The Journal of Heart and Lung Transplantation

Background: Primary graft dysfunction (PGD) remains one of the leading causes of early mortality after pediatric heart transplant (HT). While neurodevelopmental impacts of congenital heart disease (CHD) are well-characterized, the effect of PGD on long-term neurodevelopmental outcomes in pediatric HT recipients remains unknown. We sought to determine the association between PGD and neurodevelopmental outcomes in this population. Methods: We performed a retrospective cohort study using the United Network for Organ Sharing (UNOS) database. All pediatric (age <18 years) isolated heart transplant recipients from 2010-2025 were included. The most recent pre- and post-transplant neurodevelopmental outcomes including cognitive delay, motor development, academic progress, and function status (stratified by age) were compared between PGD (n=434) and non- PGD groups (n=6956). Results: PGD patients had significantly worse pre-transplant functional status and motor development. Post-transplant, PGD was associated with worse motor development (18.8% vs. 13.0% definite motor delay; p=0.01) and functional status in younger children (39.5% vs. 57.8% able to keep up with peers; p<0.001). Post-transplant stroke occurred 3.5 times more frequently in PGD patients (11.5% vs. 3.3%; p<0.001). Cognitive development (p=0.94) and academic progress (p=0.096) did not differ significantly. Thirty-day (7.8% vs. 1.9%) and 1-year mortality (20.3% vs. 6.4%) were significantly higher in PGD patients (both p<0.001). Conclusions: This is the first study to characterize neurodevelopmental outcomes in pediatric patients undergoing HT with PGD. PGD is associated with significantly worse motor development and functional status independent of pre-transplant baseline. There is a 3.5-fold higher stroke rate providing a plausible neurological mechanism. The findings support targeted developmental surveillance recommendations and early intervention for this high-risk population.

BackgroundPediatric dilated cardiomyopathy (DCM) is a rare, progressive heart disease with variable outcomes that range from recovery to heart transplantation. To date, there are no prognostic biomarkers for children with DCM. Identifying circulating biomarkers that are associated with clinical outcomes is critical for personalized management. MethodsmiRNAs were identified by RNA-seq, whereas proteins were identified by SomaScan(R). Machine learning methodologies were used to explore the predictive ability of circulating factors identified from serum samples collected at the time of presentation with acute heart failure. ResultsThirty patients experienced poor outcomes (cardiac transplantation, mechanical circulatory support, or death) and 19 patients recovered left ventricular function. Distinct miRNA and protein signatures differentiated outcomes groups. Top candidate proteins (COL2A1, CXCL12, and ADGRF5) and miRNAs (miR-874-3p, miR-335-3p, miR-323a-3p) demonstrated strong discriminatory performance within the study cohort (recovered vs poor outcomes; Area Under the Curve of 0.92). Ingenuity Pathway Analysis implicates cardiac remodeling, fibrosis, and inflammatory signaling as central pathways differentiating patient outcomes. ConclusionsCirculating miRNA and protein signatures at presentation identify a circulating molecular signature associated with divergent clinical trajectories in pediatric DCM. These findings support the potential utility of multi-omic biomarkers for early risk stratification and provide insight into mechanisms underlying divergent outcomes. CLINICAL PERSPECTIVEWhat Is New? O_LICirculating miRNA and protein profiles measured at presentation distinguish children with pediatric DCM who recover from those who progress to advanced heart failure. C_LIO_LIA combined multi-omic biomarker demonstrated strong discriminatory performance in this cohort (AUC 0.92). C_LIO_LIPathway analysis implicates extracellular matrix remodeling, fibrosis, and inflammatory signaling in children with adverse clinical trajectories. C_LI What Are the Clinical Implications? O_LISerum-based molecular biomarkers may enable earlier risk stratification in children presenting with dilated cardiomyopathy. C_LIO_LIMulti-omic integration may improve identification of pediatric patients at risk for transplantation, mechanical circulatory support, or death. C_LIO_LIThese findings support further validation of circulating biomarker panels to guide personalized management in this rare disease. C_LI RESEARCH PERSPECTIVEWhat New Question Does This Study Raise? O_LICan integrated circulating miRNA-protein signatures identify biologically distinct trajectories of recovery versus progression in children with dilated cardiomyopathy? C_LIO_LIDo circulating molecular profiles reflect underlying disease mechanisms that determine divergent clinical outcomes in pediatric DCM? C_LI What Question Should Be Addressed Next? O_LIDo the pathways identified by integrated miRNA-protein analysis (fibrosis, remodeling, and inflammation) play causal roles in determining recovery versus progression? C_LIO_LICan multi-omic biomarkers be incorporated into prospective studies to improve early risk stratification and guide clinical management? C_LI

