Patel, Parag C.

Despite advances in drug and device technology, health care delivery, and research infrastructure, cardiogenic shock (CS) continues to have nearly 50% in‐hospital mortality. In patients with CS, both the initial severity of Society for Cardiovascular Angiography and Intervention CS and its subsequent trajectory predicts the clinical outcomes. Accordingly, delayed initial recognition and failure to escalate or deescalate treatment can significantly affect the outcomes of CS. Traditional assessment methods, with the exception of blood pressure measurement, require a high index of suspicion and frequent reassessment by the clinical team. Electronic medical record‐based detection has been successfully implemented in acute and critical care patients with septic shock and acute kidney injury. In CS, electronic medical record‐based studies have largely focused on using models to predict outcomes in patients with CS, with limited data on electronic medical record‐based tools to assist with either predicting CS or providing real time alerts when escalation or de‐escalation might be indicated. Early detection of CS may be associated with detection of earlier Society for Cardiovascular Angiography and Intervention stages of CS and potentially prevent deterioration to higher stages. In this review, we seek to highlight a blueprint for electronic medical record‐based detection of CS that focuses on reproducibility, convenience, clinical decision support, and research aspects.

Background. Acute cellular rejection (ACR) remains a major cause of morbidity after heart transplantation despite advances in immunosuppression. Whole genome transcriptomic profiling offers a systems-based, unbiased approach to elucidate the molecular mechanisms underlying ACR. However, noninvasive, longitudinal biomarker assessments capable of capturing the temporal dynamics of rejection biology remain scarce. Methods. RNA sequencing of peripheral blood from heart transplant recipients before, during, and after ACR was compared with nonrejection controls. Pathway analysis was conducted using differentially expressed genes (DEGs), and a machine learning approach was applied to assess gene-based prediction of ACR. Results. A total of 235 rejection-specific significant DEGs and 863 postrejection DEGs (false discovery rate < 0.05) were identified. During ACR, DEGs were enriched for T-cell activation/differentiation, apoptosis, and B-cell receptor signaling pathways. By combining the 2 sets of DEGs, a panel of 71 common genes was identified that reflected the significant, longitudinal transcriptomic dynamics of ACR. In an elastic net machine learning–based classifier, DYNLL1 and SERF2 were identified as ACR predictive genes, and achieved a cross-validated area under the receiver operating characteristic curve of 0.63. Conclusions. Peripheral blood transcriptomics identify dynamic temporal responses in ACR including T- and B-cell pathways with potential ACR predictive genes that warrant further investigation.

Background: Progressive heart failure cardiogenic shock (HFCS) often requires escalation to temporary or durable mechanical circulatory support (MCS) as a bridge to transplant (BTT). Following the 2018 UNOS allocation changes, our center revised its BTT strategy to optimize support and shorten wait times. At our institution, the Impella 5.5 with SmartAssist via the axillary approach was selectively used for patients who remained refractory to guideline-directed medical therapy, failed single-inotrope therapy, and were not considered suitable durable LVAD candidates by our multidisciplinary heart team. We compared transplant-related outcomes of BTT patients supported with Impella 5.5 versus durable LVAD. Methods: We performed a single-center retrospective review of all heart and heart/kidney transplant candidates at Mayo Clinic Florida from October 2018 to February 2021. INTERMACS profile, baseline characteristics, and perioperative data were collected at the time of device implantation and throughout the transplant hospitalization. Results: A total of 87 heart and 4 heart–kidney transplants were completed. Forty-five patients (49%) required MCS as BTT: 27 (60%) with a durable LVAD and 18 (40%) with an Impella 5.5. All eighteen patients with Impella 5.5 as BTT (100%) were transplanted compared to nineteen patients with durable LVAD (70%), p = 0.001. The median time from listing to transplant was substantially shorter with Impella (32 vs. 696 days, p < 0.001), and this difference persisted across INTERMACS profiles. UNOS status at transplant was more urgent for Impella than LVAD (p < 0.001). Transplant surgery following Impella support required shorter cardiopulmonary bypass time (181 vs. 219 min, p < 0.001) and resulted in lower postoperative vasoactive-inotropic requirements (7.9 vs. 13, p = 0.003). No patients in the Impella group died or were delisted while awaiting transplant, whereas 5 LVAD patients (26%) died or were removed due to LVAD complications (p < 0.001). Conclusions: Our data demonstrates that the use of the Impella 5.5 as BTT was associated with significantly shorter waitlist time, higher transplantation rates, reduced perioperative morbidity, and lower postoperative vasoactive support compared with durable LVAD as BTT. These benefits were achieved despite a higher severity of illness at transplantation in the Impella cohort.

