The Journal of Heart and Lung Transplantation

BACKGROUND: Machine learning (ML) models have been used to evaluate one-year post-transplant mortality in donor-recipient pairs. Previous modeling utilizing noninterpretable ML methods (deep neural networks [DNN] and XGBoost) showed modest gains in area under the receiver operating curve (AUC) beyond logistic regression, but suffered a significant drop in predictive AUC applied to the subsequent years' data and lacked statistical significance in validating previously identified risk factors. METHODS: Using balanced SRTR datasets, we evaluated non-interpretable models against interpretable ML models (adaptive logistic regression with interaction terms [aLR], Classification and Regression tree [CART], and conditional inference tree [CIT]) for one-year mortality, including comprehensive clinician-supervised data curation and inclusion of variables describing pre- and post-2018 listing status changes. Models were trained/tested using rolling-window validation across years and further analyzed with repeated ten-fold crossvalidation. Interaction terms were obtained via Adaptive Best-Subset Selection (ABESS). RESULTS: Predictive validation before the listing policy change in 2018 showed similar AUCs between DNN (0.579), aLR (0.642), CART (0.579), and CIT (0.584), with XGBoost having a higher (0.763) AUC. However, in the post-2018 predictive analysis, aLR outperformed XGBoost (AUC 0.613 vs. 0.586). The interpretable ML models confirm the significance of previously reported risk factors (recipient bilirubin and creatinine) and identify risk factors not previously reported (donor pH, potential recipient distance, and recipient transfusion), as well as clinically relevant interaction terms. CONCLUSIONS: Carefully developed interpretable ML models of one-year transplant mortality have similar predictive performance to black-box models, while identifying novel risk factors, and showing improved performance after recent listing policy changes. With appropriate validation and additional data, interpretable ML modeling may allow real-time data-driven donor selection.

Background: Transplant arterial injury is an underlying feature of acute organ transplant rejection and is a main cause of late heart transplant failure. The role of the gut microbiota, and especially specific microbial components of this community, in controlling immune responses that cause this aspect of rejection is poorly understood. Methods: We utilized a murine aortic interposition model of transplant arterial injury to investigate the role of the gut commensal bacteria, Akkermansia muciniphila, in controlling immune responses in transplant arteries. Results: Early life treatment of female mice with broad spectrum antibiotics, which delayed colonization of the intestinal tract with bacteria until after weaning, led to the development of dysbiosis in adults that was characterized by the absence of A. muciniphila. This was related to an elevation in systemic levels of CCL2 and a reduction in the immunomodulatory short-chain fatty acid, propionate. When transplant arterial injury was examined, there was more arterial injury indicative of acute rejection and increased intimal thickening reflective of transplant arteriosclerosis in grafts from dysbiotic mice compared to controls. Dysbiosis also increased macrophage accumulation early after transplantation in dysbiotic mice. Notably, restoring A. muciniphila in the gut microbiota of dysbiotic mice through voluntary oral administration in infants ameliorated macrophage-mediated transplant arterial injury. Conclusions: A. muciniphila is an immunomodulatory component of the gut microbiota that protects against vascular injury and pathology in organ transplantation.

Chronic lung allograft dysfunction (CLAD) is a major cause of death after lung transplantation and manifests principally as bronchiolitis obliterans syndrome (BOS) or restrictive allograft syndrome (RAS). Although pulmonary macrophages are key regulators of lung injury and repair, their contributions to CLAD pathogenesis remain under-examined. We performed single-cell RNA sequencing-based transcriptomic analysis of CLAD (7 BOS, 7 RAS) and control lung tissue (n = 6), complemented by comparative and functional analyses. Two distinct macrophage populations were identified in CLAD: inflammatory macrophages expressing leukocyte immunoglobulin-like receptors (LILR), and fibrotic macrophages characterized by expression of osteopontin (SPP1). LILR macrophages were present in both BOS and RAS, whereas SPP1 macrophages were selectively enriched in RAS. Both populations were identified in idiopathic pulmonary fibrosis and cross-tissue comparisons. Surface marker-based sorting strategies were developed to isolate both populations. Functional studies demonstrated that LILR macrophages exhibited enhanced phagocytic activity, promoted T cell chemotaxis and secreted inflammatory mediators, whereas SPP1 macrophages produced soluble factors that drove fibroblast activation and contraction. These findings identify distinct inflammatory and fibrotic macrophage programs associated with CLAD, link RAS to conserved fibrotic macrophage states observed in pulmonary fibrosis and highlight macrophage populations as potential therapeutic targets for inflammatory and fibrotic allograft injury.

