The Journal of Heart and Lung Transplantation

Background and aimsTissular gene expression profiling has the potential to refine the diagnosis of cardiac allograft rejection. Contrary to whole-transcriptome approaches, targeted molecular profiling applicable to formalin-fixed paraffin-embedded (FFPE) endomyocardial biopsies (EMB) can be easily implemented in clinical practice. We aimed to develop and validate the first rejection molecular diagnostic system dedicated to heart transplantation (HTx). MethodsAn international multicenter study was designed, building a deep phenotyped cohort of HTx recipients recruited between 2011 and 2021 at 4 referral centers. Detailed donors, recipients, clinical, immunological, biological, and histological parameters were collected. EMBs were graded according to international working formulations. Tissue gene expression was analyzed on FFPE-EMB using the consensus Banff Human Organ Transplant gene set. Molecular classifiers of antibody-mediated (AMR) and acute cellular rejection (ACR) were built. Discrimination and calibration were assessed in the development and validation sets (NCT06436027). ResultsA total of 591 biopsies were included: 188 AMR (pAMR1(I+): n=51; pAMR1(H+): n=58; pAMR2-3: n=79), 289 ACR (1R n=174; 2-3R n=115) and 114 matched non-rejection cases. Biopsies were split in a derivation (n=476) and a validation set (n=115). AMR top significant transcripts were related to the IFN-gamma inducible pathway, endothelial activation, and monocyte-macrophage recruitment. ACR was characterized by transcripts related to T-cell receptor, CD3 receptor activation, and CD28 signaling. ACR and AMR molecular rejection models were strongly associated with the pathology severity of rejection and accurately identified rejection in the derivation (ROC-AUC: AMR=0.831, ACR:=0.837) and validation sets (ROC-AUC: AMR=0.812; ACR=0.849). Calibration was adequate. The robustness of the molecular classifiers were reinforced by various sensitivity analyzes. An automated report was developed to enhance the reproducibility and clinical applicability of the molecular analysis. ConclusionsIn this study, the first tissue-based rejection molecular diagnostic system applicable to FFPE- EMB and dedicated to heart transplantation rejection was developed and internally validated. This tool has the potential to refine the diagnosis of rejection.

ObjectiveHeart transplants utilizing donors from circulatory death (DCD) allografts are rapidly growing with the potential to expand the donor pool. However, little is known about the use of DCD donors for simultaneous heart and kidney transplants (SHKT) compared to SHKT using brain death donors (DBD). MethodsFrom May 22, 2020, to September 30, 2023, 1,129 adult patients received SHKT (DCD, N=91 vs. DBD, N=1,038), identified using the United Network for Organ Sharing database, excluding other multi-organ transplants and re-transplants. A 1:3 ratio propensity score matching was performed using 17 recipient characteristics and 7 donor characteristics. A total of 91 DCD and 273 DBD matched cases were compared. ResultsIn the unmatched cohort, DCD recipients were older (DCD: 60 vs. DBD: 58 years, p=0.03) and had a lower rate of dialysis at transplant (27% vs. 40%, p=0.03) and status 1 to 2 patients (43% vs. 72%, p<.001). Donors were younger (30 vs. 32 years, p=0.02) in the DCD group. In the matched cohort, kidney delayed graft function (27% vs. 22%, p=0.29) was comparable, as were recipient survival (p=0.19), heart graft survival (p=0.19), and kidney graft survival (p=0.17). In multivariate Cox proportional hazards analysis, donor type (DCD) was not associated with an increased risk of mortality (HR=1.69, 95% Cl 0.90-3.16, p=0.10). Sub-group analysis showed that survival and freedom from graft failures were comparable between different modes of DCD recovery. The centers performing both DCD- and DBD-SHKT showed significantly shorter waitlist days with comparable transplant outcomes compared to centers that only performed DBD-SHKT. Conclusions SHKT using DCD donors yields comparable survival and graft outcomes to those using DBD donors. These findings will guide treatment strategies for heart transplant candidates with kidney dysfunction, including the selection of donors and patients and safety net policy options.