Background and Aims: Acute myocarditis (AM) is a T cell-mediated myocardial disease with clinical manifestations ranging from mild chest pain to cardiogenic shock. Reliable biomarkers to stratify patients and guide therapy are currently lacking. In particular, the extent of the dysregulation of inflammatory pathways, and the impact on myocardial dysfunction, remain elusive. Methods: Serum analyses were performed in prospectively recruited AM patients (n = 103) from two independent cohorts. Multimodal data integration combining profiling of cytokine and chemokine dysregulation with clinical biomarkers was used to define clinical phenotypes with distinct inflammatory signatures. Machine-learning and regression models were applied to determine biomarkers that indicate clinical severity. Results: Immuno-proteomic profiling revealed conserved inflammatory patterns across AM cohorts, dominated by T cell-related cytokines and chemokines. In addition, AM patients showed dysregulation of fibroblast-derived cytokines, including hepatocyte growth factor (HGF), bone morphogenic protein 4 (BMP4) and the BMP4 inhibitors Gremlin-1 (GREM1) and Gremlin-2 (GREM2). Data integration and unsupervised clustering revealed two immuno-clinical phenotypes, linking T cell activation and fibroblast dysregulation to disease severity. Machine learning-based analysis identified CXCL10, GREM2 and LVEF as critical parameters for stratifying disease severity. Conclusions: These findings highlight a systemic T cell activation signature as diagnostic hallmark of AM. In addition, dysregulation of fibroblast-derived tissue cytokines serves as an indicator for distinct immuno-clinical phenotypes in myocardial inflammatory disease. Thus, the clinically relevant link between T cell-driven immune activation, myocardial inflammation and fibroblast-driven remodelling provides a versatile set of parameters to identify severe manifestations of AM.

Background: Cardiogenic shock (CS) remains associated with high short-term mortality despite contemporary advances in care. The association between institutional cardiac capability and outcomes?particularly among transferred patients and after accounting for clinical instability?remains incompletely defined. Objectives: To evaluate the association between hierarchical hospital cardiac capability and in-hospital mortality using a latent measure of acute physiologic severity. Methods: Using the National Inpatient Sample (2016?2022), hospitals were classified into five hierarchical tiers ranging from non-PCI (Tier 1) to heart transplant/durable LVAD centers (Tier 5). Generalized structural equation modeling (GSEM) assessed the relationship between hospital tier and mortality. A latent "Acute Severity" construct?comprising cardiac arrest, acute kidney and liver injury, and mechanical ventilation?was incorporated to model the effects of clinical instability Results: Among an estimated 1,177,180 CS hospitalizations, most occurred at cardiac surgical and transplant/LVAD centers. Crude mortality declined stepwise from non-PCI hospitals (64.5%) to transplant/LVAD centers (36.5%). After adjustment, higher hospital tier was independently associated with lower mortality (Tier 2 OR 0.43 [95% CI 0.38?0.48]; Tier 3 OR 0.37 [0.32?0.43]; Tier 4 OR 0.33 [0.30?0.38]; Tier 5 OR 0.35 [0.31?0.40]). Although transfer-in status was associated with increased mortality (OR 1.39 [1.33?1.46]), this association was attenuated at cardiac surgical and transplant/LVAD centers, consistent with a mitigation of transfer associated risk. Conclusions: Higher hospital cardiac capability is independently associated with lower mortality in CS. Advanced centers are associated with mitigation transfer-associated risk, supporting regionalized hub-and-spoke systems with early referral to high-capability centers.