Preoperative anaemia is common in adults undergoing cardiac surgery and may identify patients at increased perioperative risk. This systematic review and meta-analysis synthesised contemporary observational evidence in accordance with PRISMA 2020. Five databases were searched for peer-reviewed English language studies published from 2017 to July 2026. Random effects meta-analyses used restricted maximum likelihood estimation with Hartung-Knapp confidence intervals; crude exact count estimates were synthesised primarily and adjusted estimates separately. Fourteen observational cohort studies involving 74,571 adults, including 17,349 (23.3%) with anaemia, were included. Preoperative anaemia was associated with red cell transfusion (OR, 3.66; 95% CI, 2.14-6.24), acute kidney injury or renal failure (OR, 2.43; 95% CI, 1.84-3.21), early mortality (OR, 2.11; 95% CI, 1.40-3.17), and postoperative infection (OR, 1.49; 95% CI, 1.21-1.82), but not postoperative stroke (OR, 1.16; 95% CI, 0.43-3.17). Certainty was low for renal outcomes and very low for the other outcomes. Preoperative anaemia is an important perioperative risk marker, particularly for transfusion and renal complications, although causality cannot be established.

Background: Pulmonary vascular disease identifies an important phenotype of heart failure with preserved ejection fraction (HFpEF), but the relationship between systemic leukocyte activation and invasively measured pulmonary vascular hemodynamics is incompletely understood. We investigated whether the neutrophil-to-lymphocyte ratio (NLR) is associated with combined post- and precapillary pulmonary hypertension (CpcPH), pulmonary vascular burden, and subsequent cardiovascular events in HFpEF. Methods: We retrospectively studied 169 adults with HFpEF and invasively confirmed postcapillary pulmonary hypertension undergoing clinically indicated right heart catheterization. CpcPH was defined as pulmonary vascular resistance (PVR) >2 Wood units. Associations between NLR and CpcPH were evaluated using multivariable logistic regression. Fine-Gray competing-risk models assessed the composite of cardiovascular death or first heart failure hospitalization. Results: Overall, 80 patients had isolated postcapillary pulmonary hypertension and 89 had CpcPH. PVR increased across ascending NLR tertiles (1.8 [1.4-2.5], 2.2 [1.6-3.1], and 2.6 [1.7-3.8] Wood units; P for trend=0.002), whereas pulmonary artery wedge pressure showed no significant trend. Compared with the lowest NLR tertile, the highest tertile was associated with greater odds of CpcPH after adjustment for clinical covariates and filling pressure (adjusted odds ratio, 2.47 [95% CI, 1.01-6.01]; P=0.047). Higher NLR tertiles were also associated with a graded increase in cardiovascular events (Gray's P<0.001). The highest NLR tertile remained associated with outcome after adjustment for clinical and hemodynamic variables (adjusted subdistribution hazard ratio [sHR], 2.37 [95% CI, 1.12-5.03]; P=0.024). Conclusions: Among patients with HFpEF and postcapillary pulmonary hypertension, higher NLR was associated with greater pulmonary vascular hemodynamic burden, CpcPH, and subsequent cardiovascular risk. NLR may provide a readily available marker of a high-risk HFpEF phenotype warranting prospective validation.