Heart transplantation is a well-established treatment for end-stage heart failure, but many patients present in poor physical condition, complicating outcomes. The Impella 5.5 device, used in cardiogenic shock, may support pretransplant rehabilitation by stabilizing organ function and promoting functional improvement. This retrospective cohort study assessed the relationship between functional status, measured by standardized Activity Measure for Post-Acute Care Basic Mobility (AM-PAC) scores, and days alive outside the hospital within 30 days post-transplant (DAOH-30). Patients who received Impella 5.5 support before transplantation between January 2019 and October 2023 were included, excluding those without AM-PAC scores within 24 hours pretransplant. Among 65 patients, the median DAOH-30 was 15 days (interquartile range [IQR], 8–19). Higher pretransplant standardized AM-PAC scores correlate with increased DAOH-30 (adjusted coefficient 0.3; 95% confidence interval [CI] = 0.01–0.6; p = 0.04), as did AM-PAC score improvement during rehabilitation (adjusted coefficient 0.35; 95% CI = 0.01–0.6; p = 0.04). Extended rehabilitation was associated with greater functional gains. These findings suggest that better pretransplant functional status and rehabilitation-related improvements were associated with increased DAOH-30. The Impella 5.5 device facilitates rehabilitation and may enhance post-transplant outcomes. Further research should refine strategies to optimize rehabilitation and recovery in this high-risk population.

BACKGROUND: A preservation system, the Organ Care System (OCS; TransMedics) uses normothermic pulsatile perfusion during organ transport for heart transplantation. This system has demonstrated favorable outcomes in hearts recovered from extended-criteria donors after brain death (DBD) and donors after circulatory death (DCD). METHODS: The OCS Heart Perfusion Registry collects data on US heart transplantations using the OCS, static cold storage (SCS), or thoracoabdominal normothermic regional perfusion (NRP) and donor hearts recovered from DBD or DCD donors. We analyzed donor and recipient characteristics and posttransplantation outcomes in patients transplanted with OCS donor hearts (either DBD or DCD) compared with SCS hearts, and with OCS hearts from DCD donors compared with those recovered with NRP followed by SCS. Propensity score matching was used in survival analyses to adjust for differences among recipient characteristics. RESULTS: Between 2021 and 2023, 3225 consecutive heart transplantations enrolled from 56 centers were analyzed in the Heart Perfusion Registry. The OCS was used in 854 of 3225 heart transplantations (26.4%), among which 340 (39.8%) were DBD and 514 (60.2%) were DCD donors, whereas 2174 DBD donors were recovered with SCS and another 197 DCD donors with NRP techniques. The OCS-DBD group experienced a greater number of organ offer refusals before final acceptance (13 versus 6; Wilcoxon rank sum, P <0.001) and a longer transport distance (667 miles versus 232 miles; Wilcoxon rank sum, P <0.001) compared with SCS-DBD. Survival at 12 months was similar between the 2 groups (89.9% for OCS-DBD versus 90.6% for SCS-DBD; marginal Cox model, P =0.54). Among the OCS-DCD and SCS-DBD groups, survival at 12 months was also similar (91.0% versus 92.5%, respectively; marginal Cox model, P =0.32). The OCS-DCD and NRP-DCD groups demonstrated similar survival (91.0% versus 91.7%, respectively; log rank, P =0.63), although the transport distance was longer in OCS-DCD compared with DCD with NRP followed by SCS (400 miles versus 223 miles; Wilcoxon rank sum, P <0.001). By 2023, 90% of all OCS donor management and recovery was performed with dedicated organ recovery teams. CONCLUSIONS: We demonstrate that real-world implementation of the OCS for DBD donors (using predominantly a dedicated recovery team) is associated with expanded donor criteria, longer transport distance, and excellent posttransplantation outcomes. In OCS-DCD donors, outcomes parallel those of donors recovered with NRP-DCD and compare favorably with DBD donor organs.