Severe forms of inflammation-induced acute and chronic myocarditis have a poor prognosis. Promising therapeutic efforts focused on monoclonal antibodies (mAbs) inhibiting inflammation-inducing molecules. However, most mAbs target only one or a limited number of such molecules. Since inflammation involves multiple redundant pathways, we postulated that an mAb inhibiting multiple inflammatory pathways would be a potent therapeutic agent. We initially tested the commercially available anti-natural killer (NK) cell mAb (anti-NK1.1), which binds a receptor expressed on NK cells and depletes them. Since NK cells are key cellular orchestrators of inflammation, by reducing their number, we aimed to inhibit multiple inflammatory pathways. Our initial studies demonstrated that administration of this antibody significantly improved myocardial outcomes in mouse models of acute myocardial infarction and of heart failure. Since NK1.1 is not expressed in human cells, we built on these promising preclinical results by developing a novel mAb targeting CD160 on human NK cells for evaluation as an immunosuppressive therapy. We found that the anti-CD160 mAb depletes both murine and human NK cells. We also found that, while CD160+ cells were largely present in the NK population, they also occurred among CD8+ and {gamma}/{delta} T cell subsets in human cells. Anti-CD160 therapy entirely prevented the deterioration of the myocardial function of mice with autoimmune-induced acute myocarditis. This outcome suggests our novel approach for inhibiting multiple inflammatory pathways may provide a potent strategy for improving outcomes of inflammation-driven myocarditis, as well as of other inflammation-driven diseases. Key PointsO_ST_ABSQuestionC_ST_ABSCan the depletion of CD160+ cells prevent autoimmune-induced myocarditis? FindingsIn this study we found that CD160 is expressed by mouse and human natural killer cells and other subtypes of cytotoxic T cells, and that a monoclonal antibody targeting CD160 depletes NK cells. In a preclinical model of experimental autoimmune myocarditis, administration of the anti-CD160 monoclonal antibody prevented myocardial dysfunction and systemic inflammation. MeaningOur results are compatible with the hypothesis that early autoimmune-induced myocardial dysfunction is promoted by CD160+ cells, which elevate inflammation-induced circulating factors (or factors released by tissue-resident cytotoxic immune cells) that cause myocardial dysfunction in the absence of myocardial necrosis or fibrosis, and further, that targeting CD160+cells with a mAb that depletes NK cells (and probably CD160 expressing cytotoxic T cells) entirely prevents the deterioration of myocardial function in such mice. This outcome suggests our novel approach for inhibiting multiple inflammatory pathways may provide a potent strategy for improving outcomes of inflammation-driven myocarditis, as well as of other inflammation-driven diseases.

Background Exercise capacity varies among individuals with a Fontan circulation. Percent predicted peak oxygen consumption (%pVO2) may be influenced by ventricular morphology, Fontan subtype, and conduit characteristics, but data explaining variability in exercise capacity are limited. This study examined whether anatomical and surgical factors are associated with %pVO2 later in life. Methods Participants enrolled in the multicenter Single Ventricle Outcomes Network (SV-ONE) database who had cardiopulmonary exercise testing (CPET) data were included. Published reference equations were used to estimate %pVO2. Multivariable regression models evaluated associations between anthropometric, anatomical (diagnosis and dominant ventricle), and surgical (Fontan subtype, conduit size, and surgical era) factors and %pVO2. Restricted spline analyses assessed nonlinearity. Results 561 individuals with a Fontan circulation were included in the analysis; age 20 {+/-} 8 years, 54% male, mean %pVO2 was 63 {+/-} 16%. Sex and exercise modality were the strongest predictors of %pVO2, with females being 12% higher than males and treadmill 4.6% higher than a cycle. Age at CPET was a predictor of exercise capacity with %pVO2 decreasing by 0.8% per year. Ventricular morphology, diagnosis, and Fontan subtype did not have a statistical association with the primary outcome. In models restricted to patients with an extracardiac conduit (n = 330), conduit diameter and area were not associated with %pVO2, even after indexing to body surface area. Univariable nonlinear spline analyses suggested an optimal conduit size of 18 mm for %pVO2, but this was not significant after body size adjustments. Conclusion In this large multicenter cohort, surgical and anatomical features were not as important as sex, age, and body size as determinants of exercise performance in patients with a Fontan circulation. Reduced exercise capacity in this population appears to reflect progressive pathophysiological changes of the Fontan circulation rather than specific characteristics such as conduit size, ventricular morphology, or anatomy.

Abstract Background: ST-elevation myocardial infarction (STEMI) is reported to be a leading cause of mortality worldwide. While cardiac troponins are the gold standard for myocardial injury detection but creatine kinase-MB (CK-MB) and total creatine phosphokinase (CPK) retain prognostic use in resource-limited settings. Objective: To evaluate the prognostic significance of admission CK-MB and CPK levels in STEMI patients and to assess their association with hematological parameters for integrated risk stratification. Methods: This cross-sectional study enrolled 15 consecutive STEMI patients from the Punjab Institute of Cardiology, Lahore, during January 2024. Comprehensive laboratory analysis including cardiac biomarkers (CK-MB, CPK, troponin-I, LDH), complete blood count, renal function, serum electrolytes, and metabolic parameters, was performed on admission. Pearson correlation and comparative statistical analyses were also conducted to assess the relationships between cardiac biomarkers and hematological indices. Results: The cohort includes 15 patients (mean age 50.1 +/- 12.2 years; 73.3% male). Cardiac biomarker elevation was prevalent: CK-MB was elevated in 12/15 (80%), CPK was elevated in 12/15 (80%), with concordant elevation in 11/15 (73.3%), which indicates extensive myocardial necrosis. Troponin-I showed the highest elevation rate at 13/15 (86.7%). Hematological abnormalities included anemia (60%), WBC elevation (53.3%), and RBC reduction (40%). Random glucose averaged 150.80 +/- 63.55 mg/dL, with 66.7% highlighted the hyperglycemia. Remarkably, electrolyte balance was preserved in all of the patients (0% sodium, potassium, and bicarbonate abnormalities), indicating maintained homeostasis. Pearson correlation analysis revealed a significant correlation between CK-MB and CPK (r = 0.615, p = 0.0126), while correlations between cardiac biomarkers and hematological parameters were weak (p > 0.05). Risk stratification identified 53.3% of patients as high-risk who required intensive management. Conclusions: CK-MB and CPK demonstrate significant concordance and retain prognostic value in STEMI patients, particularly in resource-limited settings where troponin access may be constrained. While troponin-I remains the most sensitive biomarker, combined assessment of conventional cardiac enzymes supports reliable evaluation of myocardial injury. Hematological parameters reflect systemic response but show limited correlation with cardiac biomarkers.