BackgroundCardiac allograft rejection (CAR) remains the leading cause of early graft failure after heart transplantation (HT). Current diagnostics, including histologic grading of endomyocardial biopsy (EMB) and blood-based assays, lack accurate predictive power for future CAR risk. We developed a predictive model integrating routine clinical data with quantitative morphologic features extracted from routine EMBs to demonstrate the precision-medicine potential of mining existing data sources in post-HT care. MethodsIn a retrospective cohort of 484 HT recipients with 1,188 EMB encounters within 6 months post-transplant, we extracted 370 quantitative pathology features describing lymphocyte infiltration and stromal architecture from digitized H&E-stained slides. Longitudinal clinical data comprising 268 variables--including lab values, immunosuppression records, and prior rejection history--were aggregated per patient. Using the XGBoost algorithm with rigorous cross-validation, we compared models based on four different data sources: clinical-only, morphology-only, cross-sectional-only, and fully integrated longitudinal data. The top predictors informed the derivation of a simplified Integrated Rejection Risk Index (IRRI), which relies on just 4 clinical and 4 morphology risk facts. Model performance was evaluated by AUROC, AUPRC, and time-to-event hazard ratios. ResultsThe fully integrated longitudinal model achieved superior predictive accuracy (AUROC 0.86, AUPRC 0.74). IRRI stratified patients into risk categories with distinct future CAR hazards: high-risk patients showed a markedly increased CAR risk (HR=6.15, 95% CI: 4.17-9.09), while low-risk patients had significantly reduced risk (HR=0.52, 95% CI: 0.33-0.84). This performance exceeded models based on just cross-sectional or single-domain data, demonstrating the value of multi-modal, temporal data integration. ConclusionsBy integrating longitudinal clinical and biopsy morphologic features, IRRI provides a scalable, interpretable tool for proactive CAR risk assessment. This precision-based approach could support risk-adaptive surveillance and immunosuppression management strategies, offering a promising pathway toward safer, more personalized post-HT care with the potential to reduce unnecessary procedures and improve outcomes. Clinical PerspectiveWhat is new? O_LICurrent tools for cardiac allograft monitoring detect rejection only after it occurs and are not designed to forecast future risk. This leads to missed opportunities for early intervention, avoidable patient injury, unnecessary testing, and inefficiencies in care. C_LIO_LIWe developed a machine learning-based risk index that integrates clinical features, quantitative biopsy morphology, and longitudinal temporal trends to create a robust predictive framework. C_LIO_LIThe Integrated Rejection Risk Index (IRRI) provides highly accurate prediction of future allograft rejection, identifying both high- and low-risk patients up to 90 days in advance - a capability entirely absent from current transplant management. C_LI What are the clinical implications? O_LIIntegrating quantitative histopathology with clinical data provides a more precise, individualized estimate of rejection risk in heart transplant recipients. C_LIO_LIThis framework has the potential to guide post-transplant surveillance intensity, immunosuppressive management, and patient counseling. C_LIO_LIAutomated biopsy analysis could be incorporated into digital pathology workflows, enabling scalable, multicenter application in real-world transplant care. C_LI

BackgroundTraditional heart transplant registries often lack the granularity required for deep phenotyping and rely on labor-intensive manual abstraction. We describe the methodology and validation of a next-generation, automated, multi-source registry designed to address these limitations. MethodsUtilizing a High-Performance Computing environment, we integrated structured data from Epic data warehouses (Clarity and Caboodle), external molecular diagnostics, and verified UNOS survival records. A custom deterministic rule-based Natural Language Processing (NLP) engine was developed to extract echocardiographic measures, rejection grades, and vasculopathy scores from over 21,000 unstructured clinical reports. ResultsThe Houston Methodist J.C. Walter Jr. Transplant Center Precision Registry and Platform-Heart (TCPR-Heart) captures 1,687 heart transplants (1,636 patients) spanning the years 1984-2025. The TCPR-Heart comprises 1,054 transplants with active clinical follow-up: 555 transplants were extracted and abstracted from our modern electronic health record (EHR) in the decade since deployment, providing access to data throughout the patients course of heart transplant; 427 were legacy active transplants (transplanted pre-2016 with continued follow-up), and 72 were external transplants (transplanted elsewhere but followed at Methodist). Additionally, the registry houses a historic cohort of 633 transplants (last follow-up < June 2016) with limited variables. Automated deep phenotyping successfully generated longitudinal data trends across clinical domains, including immunosuppression strategies, rejection, immunologic HLA data, renal function, metabolic profiles, vasculopathy, graft function, hospitalization burden and survival information. ConclusionThis automated framework unifies clinical, administrative, and molecular data streams. By leveraging an automated, regularly updated registry, we established a scalable, high-fidelity data source as a foundation for further innovations and novel applications based on an expertly curated and validated data source.