BACKGROUND: Increased left ventricular mass (LVM) at a single time point after heart transplantation (HT) predicts future adverse outcomes. However, dynamic changes in LVM could have better biological relevance and reflect adverse graft remodeling (AGR). The prognostic significance of such serial changes has not been studied. METHODS: Using an automated, electronic health record-based institutional data infrastructure, we studied 439 HT recipients with 5,563 LVM measurements. Separate Bayesian joint models estimated the simultaneous associations of current LVM and its instantaneous rate of change with graft dysfunction (GD) and mortality. A joint-model-derived remodeling score combining patient-specific deviations in LVM and slope was dichotomized to define AGR and non-AGR groups. A mixed-effects analysis of all clinical variables was performed to assess associations with LVM both between and within patients. An independent cohort of 35 patients with 79 surveillance-biopsy RNA-sequencing samples was used to examine early stress-responsive pathways associated with the remodeling score. RESULTS: LVM declined by approximately 7 g/year after transplantation, with regression attenuating over time. Sixty patients (13.7%) had GD, and 75 (17.1%) died. Higher LVM was associated with subsequent GD (hazard ratio [HR] per 10 g, 1.14; 95% credible interval [CrI], 1.02-1.28) and mortality (HR, 1.10; 95% CrI, 1.02-1.19). A more positive LVM slope was associated with GD (HR per 1 g/year, 1.21; 95% CrI, 1.06-1.42) and with cardiac allograft vasculopathy (CAV) grade 2 or 3 (HR, 1.39; 95% Crl, 1.02-1.96). LVM regressed more slowly in the AGR group (-5.8 vs -8.4 g/year), with higher GD (21.0% vs 6.4%) and mortality (24.2% vs 10.0%). Time-updated GD was associated with subsequent death (HR, 8.12; 95% Confidence Interval [CI], 4.67-14.14). Transcriptomic analysis showed enrichment of interferon-mediated signaling and vascular endothelial activation with higher remodeling scores, whereas lower scores were associated with mitochondrial and metabolic processes, ribosome biogenesis, and pathways related to tissue repair and stress responses. CONCLUSIONS: AGR is an easily accessible imaging biomarker that reflects the changes in the allograft in response to various stressors and predicts future adverse outcomes. Discovery of molecular mechanisms of AGR could lead to novel therapies to protect the allograft from chronic rejection.

Background: Severe aortic stenosis is associated with systemic and splanchnic hemodynamic disturbances that may alter gut microbial metabolism and host inflammatory responses. Objectives: We aimed to determine whether TAVI remodels the gut microbiome-derived metabolome and whether post-procedural SCFA dynamics are associated with the inflammatory cytokine response. Methods: We conducted a prospective paired single-center study of patients undergoing elective TAVI at Bern University Hospital. Stool and blood samples were collected before and three months after the procedure. Gut microbial composition was profiled by full-length 16S rRNA sequencing, circulating short-chain fatty acids (SCFAs) by targeted metabolomics, and inflammatory mediators by multiplex cytokine analysis, and integrated with hemodynamic and clinical data. Results: Forty patients were enrolled. Following TAVI, microbial richness declined without significant restructuring of overall community composition. In contrast, circulating SCFA profiles were significantly remodeled, driven by selective reductions in butyrate and isovalerate. A greater decline in circulating butyrate was inversely associated with IL-18 elevation (rho=0.668, p<0.001, n=36), independent of aortic valve calcification burden, hemodynamic improvement, and cardiovascular medications. Baseline isovalerate was nominally associated with 1-month adjudicated adverse events (AUC 0.77; exploratory). Conclusions: TAVI is associated with selective changes in gut microbiome-derived metabolic output rather than broad alterations in microbial community structure. Declining circulating butyrate identifies a gut-metabolite-immune axis linked to IL-18 dynamics and represents a potential biomarker of inflammatory recovery following valve intervention.

ABSTRACT Background: The modified Blalock-Taussig-Thomas shunt (mBTTS) sustains pulmonary blood flow in infants with cyanotic or single-ventricle heart disease, but shunt thrombosis occurs in 8-12% of cases and carries substantial mortality. Systemic anticoagulation has limited efficacy. Objectives: This study tested whether surgically modifiable shunt geometry might form a second, patient-specific approach to maintaining shunt patency, via management of thrombogenic hemodynamics. Methods: Three-dimensional mBTTS anatomies were reconstructed from computed tomography in 10 infants (4 thrombosed, 6 patent). Pulsatile inlet waveforms derived from Doppler ultrasound were coupled with three-element Windkessel outlet models individually calibrated to catheter-derived pressures. Transient computational fluid dynamics simulations predicted wall shear rate (WSR) and elongational strain rate (ESR). Associations between surgically relevant geometric parameters and hemodynamic metrics were evaluated. Results: Simulated pressures closely matched clinical measurements at all four outlets in all 10 models. Despite substantial anatomic variability, peak WSR and ESR consistently localized to the shunt-subclavian junction in 8 of 10 patients, including all 4 thrombosed shunts. Greater deviation of shunt insertion angle from perpendicular was associated with higher systolic and cycle-averaged normalized WSR ({rho} = 0.94, p < 0.001; {rho} = 0.88, p = 0.002) and ESR ({rho} = 0.82, p = 0.007; {rho} = 0.70, p = 0.03). Larger shunt diameter was associated with lower WSR and ESR. Thrombosed shunts demonstrated higher shear-related metrics than patent shunts, particularly during systole. Conclusions: In patient-specific mBTTS anatomies, insertion angle and shunt diameter are determinants of local abnormal flow, concentrated at the shunt-subclavian junction. Patient-specific hemodynamic assessment may inform shunt construction and interstage risk stratification.