AbstractBackgroundThe prognosis in patients with advanced cardiac amyloidosis (CA) remains poor.ObjectivesWe sought to describe survival post heart transplantation (HT) in amyloid compared with non‐amyloid recipients, highlight waitlist times within the new allocation system across three Organ Procurement and Transplantation Network (OPTN) regions, and describe multiorgan transplantation (MOT) in hereditary amyloidosis.MethodsThis is a retrospective review of end‐stage CA patients who underwent HT at Mayo Clinic from January 2007 to December 2020. Wait time was compared in the new versus old OPTN allocation era starting December 18, 2018 by Wilcoxon rank sum test. All‐cause mortality for those with and without CA was compared using Kaplan–Meier estimates with log rank analysis, censoring December 16, 2022.ResultsFifty‐five patients with CA underwent HT between 2007 and 2020, 8 light chain amyloidosis (AL) (14.5%), 28 hereditary transthyretin (ATTRv) (50.9%), 17 wildtype transthyretin (ATTRwt) (30.9%), and 2 hereditary apolipoprotein A1 (AApoA1) amyloidosis patients (3.6%). No significant difference in overall survival post‐transplant was seen in amyloid compared with non‐amyloid (p = 0.816). Median time to HT was shorter in the new system, 45 days (IQR 24, 78) versus 174 days (IQR 76.5, 483.5), p = 0.006. There was a decline in MOT in hereditary amyloidosis over time with the concomitant rise in disease‐targeted therapies.ConclusionsHT survival in CA patients was similar to non‐amyloid patients. The new allocation system benefits this cohort with shorter wait times. There is less MOT in hereditary amyloidosis with increased utilization of disease‐targeted therapy.

Background: The Society for Cardiovascular Angiography and Interventions (SCAI) staging system is a crucial tool for categorizing cardiogenic shock (CS) and guiding interventions. SCAI staging is traditionally static and may not capture dynamic changes. We evaluated the impact of axillary mechanical circulatory support and SCAI stage transition in patients with CS supported until heart transplantation. Methods: A retrospective study was conducted on patients with Impella support as bridge to transplant. Hemodynamic and vasoactive support parameters were collected and SCAI stage recorded at baseline and after 72 hours. Results: 36 patients were included in the analysis. The median age was 61 (52 – 68) with an EF of 19% (15-26%) (Figure 1). Before Impella placement, the distribution of patients across SCAI stages was as follows: 19 patients in SCAI B, 8 patients in SCAI C, and 9 patients in SCAI D. After 72 hours of Impella support, 7 patients initially classified as SCAI C transitioned to SCAI B with one deteriorating to SCAI D (Figure 2). Patients in SCAI D showed notable improvement, with 8 out of 9 patients transitioning to SCAI B. For patients initially SCAI B, RA changed from 10 to 11 mmHg, and PCWP decreased from 23 to 17 mmHg. The Fick CI increased from 2.53 to 3.02 L/min/m 2 (p=0.04), and the vasoactive inotropic score (VIS) decreased from 7.5-5.0 (p=0.05). In patients initially classified as SCAI C, RA pressure decreased from 13 to 8 mmHg, and PCWP reduced from 32 to 30 mmHg. The Fick CI improved from 1.79 to 2.61 L/min/m 2 (p<0.001), while the VIS decreased from 9.2 to 6.3 (p=0.004). For those initially in SCAI D, RA pressure reduced from 8 to 5 mmHg, and PCWP decreased from 27 to 18 mmHg. The Fick CI increased from 1.55 to 2.67 L/min/m 2 (p=0.002), and the VIS was notably reduced from 4.75 to 3.8 (p=0.36). All 36 patients survived to heart transplantation without major pre-transplant complications. Conclusion: SCAI stage C-E mortality ranges from 25 – 50% or worse. Implementing Impella 5.5 support reduced SCAI severity and may be associated with improved survival in HFCS. We demonstrated lower VIS after Impella 5.5 and a 100% event free survival to heart transplantation despite a 25% baseline SCAI D cohort. Larger data should be evaluated to assess this trend.

Background: In the landscape of organ transplantation, heart transplantation stands as a life-saving procedure for patients with end-stage heart failure. Comprehensive analyses of transplant programs are imperative to optimize outcomes and understand the complexities. Hypothesis: This study hypothesizes that an increasing trend of heart transplant service and short-term mechanical circulatory support (STMCS) is the bridge to transplant; the UNOS (United Network for Organ Sharing) guideline positively impacts STMCS utilization. Even with the standard of care, there might be a disparity in receiving care in terms of gender and race. Goal/ Aims: By examining this center's collective experience, this research provides valuable insights into the evolving landscape of heart transplantation, ultimately contributing to advancements in patient care and transplant policy. Methods: This retrospective cohort study includes heart transplant patients in a single large transplant center. For statistical analysis, Cox regression, Mann-Whitney test, Kruskal Wallis, and Chi-Square test were used in IBM SPSS 25. Result: Trends: This retrospective study covering 2010 to 2022 comprehensively analyzed 1513 heart transplant patients. The cohort consisted of 1071 (70.78%) males and 442 (29.21%) females, 31.9% were bridged through STMCS. 76.7% of Caucasian and 16.1% were African American.The mean utilization of STMCS was 20.08% before the UNOS policy change, increasing to 53.81% after that (p < 0.001). Disparity Analysis: There was a statistically significant difference in STMCS utilization between white and black patients (p= 0.008) but no difference in between obese and non-obese cohorts (P=0.362).Wait time was similar among the genders (p=0.161) and different races (p=0.302). Survival Analysis: There is a significant survival discrepancy between patients bridged through MCS and those without STMCS(p< 0.001). However, yearly trend analysis showed an evolving survival trajectory favoring STMCS users. There are statistically significant survival differences among whites and blacks (P =0.008) but similar among the genders (p=0.589). Summary: The study reveals significant changes in the trend of transplants regarding STMCS utilization since the UNOS guideline. There are substantial differences in survival between STMCS vs. non-STMCS groups and among the races.There was a significant difference in STMCS utilization among the races.