This study compares myocardial injury responses in human donor hearts from donation after brain death (DBD) and donation after circulatory death (DCD), with a focus on myocardial membrane integrity, pyroptosis, and damage. Unlike DCD hearts, which are exposed to varying durations of functional warm ischemic times (fWITs), DBD hearts - never subjected to warm ischemia - served as controls. A total of twenty-four human hearts were procured, consisting of six from the DBD group and eighteen from the DCD group. All procured hearts were placed in cold normal saline and stored for up to six hours. Left ventricular biopsies were performed at 0, 2, 4, and 6 hours to assess plasma membrane repair proteins (Annexin A1, Dysferlin), pyroptosis markers (NLRP3, caspase-1, GSDMD-NT), and to evaluate edema and injury scores. Data suggest that DBD hearts maintained stable levels of plasma membrane repair proteins and showed no evidence of pyroptosis activation or significant injury throughout cold storage. In contrast, DCD hearts exhibited profound Annexin A1 depletion, early and progressive pyroptosis, elevated edema, and worsening histopathological injury - directly correlated with fWITs. These findings underscore that warm ischemia is a critical determinant of pyroptotic damage in donor hearts, and highlight the relative resistance of DBD hearts to such injury during preservation. For DCD hearts, strategies to enhance membrane repair capacity and inhibit pyroptosis should focus on the fWIT phase to assess donor heart quality and suitability for transplantation. New & NoteworthyThis study demonstrates that donor hearts procured after circulatory death (DCD) exhibit early Annexin A1 depletion and activation of the NLRP3/caspase-1/GSDMD-mediated pyroptosis pathway during cold storage - a phenomenon absent in brain-dead (DBD) donors. We establish a direct correlation between warm ischemia time and pyroptotic damage in DCD hearts. These findings identify Annexin A1 as a key mediator of ischemia injury and a promising therapeutic target to improve viability in marginal donor hearts.

BackgroundEx vivo oxygenated perfusion systems is a promising approach to extend cardiac allograft preservation beyond the typical 4-6h limit allowed by static-cold-storage (SCS). Hypothermic oxygenated perfusion (HOPE) has been proven to safely preserve donor hearts, yet its underlying molecular mechanisms have not been extensively evaluated. ObjectivesThe aim of the study is to characterize cardiomyocyte viability, transcriptomic and metabolomic responses, and functional recovery of porcine hearts preserved with HOPE for up to 48h, including evaluating their ability to regain sinus rhythm following bench-top normothermic reperfusion (NMP). MethodsSeventeen Yorkshire pigs underwent donor cardiectomy. In the first arm, ten hearts were preserved for up to 48h using either SCS (n=5) or HOPE (n=5). Endomyocardial biopsies were collected at 0, 12, 24, and 48h for histology, RNA sequencing, flow cytometry, and metabolomics. In the second arm, six HOPE-preserved hearts (3h, 24h, 48h) and one SCS-preserved heart (24h) underwent 2h NMP to simulate transplantation and assess reanimation. ResultsHOPE preserved cardiomyocyte viability and structural integrity for 48h, in contrast to SCS in both arms of the study. RNA sequencing and untargeted metabolomics revealed conserved energy-substrate profiles in HOPE and progressive ischemic metabolite accumulation in SCS. All HOPE hearts regained stable sinus rhythm. ConclusionsHOPE enables 48h ex vivo heart preservation while maintaining cardiomyocyte integrity, normal gross and microscopic architecture, and rapid functional recovery on bench-top reperfusion in a preclinical model. These findings establish a foundation for redefining clinical preservation times and widening geographic donor access. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=176 SRC="FIGDIR/small/25335053v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@6c4feorg.highwire.dtl.DTLVardef@6f00bcorg.highwire.dtl.DTLVardef@1993bfdorg.highwire.dtl.DTLVardef@1319f76_HPS_FORMAT_FIGEXP M_FIG C_FIG

Tricuspid regurgitation and pulmonary artery systolic pressure may contribute to post-operative morbidity and mortality in liver transplantation. Previous studies suggest that a high Model for End-Stage Liver Disease score may influence the relationship between tricuspid regurgitation and post-operative mortality. Adult patients undergoing liver transplantation workup between 2010 and 2023 were included in this retrospective observational cohort study. Patients with significant portopulmonary hypertension were excluded. Transthoracic echocardiograms were completed pre-transplant and patients were followed up for one year post-operatively. 1031 patients (median MELD score 17, IQR 12-23) underwent transthoracic echocardiography for liver transplantation workup, of whom 708 underwent successful transplantation. Mild or greater tricuspid regurgitation did not predict 1-year mortality in the overall population (HR 1.79 (95% CI 0.78-4.11), p=0.19). Among patients with MELD scores [&ge;]20, mild or greater tricuspid regurgitation was a significant predictor of 1-year mortality (7 (12.7%) vs 9 (3.8%), p=0.01) (HR 3.46 (1.30-10.32), p=0.02). Tricuspid regurgitation in patients with high MELD scores was associated with a trend towards an increased risk of 30-day major adverse cardiovascular events (9 (16.4)% vs 46 (8.1%), p=0.06), driven predominantly by rates of post-operative heart failure (12.7% vs 3.8%, HR 3.66 (95%CI 1.30-10.32), p=0.01). Elevated pulmonary artery systolic pressure was associated with prolonged hospital stay (30 days (14-46) vs 15 days (11-29), p=0.01). Our study confirms that mild or greater tricuspid regurgitation is a significant predictor of 1-year mortality in patients with high MELD scores undergoing liver transplantation. Tricuspid regurgitation severity should be considered during pre-liver transplantation risk stratification.