Objectives: Clinical prediction models estimate the risk of a future outcome in patients. Such models are often externally validated using independent datasets; however, even when a model has been rigorously validated in a new setting and patient population, its performance across other clinical settings remains unclear. Therefore, we systematically evaluated model performance and clinical utility across diverse patient populations to quantify the limits of transportability. Methods: Using liver transplantation as an example, we used the UK donation-after-circulatory-death (DCD) risk score and descriptive statistics from Swiss DCD liver transplant populations to simulate realistic target populations with varying donor and recipient characteristics. The risk score's ability to predict one-year graft failure was evaluated using calibration intercept, calibration slope, area under the receiver operating characteristic (ROC) curve, and net benefit. Results: The UK DCD Risk Score's performance depended heavily on the simulated population characteristics. While the score performed adequately in settings similar to those where it was derived, it was not satisfactory in others. Discussion: The study showed, using a risk score in liver transplantation as an example, that the application of a prediction model can be limited in certain external populations when they differ, and that its transportability in new settings is not guaranteed. Conclusion: This study highlights the importance of external validation of clinical prediction models to determine transportability to various target populations. Their application requires careful consideration and potential model re-estimation.

Aims: Responses to remote pulmonary artery pressure data vary across programs. We evaluated SMART-HF, a structured pulmonary artery diastolic pressure (PAD)-guided workflow, in a community heart failure cohort. Methods: We retrospectively analysed adults with heart failure and an implanted pulmonary artery pressure sensor managed with SMART-HF. Pulmonary artery diastolic pressure (PAD) was calculated from prespecified 14-day windows at baseline, 90 days, and 6 months. Two hemodynamic management performance indices (HMPI) were prespecified: the 6-Month Delta HMPI (PAD reduction >2 mmHg from baseline) and the 90-Day Target HMPI (PAD [&le;]20 mmHg at 90 days). Exploratory analyses evaluated patients with baseline PAD >20 mmHg. Results: Of 37 patients, 36 had paired 90-day and 29 had paired 6-month windows. Mean PAD decreased from 18.3 +/- 7.0 to 16.1 +/- 6.3 mmHg at 90 days and from 18.8 +/- 6.8 to 15.5 +/- 5.8 mmHg at 6 months (both P < 0.001). The 90-Day Target HMPI was achieved in 26/36 (72.2%) and the 6-Month Delta HMPI in 19/29 (65.5%) [95% CI 45.7-82.1]. In the exploratory subgroup (baseline PAD >20 mmHg), mean PAD changes were -2.9 +/- 3.6 mmHg at 90 days (n = 19; P = 0.002) and -4.9 +/- 4.9 mmHg at 6 months (n = 15; P = 0.002). Conclusions: SMART-HF was associated with improved ambulatory pulmonary artery diastolic pressure control at 90 days and 6 months. Exploratory subgroup findings support further evaluation in patients with elevated baseline pulmonary artery diastolic pressure.