Background: The Lung Transplant Frailty Scale (LT-FS) is a validated binary measure of frailty in lung transplant candidates. We aimed to refine the LT-FS Base and Body Composition measures by developing a three-category classification to improve clinical risk stratification with serum albumin as a more clinically practical frailty biomarker. Methods: To develop the refined LT-FS, we applied a 4-step measure development method to a multicenter prospective cohort study of lung transplant candidates. Low albumin (<3.5 g/dL) replaced high serum C-reactive protein ([&ge;]10 mg/L) as the LT-FS biomarker. Cutpoints that balanced discrimination, risk prediction, and calibration were identified to define ''frail'', ''pre-frail'', and ''not frail'' categories. Next, we evaluated associations between the refined LT-FS and exercise capacity, patient-reported outcomes, and mortality using multivariate linear and Cox regression. Results: Among 419 participants, the refined LT-FS identified a graded increase in mortality risk across frailty categories. For example, compared with candidates who were not frail, pre-frailty and frailty by the LT-FS Body Composition were associated with a 2.9-fold (HR 2.9, 95% CI 1.2-6.9) and 7-fold (HR 6.9, 95% CI 2.6-18.2) higher risk of waitlist delisting or death, respectively. Pre-frailty and frailty by LT-FS Body Composition were associated with 2-fold (HR 2.1, 95% CI 1.2-3.8) and 3.6-fold (HR 3.6, 95% CI 1.8-7.3) higher risk of mortality after transplant. Relationships with exercise capacity and patient-reported disability were less consistent. Conclusions: A refined Lung Transplant Frailty Scale incorporating serum albumin demonstrates strong associations with waitlist and post-transplant mortality. The addition of a pre-frail category better captures the continuum of frailty and improves clinical risk stratification of lung transplant candidates.

BACKGROUND: Left ventricular ejection fraction (LVEF) independently predicts mortality in repaired tetralogy of Fallot (ToF), but the causes of LV dysfunction are incompletely understood. The intrinsic aortopathy of ToF increases pulsatile afterload, yet whether this contributes to LV dysfunction is unknown. We sought to determine whether aortic dimensions and flow-derived afterload act as cross-sectional markers of LV dysfunction, dynamic contributors to change in LV function over time, or both. METHODS: Retrospective longitudinal study of 554 patients with repaired ToF (1,448 serial cardiovascular magnetic resonance examinations, 2003-2026). Aortic root dimensions, total arterial compliance (TAC: aortic forward flow volume/pulse pressure), and systemic vascular resistance (SVR) were derived, and a within-between decomposition separated between-patient from within-patient associations with LVEF in mixed-effects models. RESULTS: In the analytic sample (1,053 observations, 521 patients), aortic sinus diameter predicted LVEF at both levels (within:{beta} = -0.23, p<0.001; between: {beta} = -0.20, p=0.003). Associations were reproduced at the sinotubular junction but absent at the ascending aorta, localising the effect to the root. TAC predicted LVEF within patients ({beta}=0.90 per mL/mmHg, p=0.014) but not between patients (p=0.62), indicating that pulsatile afterload is a dynamic contributor to LV function. SVR predicted LVEF at both levels (within: {beta} = -0.23; between: {beta} = -0.25; both p<0.001). Blood pressure components alone, expressed as systolic and diastolic or as mean arterial and pulse pressure, did not predict LVEF and fitted the data less well. Adjustment for right ventricular ejection fraction attenuated the within-patient compliance association by 35%, suggesting a component shared with right ventricular function. CONCLUSIONS: Aortic root dimensions, TAC and SVR are independent longitudinal determinants of LVEF in repaired ToF, establishing an important role for aortic haemodynamics in LV function and identifying the systemic vasculature as a potentially modifiable contributor to LV dysfunction.