ObjectivesDonation after circulatory death (DCD) expands the donor heart pool but is limited by warm ischemia and short preservation times. Hypothermic oxygenated perfusion (HOPE) extends storage beyond the 4-6-hour limit of static cold storage (SCS), yet cellular and molecular responses remain undefined. We evaluate cardiomyocyte integrity and functional recovery of DCD porcine hearts after in situ reanimation with normothermic regional perfusion (NRP) and preservation by SCS (2h) or HOPE (24h) and assess the impact of NRP under DCD conditions. MethodsNine Yorkshire pigs underwent DCD cardiectomy. Six animals experienced 15 min warm ischemia followed by 60 min NRP. Three hearts were preserved for 2h with SCS and three for 24h with HOPE. A second DCD group (n=3) underwent direct procurement without NRP and 2h of HOPE preservation. All hearts were reanimated by normothermic machine perfusion to assess rhythm and contractility. Cardiomyocyte viability, transcriptomics, and metabolomics were analyzed. ResultsAfter DCD+NRP, 2h SCS preserved intact cardiomyocyte viability. HOPE maintained measurable, though reduced, viability at 24h, while 24h SCS failed even under donation after brain death (DBD) conditions. Transcriptomic and metabolomic analyses showed marginal differences between 2h SCS and 24h HOPE. All 24h HOPE hearts regained sinus rhythm but showed reduced contractility vs 2h SCS. Without NRP, 2h HOPE hearts showed the lowest viability and contractility. ConclusionsHOPE supports extended preservation of DCD hearts, but viability and function decline by 24h. NRP is essential for functional recovery of hearts preserved at hypothermic temperatures in a porcine preclinical DCD model. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=186 SRC="FIGDIR/small/25337185v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@1639a35org.highwire.dtl.DTLVardef@210e49org.highwire.dtl.DTLVardef@30f455org.highwire.dtl.DTLVardef@1f904db_HPS_FORMAT_FIGEXP M_FIG C_FIG

IntroductionFreedom from chronic lung allograft dysfunction (CLAD) is a key objective after lung transplantation, yet predicting its onset remains challenging. This study investigated whether early proteomic changes in bronchoalveolar lavage fluid (BALF) can differentiate between patients maintaining stable graft function at 36 months and those developing CLAD within the first year. Additionally, findings were compared to proteomic data from non-transplanted individuals. MethodsBALF samples were collected at one and twelve months post-transplant from 43 lung transplant recipients together with clinical parameters. Proteomic analysis was performed using mass spectrometry with label-free quantification for global protein profiling and heavy-labelled peptides for absolute quantification of mucins and related proteins. Differentially expressed proteins were identified and analyzed through pathway enrichment to explore biological mechanisms associated with CLAD. ResultsNo significant proteomic differences were detected at one month. By twelve months, 63 proteins were differentially expressed between patients who developed early CLAD and those with stable function. Mucin levels declined in stable patients but remained elevated in both groups compared to healthy controls. Cartilage acidic protein 1 was significantly higher in stable patients at twelve months and correlated with better pulmonary function. Pathway analysis linked several altered proteins in CLAD patients to networks associated with lung injury and remodelling. ConclusionProtein profiles in BALF that resemble those of healthy lungs are associated with sustained graft function, while persistent expression of lung injury markers is associated with early CLAD. This suggests an adaptive process is needed for long-term post-transplant success.

BackgroundWe aimed to identify data-driven FEV1 trajectory phenotypes post-chronic lung allograft dysfunction (CLAD), relate these phenotypes to patient factors and future graft loss, and develop a classification approach for prospective patients. MethodsWe studied adult first lung recipients with probable CLAD from two prospective multicenter cohorts: CTOT-20 (n=206) and LTOG (n=1418). FEV1 trajectories over the first nine months post-CLAD were characterized using joint latent class mixed models, jointly modelling time-to-graft loss to account for informative censoring. Models were fit independently in both cohorts and also only among LTOG bilateral recipients. A classification and regression tree (CART) model was derived in LTOG bilateral recipients and applied to CTOT-20 bilateral recipients. FindingsFour distinct early FEV1 trajectory classes were identified in CTOT-20, with large differences in nine-month graft loss (72{middle dot}3%, 31{middle dot}1%, 2{middle dot}2%, 0%). In LTOG, similar trajectory patterns were reproduced, with an additional class demonstrating early post-CLAD FEV1 improvement. Among bilateral recipients, trajectory classes showed a clear risk gradient, including a high-risk class with 100% graft loss and a low-risk class with no early graft loss. A CART model incorporating clinical and spirometric variables demonstrated good discrimination in LTOG bilateral recipients (multiclass AUC 0{middle dot}85) and consistent class assignment and trajectory patterns when applied to CTOT-20. InterpretationWe identified reproducible, clinically meaningful early post-CLAD FEV1 trajectory phenotypes with differential graft loss risk. These phenotypes and a pragmatic classification tool may support risk stratification, trial enrichment, and improved prognostication for patients and clinicians. FundingNational Institutes of Health, Cystic Fibrosis Foundation