The intestinal microbiome influences immune recovery and long-term outcomes after allogeneic hematopoietic stem cell transplantation (allo-SCT). While reduced bacterial diversity and depletion of immunomodulatory microbial metabolites during peri-engraftment have been linked to acute graft-versus-host disease (aGvHD) and mortality, it remains unclear whether microbiome recovery after engraftment and immune reconstitution is better reflected by bacterial diversity or by microbial metabolic output. We aimed to define microbiome recovery in the late post-transplant period and test whether a metabolite-based biomarker improves the prediction of clinical outcomes, including overall survival (OS) and chronic (c) GvHD. In this two-center longitudinal observational study, serial stool samples were collected from pre-transplant baseline to day +100 after allo-SCT in a discovery cohort (n = 20, Technical University Munich University Hospital (TUM)) and an independent validation cohort (n = 100, University Hospital Regensburg (UKR)). Gut microbiome composition was assessed by 16S rRNA gene amplicon sequencing, with metagenomic profiling in selected patients, and stool metabolites were quantified using targeted mass spectrometry. Patients were classified as RECOVERY or NO RECOVERY based on changes in bacterial richness between baseline and the post-transplant period. To capture microbial metabolic output, the previously established Immune-Modulatory Metabolite Risk Index (IMM-RI), comprising butyric, propionic, and isovaleric acids, desaminotyrosine and indole-3-carboxaldehyde, was adapted to the late post-transplant period (IMM-RI post-TX). Bacterial alpha diversity frequently improved by day +100; however, this did not consistently indicate restoration of baseline community structure and was not paralleled by recovery of stool metabolite profiles. Accordingly, RECOVERY status showed a limited association with survival or transplant-related mortality (TRM). In contrast, IMM-RI post-TX low-risk identified patients with preserved butyrate-associated biosynthetic capacity and was significantly associated with improved OS in both cohorts (UKR: HR 0.2052, 95% CI 0.07703 - 0.5466, p < 0.0001). In the validation cohort, IMM-RI post-TX low-risk was significantly associated with reduced relapse-related mortality. Interestingly, stool butyric-, propionic and valeric acid concentrations were increased in cGvHD of the skin, indicating context-dependent metabolite effects. These findings suggest that metabolite profiling outperforms bacterial diversity for predicting outcomes after allo-SCT and support microbial metabolites as promising biomarkers for risk stratification and actionable candidates for precision microbiome interventions after allo-SCT.

Background Cardiac MRI (CMR) is often utilized for patients with suspected cardiac amyloidosis (CA). However, data are lacking for use in patients with advanced renal dysfunction (ARD) (GFR<30 mL/min/1.73 m2, dialysis dependent, or renal transplant). This study evaluates the utility of CMR for diagnosis of CA in this population. Methods Patients with ARD who underwent CMR in a 3T field for suspicion of CA between 2010 and 2024 at our institution were included. A diagnosis of CA was made if any of the following were present a)?PYP scintigraphy grade ? 2, b) positive endomyocardial biopsy, or c) positive extracardiac biopsy with clinical features of CA. Two CMR-trained physicians independently assessed T1 relaxation time, ECV, Ti scout, LGE, and overall likelihood of CA. Results Out of the 65 patients included 14 (22%) had a diagnosis of CA. Although T1 time [1352 (1276-1428) ms] and ECV (40.3% +/- 9.1%) were elevated across the cohort, they were significantly higher in patients with CA (p<0.001 for both). Both ECV and T1 time reliably predicted CA (AUC of 0.87 and 0.88 respectively). ECV of ?45% had 75% sensitivity and 80% specificity for CA. A T1 time ? 1390 ms had 75% sensitivity and 85% specificity for CA. LGE was prevalent and was seen in 86% and 84% patients with and without CA respectively. Of the 31 patients deemed to be unlikely CA by a CMR reader, 6% had CA. However, of the 34 patients read as possible/likely CA, only 35% had confirmed CA. Conclusions In this understudied population of ARD, CMR parametric mapping exhibits high negative predictive value (NPV) for CA and improved positive predictive value (PPV) when higher cutoffs are used for T1 time and ECV. CMR reader overall impression exhibits high NPV but low PPV for CA.

Aims: Dynamic left ventricular outflow tract obstruction (LVOTO) is a hemodynamically significant complication following transcatheter aortic valve replacement (TAVR) that remains difficult to predict with conventional transthoracic echocardiography (TTE). We examined whether a deep learning (DL) model developed for LVOTO detection in hypertrophic cardiomyopathy (HCM) could predict post-TAVR LVOTO from pre-TAVR TTE in patients with severe aortic stenosis (AS). Methods and Results: In this retrospective study of 302 consecutive patients undergoing TAVR for severe AS, a pre-trained DL model was applied to pre-TAVR TTE to generate a patient-level DL index of LVOTO (DLi-LVOTO; range 0-100). Post-TAVR LVOTO was defined as a peak pressure gradient [&ge;]30 mmHg on follow-up TTE. Logistic regression and receiver operating characteristic analyses assessed the association and discriminative performance of DLi-LVOTO. Pre-TAVR LVOTO was present in 32 patients (10.6%) and post-TAVR LVOTO in 35 (11.6%). Follow-up TTE was performed at a median of 47 days (IQR 37-63) after TAVR, with the majority of TTE (216 of 302, 71.5%) performed within 2 months. DLi-LVOTO was significantly higher in patients with LVOTO at both pre- and post-TAVR TTE (all p<0.001). In multivariable analysis, DLi-LVOTO remained independently associated with post-TAVR LVOTO even after adjusting for conventional TTE parameters and pre-TAVR LVOTO (adjusted OR 1.29, 95% CI 1.06-1.56 per 10-score increase, p=0.011), with an AUROC of 0.78 (95% CI 0.72-0.85). Among patients without pre-TAVR LVOTO, DLi-LVOTO retained independent predictive value (adjusted OR 1.56, 95% CI 1.19-2.06, p=0.001; AUROC 0.84, 95% CI 0.77-0.91). Conclusion: A DL model originally trained in HCM patients independently predicts post-TAVR LVOTO from pre-TAVR TTE, including in patients without pre-existing LVOTO, suggesting it captures hemodynamic features beyond conventional echocardiographic assessment.