Background: Blood volume (BV) in patients with chronic heart failure (HF) is characterized by heterogeneity in volume profiles; one profile being "normal BV". While overall intravascular volume may be considered normal clinically, the relative contributions of red blood cell (RBC) mass and plasma volume (PV) may not be. Objective: Assess how normal is a "normal BV" based on quantitative measures of RBC mass and PV. Methods: Retrospective analysis was undertaken in 395 patients with Class II-III HF. BV was quantitated using indicator-dilution methodology. Cohort was stratified by normal and hypervolemic BV. Results: Of the cohort, 31% (123/395) demonstrated normal total BV and 62% (244/395) hypervolemic BV. Of patients with "normal BV", 36% (44/123) demonstrated normal RBC mass and 60% normal PV (74/123). Importantly, 60% (74/123) demonstrated a deficit in RBC mass (true anemia), while a low hemoglobin (<12 g/dL) was present in just 29% (36/123). An excess in RBC mass (erythrocytosis) in 4% (5/123). Notably, true normal BV (i.e., normal RBC mass and normal PV) was observed in only 30% (37/123) of patients with an overall "normal" intravascular volume. Conclusions: Findings reveal that "normal BV" can be misleading by concealing substantial variability in RBC mass (including unrecognized anemia and erythrocytosis) as well as different degrees of PV expansion and contraction. An actual normal BV was identified in a minority of "normal BV" patients. This underscores the importance of looking beyond overall "normal BV" to the contributing elements of RBC mass and PV with significant implications for patient management and outcomes.

Background Risk stratification for primary ventricular tachycardia/ventricular fibrillation (VT/VF) in patients with ST-elevation myocardial infarction (STEMI) remains limited. We aimed to identify gut microbiome biomarkers and microbial metabolic pathways associated with primary VT/VF in STEMI using machine learning (ML). Methods Stool samples from 33 STEMI patients (7 with primary VT/VF and 26 without VT/VF) underwent full-length 16S rRNA sequencing during the acute ([&le;]7 days) and recovery (30?60 days) phases. An ML pipeline integrating taxonomic features identified reproducible features associated with primary VT/VF. Core biomarkers were defined as taxa demonstrating both univariate significance (false discovery rate [FDR] <0.05) and multivariate classification importance. Functional pathways and enzymes were predicted using PICRUSt2. Results Five acute-phase taxa were reproducibly associated with primary VT/VF: Clostridium aldenense, Enterocloster bolteae, bacterium NLAE-zl-G101, Alistipes shahii, and Roseburia sp. (all FDR <0.05). A reduced-feature support vector machine model achieved an area under the receiver operating characteristic curve of 0.846 (95% confidence interval, 0.676?0.984), with 85.7% sensitivity and 76.9% specificity. Differential abundance analysis showed enrichment of Bacteroides fragilis, Bacteroides thetaiotaomicron, and E. bolteae. Functional analysis demonstrated enrichment of fucose degradation and purine catabolism, with increased predicted abundances of L-fucose mutarotase and xanthine dehydrogenase. Conclusions Primary VT/VF in STEMI was associated with a distinct gut microbiome-metabolic signature characterized by Lachnoclostridium-related taxa, persistent Bacteroides enrichment, and enhanced predicted fucose and purine metabolism. These exploratory findings warrant validation in larger independent cohorts and mechanistic studies.

Background Long-term survival after solid organ transplantation remains limited by infection, graft dysfunction, and systemic complications. Recent evidence suggests that gut dysbiosis, marked by loss of beneficial commensals and expansion of opportunistic pathogens, is associated with increased mortality in solid organ transplant recipients (SOTRs). While specific species have been associated with higher mortality risk or improved survival, the functional mechanisms on the strain level underlying these associations remain unclear. Here, we integrated gene-centric functional profiling with strain-level resolved metagenome-assembled genomes (MAGs) across 1231 gut metagenomes from 1008 SOTRs (580 kidney, 245 liver, 133 lung and 50 heart transplant recipients) and 233 healthy controls from the TransplantLines Biobank and Cohort Study to link gut microbial functions and metabolic modules to their originating MAGs and assess their association with post-transplant overall survival. Results Functional profiling of the gut microbiome revealed pronounced functional dysbiosis in SOTRs compared with healthy controls, with higher dysbiosis scores significantly associated with increased post-transplant mortality. We identified 97 microbial functions (KEGG Orthologs, KOs) positively associated with impaired survival (hazard ratio >1; FDR < 0.10) and 661 KOs associated with improved survival (hazard ratio <1; FDR < 0.10) after transplantation. KOs associated with excess mortality predominantly encoded functions related to bacterial adhesion, virulence, and stress adaptation. In contrast, protective KOs mapped to 12 highly complete metabolic modules, including shikimate and pyridoxal phosphate biosynthesis. Genome-resolved analysis of 10,397 MAGs revealed that KOs associated with excess mortality were concentrated in members of the Proteobacteria phylum, particularly the Enterobacteriaceae family, whereas protective KOs were enriched in members of the Firmicutes A lineage. Conclusion The functional capacity of the post-transplant gut microbiome differed significantly from that of healthy controls, consistent with a state of post-transplant gut dysbiosis. Notably, functional dysbiosis of the gut microbiome was associated with post-transplant survival. These findings highlight microbial functional potential as a determinant of post-transplant survival and a promising target for microbiome-informed risk prediction and therapeutic intervention.