BACKGROUNDThere is an urgent need to better understand the pathophysiology of primary graft dysfunction (PGD) so that point-of-care methods can be developed to predict those at risk. Here we utilize a multiplex multivariable approach to define cytokine, chemokines, and growth factors in patient-matched biospecimens from multiple biological sites to identify factors predictive of PGD. METHODSBiospecimens were collected from patients undergoing bilateral LTx from three distinct sites: donor lung perfusate, post-transplant bronchoalveolar lavage (BAL) fluid (2h), and plasma (2h and 24h). A 71-multiplex panel was performed on each biospecimen. Cross-validated logistic regression (LR) and random forest (RF) machine learning models were used to determine whether analytes in each site or from combination of sites, with or without clinical data, could discriminate between PGD grade 0 (n = 9) and 3 (n = 8). RESULTSUsing optimal AUROC, BAL fluid at 2h was the most predictive of PGD (LR, 0.825; RF, 0.919), followed by multi-timepoint plasma (LR, 0.841; RF, 0.653), then perfusate (LR, 0.565; RF, 0.448). Combined clinical, BAL, and plasma data yielded strongest performance (LR, 1.000; RF, 1.000). Using a LASSO of the predictors obtained using LR, we selected IL-1RA, BCA-1, and Fractalkine, as most predictive of severe PGD. CONCLUSIONSBAL samples collected 2h post-transplant were the strongest predictors of severe PGD. Our machine learning approach not only identified novel cytokines not previously associated with PGD, but identified analytes that could be used as a point-of-care cytokine panel aimed at identifying those at risk for developing severe PGD.

Donor derived cell free DNA (ddcfDNA) is increasingly used for post transplantation non invasive surveillance; however, its clinical interpretation remains inconsistent, with widely ranging thresholds and is typically applied as a single binary cutoff in literature. The optimal decision framework for rule out and rule in decisions, and whether a single threshold remains clinically meaningful, are currently uncertain. We performed a Bayesian hierarchical summary receiver operating characteristic (HSROC) meta analysis of 14 studies (1,763 patients) evaluating ddcfDNA against endomyocardial biopsy. To account for serial testing within individuals, we applied a cluster corrected design effect, reducing 6,103 observations to 2,518 effective tests. Threshold dependent sensitivity and specificity were modelled continuously. We compared a conventional single threshold approach (Youden index) with a data driven adaptive framework defining rule out and rule in thresholds. Clinical utility was evaluated using decision curve analysis across a range of rejection prevalences (10% to 30%), incorporating repeat testing strategies. The pooled area under the HSROC curve was 0.78 (95% CrI, 0.67 to 0.84). The Youden optimal threshold (0.20%) yielded balanced sensitivity (0.77) and specificity (0.77) but failed to support clinical objectives of diagnosis. An adaptive framework identified a rule out threshold of 0.16% (sensitivity 0.80) and a rule in threshold of 0.48% (specificity 0.90), defining a indeterminate / grey zone. Across all prevalence scenarios, ddcfDNA guided strategies provided positive net benefit compared with biopsy all and biopsy none approaches. A repeat if borderline strategy consistently achieved the highest net benefit, particularly in low and intermediate risk settings, by reducing false positive biopsies without materially compromising detection. A single threshold interpretation is not clinically adequate for post heart transplant surveillance. Our tri state, prevalence aware framework integrating rule out, indeterminate, and rule in zones with selective repeat testing, more accurately reflects biomarker behavior and improves clinical decision making. These findings support a shift away from binary thresholds toward dynamic, context dependent use of ddcfDNA in transplant surveillance.