Rationale: Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome with substantial unmet diagnostic and therapeutic needs. Circulating lipid metabolism is increasingly implicated in HFpEF pathophysiology but has not been systematically leveraged for molecular stratification. Objective: To determine whether plasma lipidomics can identify molecular phenogroups of HFpEF associated with distinct clinical characteristics and outcomes. Methods and Results: Untargeted plasma lipidomics was performed in non-HF subjects and HFpEF patients from a primary Belgian cohort and an independent Canadian cohort (n=177 in each cohort). In the Belgian cohort, 235 unique lipids spanning 19 subclasses were annotated, including 96 significantly associated with HFpEF (q<0.02). Unsupervised analyses revealed marked lipidomic heterogeneity, with a distinct HFpEF subgroup separable from non-HF subjects. Hierarchical clustering identified three phenogroups with divergent lipid profiles and clinical features. One phenogroup exhibited severe atrial dysfunction, congestion-related biomarkers, elevated indices of cardiac and liver fibrosis, and markedly reduced survival, a second was characterized by prominent metabolic syndrome features, and a third by preserved renal function. Cross-cohort comparison using a supervised classifier trained on 158 shared lipids confirmed analogous lower-risk phenogroups in the Canadian cohort, while the high-risk phenotype was underrepresented. A signature of 10 lipids across six subclasses, including long-chain acylcarnitines, ether phosphatidylcholines, and oxidized sphingomyelins, discriminated the high-risk group and correlated with markers of disease severity. Conclusion: Our findings demonstrate that HFpEF comprises metabolically distinct patient subgroups across cohorts, revealing specific lipidomic dysfunctions that deepen our understanding of HFpEF heterogeneity and underlying pathophysiology.

Abstract Background: Despite widespread adoption of contemporary guideline-directed medical therapy (GDMT), patients with heart failure with reduced ejection fraction (HFrEF) continue to experience substantial residual morbidity and mortality. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have demonstrated cardiometabolic benefits in diabetes and obesity, but their role in HFrEF remains uncertain. Objectives: To evaluate whether the addition of GLP-1RAs to optimized GDMT is associated with improved clinical outcomes in patients with HFrEF (NYHA class II-IV). Methods: We conducted a retrospective, multicenter cohort study using the TriNetX Research Network. Adults ([&ge;]18 years) with HFrEF (LVEF [&le;]40%) receiving GDMT between January 2020 and October 2024 were included. Patients treated with GLP-1RAs were compared with those on GDMT alone. After 1:1 propensity score matching, 1,518 patients were included in each cohort. Outcomes over 2 years included all-cause mortality, major adverse cardiovascular events (MACE), critical care utilization, and acute kidney failure. Time-to-event analyses were performed using Kaplan-Meier methods and Cox proportional hazards models. Results: In the matched cohort (mean age [~]63 years, [~]33% female), GLP-1RA use was associated with significantly lower all-cause mortality compared with GDMT alone (12.8% vs 23.8%; hazard ratio [HR] 0.48; 95% CI 0.40-0.57; p<0.001), corresponding to an absolute risk reduction of 11.0%. MACE was also reduced (35.8% vs 47.4%; HR 0.64; 95% CI 0.58-0.72; p<0.001). Additionally, GLP-1RA therapy was associated with lower critical care utilization (18.4% vs 28.9%; HR 0.55; 95% CI 0.47-0.64; p<0.001) and reduced acute kidney failure (29.2% vs 37.3%; HR 0.67; 95% CI 0.59-0.76; p<0.001). Rates of pancreatitis and substance-related disorders were low and not significantly different between groups. Conclusions: Among patients with HFrEF receiving contemporary GDMT, adjunctive GLP-1RA therapy was associated with significant reductions in mortality, cardiovascular events, and healthcare utilization. These findings support the potential role of GLP-1RAs as a novel, mechanism-complementary therapy in HFrEF. Prospective randomized trials are needed to confirm these observations and determine whether GLP-1RAs should be incorporated as a fifth pillar of GDMT.