BACKGROUND: The revised 2018 AHA/ACC guidelines introduced the Adult Congenital Heart Disease Anatomic and Physiologic classification (ACHD-AP) to better categorize disease severity and prognosis in the ACHD population. The ACHD-AP has not been rigorously studied as a perioperative prediction tool. OBJECTIVE: We aimed to assess the accuracy of the ACHD-AP classification in predicting perioperative morbidity and mortality. METHODS: This retrospective cohort study included 295 ACHD patients at a single academic institution between 2018 to 2022. Patients were identified by the STS congenital surgery registry and had undergone a congenital surgical procedure. The primary outcome was overall mortality. Secondary outcomes included short-term post-operative morbidity and comparison of the ACHD-AP score to other existing surgical mortality risk scores. Kaplan-Meier and area under the curve (AUC) of Receiver Operating Characteristic curves were used to evaluate mortality. Logistic regression was used to compare short-term morbidity. RESULTS: A total of 295 patients were included with a median age of 30 years (interquartile range 21-41 years) and 52% were female. There was a total of 14 deaths with 5 (2%) early post-operative deaths and 9 (3%) long-term deaths. By increasing anatomy complexity, overall mortality was 0%, 4% (n=10), and 8% (n=4), respectively. By increasing physiologic severity, overall mortality was 0%, 3% (n=2), 4% (n=7), and 14% (n=5). Moderate and complex anatomy trended towards increased mortality but were not statistically significant (p-value > 0.9). More severe physiology scores predicted increased mortality (p-value = 0.02). Higher physiologic or anatomic complexity scores were associated with longer post-operative length of stay (>5 days). The ACHD-AP AUC was 0.711 for mortality, which was comparable to the Adult Congenital Heart Surgery (ACHS) score (AUC 0.798) and better than the PEACH score (AUC 0.575). CONCLUSION: The ACHD-AP score revealed comparable or better predictive power to existing risk models. Worsening physiologic and anatomy scores were associated with worse post-operative outcomes. Further prospective studies are needed to validate the ACHD-AP score as a prognostic factor for patients undergoing ACHD surgery.

Background Studies of the 2018 United Network for Organ Sharing (UNOS) policy revision suggest improved early transplantation access for the sickest patients. It remains unknown whether these benefits vary as a function of time on the waitlist. Thus, we evaluated potential time-dependent effects of the 2018 heart allocation policy revision on waitlist outcomes. Methods Using UNOS data, we analyzed adult heart transplant candidates listed five years before (pre-policy) and after (post-policy) policy change, categorized as high-acuity (Status 1-3 or 1A) or low-acuity (Status 4-6 or 1B/old 2). Landmark analysis at weeks 0, 1, 2, 4, 8, 16, 24 using a competing risks framework was performed to assess transplantation, death/deterioration, and myocardial recovery. Sub-distribution and cause-specific hazard ratios were calculated. Absolute number and proportion of far-away transplants (donor distance [&ge;]500 nautical miles) were calculated at each timepoint. Results High-acuity patients experienced significantly higher risk of transplantation within 2 weeks post-policy change but equivocal risk by week 16. Low-acuity patients exhibited increased rate/risk of myocardial recovery and equal or improved death/deterioration risk at all timepoints; early transplantation cumulative incidence was increased. At all timepoints, both groups experienced significantly increased far-away donor use, highest immediately after listing and progressively declining over time. Conclusions The 2018 heart allocation policy change resulted in an initial appearance of time-dependent benefits among high-acuity, post-policy patients, but this was likely due to rapid transplantation of Status 1 and 2 patients from broader geographic sharing rather than a true temporal phenomenon. Post-policy, low-acuity patients experience benefits in all waitlist outcomes.