BackgroundIn 2018, the United Network for Organ Sharing (UNOS) revised the donor heart allocation policy, replacing the single urgency status for left ventricular assist device (LVAD)-related complications with three distinct categories. We evaluated the impact of this policy modification on transplant access and outcomes. MethodsThe UNOS Standard Transplant Analysis and Research File was queried to identify adult patients listed for heart transplantation with a LVAD-related complication in the United States between 2018 and 2023. The cumulative incidence of heart transplantation, mortality on device, and overall mortality following complication were assessed. ResultsDuring the study period, 792 patients experienced an LVAD complication that led to an initial listing or change in urgency status. Device infection was the most frequent complication (n=472, 59.6%), followed by device malfunction (n=80, 10.1%), aortic regurgitation (n=73, 9.2%), ventricular arrhythmias (n=46, 5.8%), thrombosis/hemolysis (n=43, 5.4%), bleeding (n=42, 5.3%), and right heart failure (n=36, 4.5%). At 1 year, transplantation incidence was 71.5% (95% CI, 67.9-74.8%), mortality on device was 3.8% (95% CI, 2.5-5.4%), and overall mortality was 12.3% (95% CI, 9.9-15.1%). Right heart failure was associated with increased 1-year mortality (34.1%, 95% CI, 18.2-50.8%; adjusted HR 2.0, 95% CI, 1.1-3.8). ConclusionsThe revised allocation system provides LVAD patients with complications timely access to transplantation, reflected in high transplant rates and low mortality. Right heart failure remains a distinct subgroup, with one-third of patients not surviving to one year, suggesting this complication may warrant consideration for higher urgency status.

BackgroundChronic lung allograft dysfunction (CLAD) leads to declining respiratory function and high mortality, representing the main barrier to long-term survival in lung transplantation (LT). We performed the first genome-wide association study (GWAS) investigating donors and recipients genetic factors associated with CLAD. MethodWe genotyped 392 donor-recipient pairs from the multicentric Cohort in Lung Transplantation. We tested 4.5 million SNPs for association with CLAD using multivariable logistic regression models corrected for age, sex, initial disease and genetic ancestry. Three levels of explanatory variables were separately considered to conduct GWAS: donors-only, recipients-only, and donor-recipient mismatches. We also ran HLA-centric analyses using the same models. ResultsOur analysis confirmed the deleterious impact of HLA allelic and epitopic mismatches on CLAD risk, mostly driven by class I HLA (p=0.004). No significant associations with CLAD were found for donors genotypes or donor-recipient non-HLA mismatches. We highlighted two independent recipients loci associated with CLAD, including one protective signal (0.39 in CLAD vs 0.66 in non-CLAD recipients, p-value=5.05x10-7, q-value=0.017, OR=0.35) encompassing the PLXDC2 gene, and one risk signal (0.66 in CLAD vs 0.38 in non-CLAD recipients, p-value=9.86x10-7, q-value=0.017, OR=2.83) encompassing the ZNF518A/BLNK genes. These non-coding SNPs are putative regulatory variants of gene expression. Importantly, our single-cell RNA-sequencing showed a down-regulation of PLXDC2 in monocytes and lung epithelium in CLAD vs healthy controls (p[&le;]2.0x10-16). ConclusionThis first LT GWAS revealed two candidate loci from the recipients genome, both biologically relevant for CLAD pathogenesis. Our study calls for larger LT genomic initiatives to increase power for signal discovery.

ObjectiveTo analyze the experience of the last six years with ECMO in Uncontrolled Donation after Circulatory Death (uDCD), assessing the clinical and logistical factors that determine donation effectiveness and the viability of retrieved organs, with the nurse perfusionist as the central figure in organ perfusion. MethodsRetrospective observational study of uDCD procedures performed at Hospital Clinic de Barcelona between June 2019 and October 2025. ResultsOf 184 out-of-hospital ECMO-CPR activations, 108 (58.7%) underwent perfusion; 72 donor cases (66.7%) were generated, and 109 kidneys (75.7%) and 3 livers (4.15%) were retrieved. The annual number of uDCD donors was heterogeneous. Compared with non-effective donors, effective donors were significantly younger (48.1 {+/-} 12.4 vs 53.0 {+/-} 10.7 years, p=0.03) and had fewer comorbidities such as hypertension (13.8% vs 33.0%, p=0.018) and diabetes (4.1% vs 16.6%, p=0.027). Although effective donors had a shorter cannulation time (25.6 {+/-} 13.9 vs 29.1 {+/-} 11.9 min, p=0.09), the difference was not statistically significant; however, cardiocompressor time did show a significant difference (58.9 {+/-} 17.7 vs 65.8 {+/-} 18.2 min, p=0.03). ConclusionsuDCD was a useful source of transplantable organs, mainly kidneys (two out of every three perfused patients became donors), in the current context of scarcity of brain-dead donors. Shorter warm ischemia times (cardiocompressor and cannulation times) were significantly associated with more effective organ donation. The multidisciplinary transplant team may benefit from perfusion professionals with expertise in extracorporeal oxygenation therapy.

