. Aims: We aimed to identify which metabolites and metabolic pathways associated with imaging measures of RV systolic function. Methods: We analyzed data from the multi-center PVDOMICS cohort, which includes echo, CMR, invasive hemodynamics, clinical phenotyping, and untargeted plasma metabolomics (via Metabolon). RV systolic function metrics selected as the outcome measures for this study were fractional area change (echo), global longitudinal strain (echo), and RVEF (CMR). Associations between non-xenobiotic, named metabolites and RV function measures were assessed using linear regression adjusted for age, sex, BMI, and PH group, with significance defined by FDR <0.05. Metabolite set enrichment analysis (MSEA) was performed to identify significantly enriched pathways (FDR <0.20). To complement MSEA, we conducted mean-aggregation analysis: we averaged metabolite concentrations within each pathway and tested associations with RV function using the same covariate adjustments (FDR <0.05). Results: We identified 979 participants with plasma metabolomics and at least one available outcome measure (317 Group 1 PH; 106 Group 2 PH; 140 Group 3 PH; 51 Group 4 PH; 26 Group 5 PH; 81 Healthy Controls; 258 Disease Comparators). Linear regression identified 170 metabolites from the 647 named metabolites significantly associated with all 3 RV metrics (Top 10 by average ranked p-value displayed in Image 1 ). MSEA revealed seven enriched pathways across all RV metrics: Androgenic Steroids, Pregnenolone Steroids, Progestin Steroids, Fatty Acid Metabolism (Acyl Choline), Histidine metabolism, Vitamin A metabolism, Gamma-glutamyl Amino Acid ( Image 2) . Mean aggregation analysis showed that higher concentrations of Androgenic/Pregnenolone Steroids and Vitamin A metabolites strongly associated with improved RV function, while higher levels of Fatty Acid Metabolism (Acyl Carnitine) and Acetylated Peptides associated with worse function ( Image 3 ). Conclusions: Using data from the multi-institutional PVDOMICS cohort, we provide a blueprint of metabolites and metabolic pathways associated with RV systolic function across the spectrum of PH. Steroid hormones as well as Vitamin A and fatty acid metabolites emerged as central to RV systolic function.

Introduction: Microaxial flow pumps reduce mortality in myocardial infarction (MI) related cardiogenic shock (CS). The Impella 5.5 generates increased flow to provide circulatory support, and optimization relies on mechanistic understanding of pressure-volume (PV) relationships. Aim: Using a porcine model of acute MI in tandem with biventricular (BiV) PV loop conductance catheters, this study aimed to understand the impact of Impella 5.5 on BiV hemodynamics in MI CS. Methods: In 6 Domestic Yorkshire Pigs, an Impella 5.5 (J&J MedTech, NJ) was inserted percutaneously under fluoroscopic guidance via carotid or aortic access. An angioplasty balloon catheter was advanced past the first diagonal and inflated to above nominal pressure with blood flow obstruction for 90 minutes. BiV PV loop conductance catheters (Sigma-M, CD Leycom, Hengelo, The Netherlands) were inserted via femoral venous access. The left ventricle (LV) PV loop catheter is positioned via transeptal puncture using intracardiac echocardiography. BiV PV loops are generated for each level of Impella support from P1 to P7. Results: With increasing Impella 5.5 support, LV PV loops shifted to the left and right ventricular (RV) loops to the right. Without statistical significance, LV end diastolic volume (EDV) decreased by a mean of 12.3 ± 10.7% from baseline and RV EDV increased by 32 ± 40%. Native LV function decreased with increasing Impella 5.5 support, demonstrated by a reduction in stroke volume (SV) (35±13 ml to 27±14 ml; p<0.001), cardiac output (CO) derived from SV&heart rate (2.0±0.5 ml/min to 1.7±0.7 ml/min; p<0.001), and ejection fraction (EF) (37±7% to 29±12%; p<0.001). Less consistent trends were noted in peak positive dP/dt and end-systolic pressure volume relationship. Native RV function increased with higher levels of Impella 5.5 support, noted by increasing SV (27±24 ml to 41±28 ml; p=0.004), CO (1.6±1.2 ml/min to 2.3±1.4 ml/min; p=0.001), and EF (42±16% to 45±9%; p=0.04). Arterial elastance and ventriculo-arterial coupling increased in the LV from baseline to P7 (2.2±1.4 mmHg/ml to 2.8±1.0 mmHg/ml and 1.8±0.5 to 3.2±1.9, respectively; p<0.001) and decreased in the RV (1.3±0.7 mmHg/ml to 0.9±0.7 mmHg/ml (p<0.001) and 2.1±2.2 to 1.3±0.6 (p=0.004)). Conclusions: Impella 5.5 speed modulation highlights significant ventricular interdependence in the setting of acute MI. PV loop derived parameters here visualized parameters that may be utilized to improve optimization of hemodynamic support in CS.

Background: Critical congenital heart disease (CCHD) screening algorithms based on pulse oximetry have up to 27% false positive rate at high altitudes (>2500 m) despite altitude-specific cutoff changes. We examined the added value of an adult-based AI model applied to phonocardiography (AI-PCG) in the digital stethoscope EKO Core 500 in these settings. Research Question: What is the diagnostic performance of AI-PCG model compared to pulse oximetry in detecting neonatal CCHD across different altitudes in Latin America? Methods: This observational, prospective, case-control study included newborns born at different altitudes from 0 to 4380 meters in Peru, Mexico, Colombia and Bolivia. All underwent preductal and postductal oximetry at least 18 hours after birth, electrocardiography and PCG with the digital stethoscope. All CCHD cases were confirmed by echocardiography. Non-CCHD cases were defined by echocardiography or clinically if they were alive for 1 month and had 1) negative pulse oximetry, 2) no hospitalization due to cardiac or pulmonary causes and 3) no cyanosis or pneumonia. Those with abnormal pulse oximetry, genetic syndromes or murmur detection underwent echocardiography. Diagnostic performance metrics [area under the receiving operating characteristic curve (AUROC), sensitivity, specificity and false positive rate] were evaluated per modality. Results: A total of 1152 newborns were enrolled, 725 at <2500 m [13 (1.8%) with CCHD] and 427 at >2500 m [6 (1.4%) with CCHD]. Out of 19 CCHD cases, 17 had positive pulse oximetry and 9 had a positive AI-PCG model. One newborn with severe coarctation of the aorta and atrial septal defect had negative pulse oximetry and AI-PCG model. Pulse oximetry showed superior AUROC (0.932 vs 0.664), sensitivity (89.5% vs 47.4%), specificity (97% vs 85.5%) and lower false positive rate (3% vs 14.5%) compared to the AI-PCG model across altitudes. Diagnostic accuracy varied with altitude (Figure): at <2500 m, pulse oximetry showed higher AUROC (0.999 vs 0.612) and lower false positive rate (0.1% vs 16%) than AI-PCG model, but at >2500 m, pulse oximetry had similar AUROC (0.794 vs 0.774) and lower false positive rate (7.8% vs 11.9%) than the AI-PCG model. Conclusion: Pulse oximetry has superior diagnostic performance than an adult-based AI-PCG model when screening for neonatal CCHD at <2500 m, but similar performance is found >2500 m.