Background: Aortic stenosis (AS) is a valvular heart disease which imposes chronic pressure overload on the left ventricle (LV). Although LV remodelling may regress following aortic valve replacement, the molecular determinants of reverse remodelling remain poorly understood. This study develops a machine learning-based model using myocardial microRNA (miRNA) expression profiles to predict LV mass normalization one year after valve replacement. Methods: Consensus selection combining Random Forest and Bayesian Network analyses was applied to miRNA sequencing data from LV biopsies of 12 matched patient pairs with AS. Selected miRNAs were qPCR quantified in an extended cohort of 89 AS patients and incorporated into predictive models. Sex-stratified analyses were performed. Model robustness was assessed using bootstrap resampling and cross-validation. Candidate miRNAs and target genes were evaluated in LV from a murine model of pressure overload induced by transverse aortic constriction (TAC). Results: The combined Random Forest-Bayesian Network approach identified a three-miRNA signature (miR-517a-3p, miR-122b-5p, and miR-4683) associated with LV mass normalization after valve replacement. Validation in an extensive cohort demonstrated good overall discrimination and achieved its highest performance in women (AUC >0.80). Functional analyses identified drebrin (DBN1) as a putative target of miR-517a-3p and supported its potential involvement in pressure overload-induced cardiac remodelling. Conclusion: Random Forest and Bayesian Network integrated analyses enabled the identification of a myocardial miRNA signature with sex-dependent predictive value for reverse cardiac remodelling after aortic valve replacement. Functional validation supports the relevance of selected miRNAs and their downstream targets, highlighting their potential as biomarkers and candidate regulators of myocardial recovery.

BACKGROUND: Because of the high mortality rate associated with fulminant myocarditis (FM), there is limited evidence regarding the prognostic efficacy of endomyocardial biopsy (EMB). In this study, we aimed to evaluate the influence of EMB in the early phase after admission on treatment and prognosis in FM using a large-scale nationwide registry in Japan. METHODS: Patients with FM who required catecholamine or mechanical circulatory support between 2012 and 2017 from 235 hospitals across Japan were included. The primary outcome of death or heart transplantation within 90 days according to performance of early EMB were determined using Kaplan-Meier and Cox regression analyses. Factors associated with performance of early EMB, and subsequent medical treatment were analyzed. RESULTS: The median age of 736 patients with clinical FM was 56 years, and 407 patients (55%) received EMB. Most EMB (89%) were performed during the early phase (within 5 days of admission) and 63% were performed on the first day of admission. The prognosis of FM patients who underwent EMB was more favorable than that of those who did not based on the landmark analysis (log-rank test, P=0.04). Factor analysis demonstrated that FM patients who underwent EMB had a lower left ventricular ejection fraction, higher incidence of cardiogenic shock on admission, and higher rate of early mechanical circulatory support, as well as early initiation of corticosteroids and guideline-directed medical therapy (GDMT) for heart failure. Absence of any GDMT was associated with a less favorable prognosis on multivariate analysis (hazard ratio, 4.34 [95% CI, 3.14?6.01]; P<0.0001). CONCLUSIONS: Although performing EMB in the early phase after admission depends on disease severity in FM patients, it is associated with early initiation of advanced medical treatment and may contribute to improving the prognosis.

Objective: Dendritic cells (DCs) are priming local immune responses, and their tissue-associated activity increases in inflammatory conditions. In patients with coronary artery disease (CAD), circulating dendritic cell precursors (DCPs) are reduced. This study investigates circulating DCPs and tissue densities of migrated DCs in CAD patients undergoing bypass surgery, focussing on patients with chronic kidney disease (CKD) as a risk factor for CAD and a condition of chronic vascular inflammation. Approach and Results: Circulating DCPs were measured in the peripheral blood (before surgery) using fluorescence-activated cell sorting (FACS) in n=59 patients and results were compared with an age-matched healthy control group (n=45). DCs were stained (Fascin) in circular sections of the internal thoracic artery taken during bypass surgery and mature (CD83+) and immature (CD209+) DCs were differentiated. Cell densities were obtained digitally. Descriptive statistics and correlation analysis generated hypotheses. Circulating myeloid DCPs were reduced (p<0.001), concomitant CKD added no further reduction. Immature DCs were predominantly detected in the adventitia, mature DCs dominated in the intima (p<0.001). In CKD, reduced circulating myeloid DCPs correlated with immature DCs in the vessel wall (r=0.87; p=0.002) and rather mature DCs were detectable; in patients without CKD immature DCs were dominating. C-reactive protein correlated with mature DCs (r=0.38; p=0.026). Conclusions: Quantities of DCPs and mature and immature DCs vary between the vessel wall layers. The dominance of immature myeloid DCs in the adventitia suggests activation of the vascular-associated lymphoid tissue (VALT). Intensified inflammation associated with CKD may have promoted the maturation of myeloic DCs.