BackgroundNoninvasive, physiology-based methods to monitor systemic venous congestion and guide volume management early after durable LVAD implantation are lacking. We investigated whether changes in portal, hepatic, and renal vein Doppler flow patterns correlate with net fluid balance and whether these changes are associated with renal function and right ventricular (RV) performance in this setting. MethodsIn this prospective, proof-of-concept observational study at a national referral center for mechanical circulatory support, we enrolled 20 adult patients undergoing durable LVAD implantation between June 2024 and May 2025. Each patient underwent splanchnic venous Doppler ultrasound (hepatic, portal, and renal veins) and focused echocardiography at two time points: early after ICU admission (T0) and within 7 days (T1), post-implantation. Clinical, biochemical, and device parameters were recorded at each time point. Doppler findings were available to treating physicians and could inform real-time decisions; however, no predefined Doppler-guided protocol was applied. ResultsPatients experienced a significant negative fluid balance (median {Delta}=-6034 mL; IQR:- 8145 to -3476), which was accompanied by consistent improvement in venous Doppler profiles and a significant reduction in VExUS score (p < 0.001). Changes in portal and renal vein Doppler patterns correlated with net fluid balance (rho=0.45, p=0.046 and rho=0.68, p=0.001, respectively). A trend was also observed between VExUS change and fluid balance (rho=0.45, p=0.053). Renal function improved significantly, with an increase in eGFR (p=0.033), and right ventricular function showed parallel recovery: RV systolic velocity (S) increased (p=0.001), RV dilation regressed (p=0.008), and tricuspid regurgitation grade decreased (p=0.001). ConclusionsPoint-of-care Doppler assessment of splanchnic venous flow is feasible early after LVAD implantation and reflects dynamic changes in fluid balance, renal function, and RV performance. These findings suggest that venous Doppler ultrasound may provide a physiologic, bedside method to guide decongestive therapy in this complex population, warranting validation in larger, protocol-driven studies. What Is New?O_LIFirst prospective proof-of-concept study to evaluate hepatic, portal, and renal vein Doppler flow patterns in the early period after durable LVAD implantation. C_LIO_LIDemonstrates that portal and renal vein Doppler changes correlate with net fluid balance and parallel improvements in renal function and right ventricular performance. C_LIO_LIShows that bedside splanchnic Doppler assessment is feasible and captures physiologic changes in systemic venous congestion not reflected by conventional parameters. C_LI Clinical ImplicationsO_LISplanchnic vein Doppler assessment provides a noninvasive, physiology-based method to track systemic venous congestion after LVAD implantation and may yield insights into organ recovery. C_LIO_LIThese data provide a foundation for larger studies to determine whether integrating splanchnic Doppler into ICU monitoring improves post-LVAD outcomes. C_LI

BackgroundRight ventricular failure (RVF) after left ventricular assist devices (LVAD) is associated with significant morbidity and mortality and identifying patients at risk for severe RVF is an important clinical goal. Current risk prediction models were not developed in contemporary LVAD populations and have limited clinical applicability. ObjectivesTo evaluate whether the Model for End Stage Liver Disease - eXcluding INR (MELD-XI) can predict severe RVF after HeartMate 3 (HM3) implantation. MethodsWe retrospectively analyzed all adult patients who received HM3 LVAD as initial implantation at two academic medical centers. We assessed whether MELD-XI is an independent risk factor for severe RVF in multivariate analysis and compared the predictive accuracy of MELD-XI with previously published risk scores. We also investigated the relationship between MELD-XI and markers of right ventricular function and whether MELD-XI was associated with death or pump exchange at 1-year follow-up. ResultsOur study included a total of 246 patients, of which 74 (30%) experienced severe RVF. After adjusting for relevant covariables, MELD-XI was independently associated with severe RVF (OR 1.18, CI 1.09-1.29, p<0.001) and performed similarly to the EUROMACS and Michigan RVF risk scores. In addition, MELD-XI was not reflective of traditional echocardiographic or hemodynamic measures of right ventricular function. Finally, MELD-XI [&ge;] 14 predicted worse in-hospital mortality. ConclusionsAmong patients undergoing HM3 implantation, MELD-XI is independently associated with an increased risk of RVF and in-hospital mortality.