Background: Transthyretin cardiomyopathy (ATTR-CM) is a progressive, potentially fatal disease requiring accurate risk stratification. Echocardiography is the first-line imaging modality, with AI-based tools increasingly applied for automated analysis, yet their prognostic value remains unknown. Objectives: To examine the prognostic value of AI-derived echocardiographic measurements and their incremental value beyond biomarker staging in ATTR-CM. Methods: This retrospective study included patients from two ATTR-CM registries. Baseline echocardiograms were analyzed using the fully automated AI-based software Us2.ai. Prognostic performance was assessed by Kaplan-Meier analysis, Cox regression, and ROC curves. A two-parameter echocardiographic staging system combining left ventricular (LV) global longitudinal strain (GLS) and right ventricular (RV) fractional area change (FAC) stratified patients into low (both normal), intermediate (one abnormal), and high risk (both abnormal). Results: Among 347 patients (91% male, median age 78 years), 141 experienced all-cause death or heart failure hospitalization over a median follow-up of 2.4 years. In multivariable analysis, AI-derived LV-GLS (HR 1.13 [1.03-1.25], p=0.011) and RV FAC (HR 0.96 [0.93-0.99], p=0.014) were independent outcome predictors. Echo staging stratified risk into groups with 3-fold (95% CI 1.70-5.91) and 6-fold (95% CI 3.22-10.30) increased hazard compared to low risk (p<0.001), with incremental prognostic value beyond National Amyloidosis Centre (NAC) staging and age (chi-square from 53 to 80; p<0.001). AI and human measurements showed comparable 1-year predictive performance (all p>0.05). Conclusion: AI-derived echocardiographic measurements demonstrate independent and incremental prognostic value beyond biomarker-based NAC staging in ATTR-CM, comparable to human measurements, supporting their integration into clinical risk stratification.

Background: Coronary artery bypass grafting (CABG) to physiologically non-significant coronary artery stenosis may result in graft failure due to competitive native flow. We evaluated whether an instantaneous wave-free ratio (iFR)-guided revascularization strategy improves graft patency and clinical outcomes compared to conventional angiography-guided CABG. Methods: In this prospective, randomized, single-blinded trial, patients with multivessel disease and at least one angiographically intermediate stenosis (50%-75%) were randomized to either CABG guided by angiography alone or angiography supplemented with iFR assessment groups. The primary endpoint was graft patency (occlusion or hypoperfusion of the graft) evaluated by coronary computed tomography angiography (CCTA) at 2, 12, and 36 months. Results: At 36 months, 78% of the patients completed follow-up. Left internal mammary artery (LIMA)-to-left anterior descending (LAD) artery graft patency was significantly higher in the iFR-guided group than in the angiography-guided group (80.5% vs. 56.8%; absolute risk difference, 23.7% [95% CI, 3.7%-43.8%]; RR, 1.42 [95% CI, 1.03-1.95]; P = 0.03). Saphenous vein graft patency also improved with iFR guidance (90.2% vs. 70.3%; P = 0.046). Major adverse cardiac and cerebrovascular events (MACCE) were similar between groups (28% vs. 20%; RR, 1.40 [95% CI, 0.69-2.85]; P = 0.48). Conclusions: iFR-guided CABG advocates significantly improved mid-term graft patency compared with angiography-guided CABG by optimizing surgical target selection and reducing competitive flow.

Background: Each year around 4,500 people in the UK receive an organ transplant. These surgeries can be life changing and life extending for patients but are also associated with significant costs for the health service. However, by reducing the need for other expensive interventions involved in non-transplant care for organ failure, such as dialysis, some of these costs may be recovered. Methods: We assessed the lifetime costs and benefits associated with transplantation focussing on deceased donor adult transplants for kidneys, livers, hearts, and lungs. We incorporated costs of organ retrieval, surgery, post-transplant secondary care, and medications, as well as impacts on quality and duration of life. These were compared to the cost of managing patients with end-stage organ failure for whom no transplant occurs. Results: Kidney transplants were found to be cost saving with lifetime costs approximately 220,000 GBP lower than alternative treatment. Heart transplants and liver transplants were found to be more cost-effective than thresholds used by NICE for new medicines at approximately 17,000 GBP to 18,000 GBP per quality adjusted life year gained. Lung transplants were the least cost-effective organ transplant with a cost per quality adjusted life year gained of over 50,000 GBP. Conclusions: Although transplants can be costly, not providing a transplant to a patient who needs one also brings significant costs. Kidney transplants can save the health system money by reducing the need for dialysis. Increasing the number of kidney's available for transplant could save the NHS money whilst saving and improving lives.