Abstract Aims Hospitalized patients with heart failure (HF) are a heterogeneous population, with multiple phenotypes proposed. Prior studies have not examined the biological phenotypes of critically ill patients with HF admitted to the contemporary cardiac intensive care unit (CICU). We aimed to leverage unsupervised machine learning to identify previously unknown HF phenotypes in a large and diverse cohort of patients with HF admitted to the CICU. Methods We screened 6008 Mayo Clinic CICU patients with an admission diagnosis of HF from 2007 to 2018 and included those without missing values for common laboratory tests. Consensus k-means clustering was performed based on 10 common admission laboratory values (potassium, chloride, anion gap, blood urea nitrogen, haemoglobin, red blood cell distribution width, mean corpuscular volume, platelet count, white blood cell count and neutrophil-to-lymphocyte ratio). In-hospital mortality was evaluated using logistic regression, and 1 year mortality was evaluated using Cox proportional hazard models after multivariable adjustment. Results Among 4877 CICU patients with HF who had complete admission laboratory data (mean age 69.4 years, 38.4% females), we identified five clusters with divergent demographics, comorbidities, laboratory values, admission diagnoses and use of critical care therapies. We labelled these clusters based on the characteristic laboratory profile of each group: uncomplicated (25.7%), iron-deficient (14.5%), cardiorenal (18.4%), inflamed (22.3%) and hypoperfused (19.2%). In-hospital mortality occurred in 10.7% and differed between the phenotypes: uncomplicated, 2.7% (reference); iron-deficient, 8.1% [adjusted odds ratio (OR) 2.18 (1.38–3.48), P &lt; 0.001]; cardiorenal, 10.3% [adjusted OR 2.11 (1.37–3.32), P &lt; 0.001]; inflamed, 12.5% [adjusted OR 1.79 (1.18–2.76), P = 0.007]; and hypoperfused, 21.9% [adjusted OR 4.32 (2.89–6.62), P &lt; 0.001]. These differences in mortality between phenotypes were consistent when patients were stratified based on demographics, aetiology, admission diagnoses, mortality risk scores, shock severity and systolic function. One-year mortality occurred in 31.5% and differed between the phenotypes: uncomplicated, 11.9% (reference); inflamed, 26.8% [adjusted hazard ratio (HR) 1.56 (1.27–1.92), P &lt; 0.001]; iron-deficient, 33.8% [adjusted HR 2.47 (2.00–3.04), P &lt; 0.001]; cardiorenal, 41.2% [adjusted HR 2.41 (1.97–2.95), P &lt; 0.001]; and hypoperfused, 52.3% [adjusted HR 3.43 (2.82–4.18), P &lt; 0.001]. Similar findings were observed for post-discharge 1 year mortality. Conclusions Unsupervised machine learning clustering can identify multiple distinct clinical HF phenotypes within the CICU population that display differing mortality profiles both in-hospital and at 1 year. Mortality was lowest for the uncomplicated HF phenotype and highest for the hypoperfused phenotype. The inflamed phenotype had comparatively higher in-hospital mortality yet lower post-discharge mortality, suggesting divergent short-term and long-term prognosis.

Abstract Background Stiff left atrial syndrome is a well-established cause of heart failure symptoms. A parallel entity involving the right atrium (RA) has not previously been described. We present a case of refractory right heart failure (RHF) 12 years following orthotopic heart transplantation. Case summary Patient underwent annuloplasty ring placement for severe tricuspid regurgitation in 2018 and kidney transplantation in 2020. The use of multimodality imaging and a multidisciplinary approach suggested a stiff RA as a potential etiology to refractory symptoms. Redo-heart and kidney transplantation in March 2021 led to the resolution of symptoms without recurrence. Discussion We propose stiff right atrial syndrome that may need to be considered in the setting of refractory RHF primarily suggested by significant right atrial enlargement and restrictive physiology.