BackgroundSince the United Network for Organ Sharing (UNOS) allocation system change patients listed for orthotopic heart transplant (OHT) are more likely to be on temporary mechanical circulatory support (tMCS). Limited sex specific data exits for use and outcomes of tMCS since the allocation change. MethodsWe queried the UNOS registry for patients listed for OHT on tMCS from October 1, 2015 to June 28, 2023, comparing baseline characteristics and outcomes between sexes pre- and post-allocation change. ResultsWomen comprised 23% of patients listed for OHT on tMCS before and after the allocation change, despite similar cardiac index (CI) compared with men (pre: 2.03 vs 2.09 L/min m2 p=0.21; post: 1.92 vs 1.92 L/min m2 p=0.89). Women were significantly younger (54 vs 57 years; p<0.001), had lower BMI (26.9 vs 27.2; p 0.006), were more likely to be on intra-aortic balloon pump (IABP) (67% vs 61% p <0.001) and had shorter waitlist times (13 vs 16 days; p <0.001). Waitlist mortality decreased similarly for both sexes (3.6% vs 3.8%; p= 0.7). There was no significant difference in 1-year post-transplant survival between the sexes in either era (HR: 0.9, 95% CI: 0.76, 1.06 p=0.2), however, 1-year post-transplant survival improved overall for patients bridged with tMCS post allocation change independent of sex (HR 0.70 (95% CI: 0.54 to 0.90; p=0.005). ConclusionDespite an increase in the use of tMCS as a bridge to OHT since the UNOS allocation change, women comprise less than a quarter of patients listed on tMCS despite similar CI, suggesting possible underuse in women. Notably, for those bridged to OHT in the post allocation era, waitlist mortality has improved for both sexes and 1-year post-transplant survival has also improved independent of sex.

BackgroundWe investigated the myocardial perfusion differences and changes in immune cell response in heart-transplant patients with nonspecific graft dysfunction (NGD) compared to cardiac allograft vasculopathy (CAV) patients and normal heart-transplant patients. Methods and ResultsWe prospectively studied 17 heart-transplant patients (59.8{+/-}14.1 years, 78% male) from January to June 2016. Regadenoson stress cardiac MRI was performed in the patients and peripheral blood obtained contemporaneously to isolate peripheral blood mononuclear cells (PBMCs). Stress myocardial perfusion showed significantly decreased myocardial perfusion using maximum upslope method in NGD and CAV patients compared to normal heart-transplant patients. Myocardial scar by late gadolinium enhancement also was significantly increased in nonspecific graft dysfunction patients compared to normal. Evaluation of PBMCs by flow cytometry showed a trend towards increased activated HLA-DR+ T cells in NGD patients compared to normal. Clinical outcomes for cardiac hospitalization, allograft loss/retransplant, death were assessed at 8 years. ConclusionsNGD shows decreased stress myocardial perfusion by cardiac MRI and a trend towards increased activated T cells in PBMCs, suggestive of an immune-mediated cause for allograft dysfunction.

BackgroundCardiac allograft vasculopathy (CAV) is the leading cause of late graft failure and mortality after heart transplantation (HT). Among non-HT patients, elevated Lp(a) levels are associated with increased atherosclerotic cardiovascular disease (ASCVD) risk. However, it is less clear what role Lp(a) may play in the development of CAV and how it interacts with other lipids post-transplant. ObjectivesWe sought to examine the association between elevated Lp(a) and CAV among adult HT recipients at a single high-volume heart transplant center. MethodsWe performed a retrospective analysis of 504 adult HT recipients followed at the transplant center who had undergone coronary angiography for CAV evaluation within 5 years post-transplant. Maximum Lp(a) values and lipid panels obtained concurrently were collected. Patients were considered to have CAV if they had CAV 1 or higher by ISHLT grading on any coronary angiography obtained within 5 years post-transplant. ResultsIn our cohort, 114 patients developed CAV. Among all patients who developed CAV, there was a significant difference in 5-year incidence rate of CAV when stratified by Lp(a) [&ge;] 90 mg/dL or < 90 mg/dL. The incidence of CAV was 9.4 per 100 person/years in the lower Lp(a) group versus 15.2 per 100 person/years in the higher Lp(a) group (p=0.031). Kaplan-Meier plots of CAV-free survival showed a significant association between CAV-free probability and Lp(a) [&ge;] 90 mg/dL (p=0.037). After stratifying Kaplan-Meier plots by LDL, the relationship between Lp(a) [&ge;] 90 mg/dL and CAV-free probability remained significant (p=0.012) among patients with LDL [&le;] 100 mg/dL but was no longer significant (p=0.85 in patients with LDL > 100 mg/dL. Among patients with LDL [&le;] 100 mg/dL, the Cox model results suggested higher Lp(a) levels increase the risk of developing CAV after HT (HR 1.35, 95% CI 1.03-1.76, p=0.03). ConclusionsAmong post-HT patients, Lp(a) [&ge;] 90 mg/dL was associated with increased risk for development of CAV, particularly at lower LDL levels. In patients with LDL [&le;] 100 mg/dL, Lp(a) [&ge;] 90 mg/dL was associated with CAV-free survival. Lp(a) may be a useful biomarker for risk stratification in transplant patients and a potential future target for CAV prevention with emerging Lp(a) therapeutics.