BACKGROUND: Guidelines recommend aortic valve replacement (AVR) in patients with severe aortic regurgitation (AR) based on progressive changes in left ventricular (LV) function or size. We aimed to reassess the clinical relevance of current guideline recommendations pertaining to traditional echocardiographic measurements in routine practice. METHODS: Retrospective analysis of patients with severe AR who underwent serial echocardiographic follow-up over at least 18 months. The composite outcome was symptom-driven AVR, acute heart failure hospitalization, or death. We used a joint modelling approach to handle within-subject correlation and censoring. RESULTS: The cohort consisted of 140 patients, with a median follow?up of 93 months (interquartile range 58?130). LV end-systolic (LVESD) and fractional shortening (FS) showed a small but statistically significant longitudinal trend, while LVEDD did not. Changes in all three parameters in parallel joint models adjusted for age and gender were consistently associated with increased risk of the composite event. Each 1?mm increase in LVESD and LVEDD was associated with a 6% and 5% increase in risk, respectively; each 1% decrease in FS corresponded to a 12% increase in risk. Only 8 (5.7%) of patients were predicted to exceed the guideline-recommended LVEDD threshold of 65 mm over 10 years. Age at onset was also a significant risk factor, with each decade increasing risk by 65% for each of the three parallel joint models. CONCLUSIONS: LV parameters show modest changes over time, despite holding strong prognostic value in patients with severe AR. LVEDD, while associated with overall risk, does not predictably or significantly dilate over time in most patients. AVR decisions should be based on comprehensive clinical and volumetric assessment rather than waiting for simple linear progression to guideline cutoffs.

BackgroundPrimary mitral regurgitation resulting from mitral valve prolapse can lead to life-threatening complications, including arrhythmias, heart failure, and sudden cardiac death. Mitral valve prolapse is classically associated with myxomatous mitral valve degeneration, characterized by leaflet thickening, extracellular matrix disorganization, and progressive structural remodeling. Valvular interstitial cells, the predominant stromal population within the valve, maintain extracellular matrix homeostasis; however, their molecular heterogeneity, and state-specific contributions to disease pathogenesis remain incompletely defined. MethodsUsing a fibrillin-1 deficient mouse model and human tissue specimens we integrated single-cell RNA sequencing with spatial transcriptomic profiling to construct a comprehensive atlas of cellular composition and extracellular matrix organization across normal mitral valves, sporadic mitral valve prolapse, and Marfan syndrome-associated mitral valve prolapse. ResultsAnalyses revealed spatially organized cellular niches and substantial heterogeneity within the valvular interstitial cell population. Across murine and human datasets, we identified a conserved activated valvular interstitial cell population enriched for profibrotic extracellular matrix remodeling programs and preferentially localized to mechanically vulnerable leaflet tip regions. This population exhibited coordinated upregulation of collagen- and matrix-associated genes, metabolic signatures consistent with enhanced mitochondrial activity, and transcriptional features suggesting fibro-inflammatory signaling. ConclusionsWe identified a transcriptionally and spatially distinct activated valvular interstitial cell state conserved across species and disease etiologies that is strongly implicated in fibrotic remodeling during myxomatous mitral valve degeneration and provides a candidate therapeutic target.

Background | Angina with nonobstructive coronary arteries (ANOCA) is a heterogeneous condition encompassing distinct endotypes representing different underlying pathophysiological mechanisms. Endothelial dysfunction is considered a central hallmark of ANOCA. However, studying patient-derived endothelial cells (ECs) remains challenging due to the limited availability of disease-specific endothelial samples. We therefore aimed to assess the feasibility of isolating and culturing ECs from catheterization material obtained during routine coronary function testing in ANOCA patients. Methods | Catheterization material was collected from 79 ANOCA patients (84% female, age 58{+/-}10 years) undergoing coronary function testing. ECs were isolated, expanded and characterized using immunostaining, flow cytometry, gene expression profiling and functional assays. Results | EC isolation was successful in 43% of cases and resulted in 34 primary EC cultures that were expanded up to passage 10. Isolation success was independent of clinical or procedural characteristics. Isolated cells exhibited typical EC morphology and expressed EC markers confirmed by immunostaining, flow cytometry and gene expression analyses. EC marker gene expression remained largely stable over passages. However, stress- and defense-related gene expression programs increased over time, while proliferation-related processes decreased. Functional assays demonstrated that the coronary catheterization-derived ECs showed typical properties of wound healing, angiogenesis, activation responses upon stimuli and monocyte adhesion. Conclusions | This study demonstrates the feasibility of isolating and expanding ECs directly from catheterization material collected during routine coronary function testing in ANOCA patients. These patient-derived ECs retain characteristic endothelial features and functionality. This approach offers primary EC cultures to study the mechanisms underlying endothelial dysfunction in ANOCA.