Aims: Myocardial strain enables sensitive assessment of cardiac function, but its clinical application has largely focused on individual chambers or selected patient populations. We evaluated the feasibility and clinical relevance of fully automated multi-chamber strain assessment in consecutive patients undergoing routine transthoracic echocardiography (TTE). Methods and results: This retrospective study included 8,350 consecutive adults undergoing TTE. A hospital-wide artificial intelligence (AI)-based system automatically measured left ventricular (LV) global longitudinal strain (LVGLS), left atrial (LA) reservoir strain (LASr), and right ventricular (RV) free-wall strain (RVFWS). AI-derived LVGLS was available from at least one apical view in 97.1% of patients and from all three views in 94.8%; LASr and RVFWS were available in 94.1% and 94.5%, respectively, resulting in complete multi-chamber strain assessment in 90.3%. Strain measures showed modest correlations with conventional chamber-specific echocardiographic parameters and differential associations with clinical outcomes. Gaussian mixture modeling identified three distinct clusters characterized by preserved multi-chamber function, RV-dominant dysfunction, and pan-chamber dysfunction. Compared with the preserved cluster, pan-chamber dysfunction was associated with the highest risk of all-cause death or heart failure hospitalization (adjusted hazard ratio, 3.44; 95% CI, 2.43-4.88; P<0.001). Prognostic associations remained evident in patients with LV ejection fraction (LVEF) [&ge;]50%, and cluster assignment provided incremental prognostic information beyond clinical factors, LVEF, and RV fractional area change. Conclusions: Fully automated multi-chamber strain assessment was feasible in a large consecutive TTE cohort. Integrating strain across cardiac chambers may provide complementary functional characterization and identify clinically relevant clusters with prognostic information beyond conventional assessment.

Background: Adults with congenital heart disease (ACHD) represent a rapidly expanding population with evolving mortality patterns. Despite improved survival, excess mortality persists. Objective: To evaluate the incidence, causes, and predictors of mortality in a contemporary ACHD cohort. Methods: We performed a retrospective cohort study of adults (?18 years) first evaluated at Mayo Clinic from 2002?2023. Baseline clinical, imaging, and electrocardiographic data were analyzed. Vital status was determined using institutional records and the Accurint national mortality database. Kaplan-Meier analysis and Cox proportional hazard models were used to evaluate mortality and identify independent predictors of mortality Results: A total of 7,678 ACHD patients were included, with median age of 36.8 years and median follow-up of 11.4 years. During 78,768 patient-years of follow-up, 1,116 patients died (median age at death 57.2 years), corresponding to an annual mortality rate of 1.4%. The cumulative rate of all-cause mortality at 5, 10, 15, and 20 years was 6.9%, 12.0%, 19.0%, and 26.2%, respectively. When stratified by CHD complexity, the annual death rate in patients with severe CHD (2.4%/year) was twice that of patients with moderate or mild CHD (both 1.2%/year). Older age and ACHD subtypes, specifically, cyanotic heart disease (HR 3.9, 95% CI 2.9?5.3) and Fontan physiology (HR 3.2, 95% CI 2.3?4.4), were strongly associated with increased mortality. Additional independent predictors included male sex, ventricular dysfunction, advanced NYHA class, prior heart failure hospitalization, hypertension, smoking, coronary artery disease, renal dysfunction, and abnormal hemoglobin levels. Cardiovascular causes accounted for 57.7% of deaths with known etiology, predominantly heart failure (48.9%) and sudden cardiac death (21.9%), while non-cardiovascular causes were driven mainly by infection and malignancy. Conclusions: In this large contemporary ACHD cohort, mortality was driven by ventricular dysfunction, heart failure, and systemic end-organ involvement in addition to the underlying congenital anatomy. Both cardiovascular and non-cardiovascular causes contributed significantly to mortality. These findings underscore the need for comprehensive multidisciplinary ACHD care focused on early recognition of cardiac functional decline, management of acquired comorbidities, and end-organ dysfunction.