Thirty years of heart transplantation at the University Medical Centre Utrecht

ECPELLA as a bridge-to-decision in refractory cardiogenic shock: a single-centre experience

BACKGROUND

In refractory cardiogenic shock, temporary mechanical support (tMCS) may be crucial for maintaining tissue perfusion and oxygen delivery. tMCS can serve as a bridge-to-decision to assess eligibility for left ventricular assist device (LVAD) implantation or heart transplantation, or as a bridge-to-recovery. ECPELLA is a novel tMCS configuration combining venoarterial extracorporeal membrane oxygenation with Impella. The present study presents the clinical parameters, outcomes, and complications of patients supported with ECPELLA.

METHODS

All patients supported with ECPELLA at University Medical Centre Utrecht between December 2020 and August 2023 were included. The primary outcome was 30-day mortality, and secondary outcomes were LVAD implantation/heart transplantation and safety outcomes.

RESULTS

Twenty patients with an average age of 51 years, and of whom 70% were males, were included. Causes of cardiogenic shock were acute heart failure (due to acute coronary syndrome, myocarditis, or after cardiac surgery) or chronic heart failure, respectively 70 and 30% of cases. The median duration of ECPELLA support was 164 h (interquartile range 98-210). In 50% of cases, a permanent LVAD was implanted. Cardiac recovery within 30 days was seen in 30% of cases and 30-day mortality rate was 20%. ECPELLA support was associated with major bleeding (40%), haemolysis (25%), vascular complications (30%), kidney failure requiring replacement therapy (50%), and Impella failure requiring extraction (15%).

CONCLUSION

ECPELLA can be successfully used as a bridge to LVAD implantation or as a bridge-to-recovery in patients with refractory cardiogenic shock. Despite a significant number of complications, 30-day mortality was lower than observed in previous cohorts.

Acute Kidney Injury After Heart Transplantation: Risk Factors and Clinical Outcomes

OBJECTIVE

Acute kidney injury (AKI) requiring renal-replacement therapy (RRT) after heart transplantation (OHT) is common and impairs outcomes. This study aimed to identify independent donor and recipient risk factors associated with RRT after OHT.

DESIGN

A retrospective data analysis.

SETTING

Data were collected from clinical routines in a maximum-care university hospital.

PARTICIPANTS

Patients who underwent OHT.

INTERVENTIONS

The authors retrospectively analyzed data from 264 patients who underwent OHT between 2012 and 2021; 189 patients were eligible and included in the final analysis.

MEASUREMENTS AND MAIN RESULTS

The mean age was 48.0 ± 12.3 years, and 71.4% of patients were male. Ninety (47.6%) patients were on long-term mechanical circulatory support (lt-MCS). Posttransplant AKI with RRT occurred in 123 (65.1%) patients. In a multivariate analysis, preoperative body mass index >25 kg/m² (odds ratio [OR] 4.74, p < 0.001), elevated preoperative creatinine levels (OR for each mg/dL increase 3.44, p = 0.004), administration of red blood cell units during transplantation procedure (OR 2.31, p = 0.041) and ischemia time (OR for each hour increase 1.77, p = 0.004) were associated with a higher incidence of RRT. The use of renin-angiotensin-aldosterone system blockers before transplantation was associated with a reduced risk of RRT (OR 0.36, p = 0.013). The risk of mortality was 6.9-fold higher in patients who required RRT (hazard ratio 6.9, 95% CI: 2.1-22.6 p = 0.001). Previous lt-MCS, as well as donor parameters, were not associated with RRT after OHT.

CONCLUSIONS

The implementation of guideline-directed medical therapy, weight reduction, minimizing ischemia time (ie, organ perfusion systems, workflow optimization), and comprehensive patient blood management potentially influences renal function and outcomes after OHT.

Diagnostic and Prognostic Value of a TDI-Derived Systolic Wall Motion Analysis as a Screening Modality for Allograft Rejection after Heart Transplantation

Background: Despite the risk for complications, allograft surveillance after orthotopic heart transplantation (OHT) is performed by cardiac catheterization and biopsies. We investigated the diagnostic and prognostic value of a TDI-derived systolic wall motion analysis of the posterobasal wall of the left ventricle (Sm) as a screening modality in OHT aftercare. Methods: We examined data of 210 eligible patients who underwent OHT between 2010 and 2020. Forty-four patients who had died within the initial hospital stay were excluded. For 166 patients, baseline and follow-up data were analyzed. The mean age at OHT was 46.2 (±11.4) years; 76.5% were male. Results: Within the observational period, 22 (13.3%) patients died. In total, 170 episodes of acute cellular or humoral rejections occurred (84 ISHLT1R; 13 ISHLT2R; 8 ISHLT3R; 65 AMR), and 29 catheterizations revealed cardiac allograft vasculopathy (5 CAV1; 4 CAV2; 20 CAV3). Individual Sm radial/longitudinal remained stable within the follow-up period (11.5 ± 2.2 cm/s; 10.9 ± 2.1 cm/s). Patients with acute rejections and CAV3 showed significant Sm radial/longitudinal reductions (AMR1: 1.6 ± 1.9 cm/s, confidence interval (CI) 0.77–0.243, p < 0.001; 1.8 ± 2.0 cm/s, CI 0.92–0.267, p < 0.001. ISHLT1R: 1.7 ± 1.8 cm/s, CI 1.32–2.08, p < 0.001; 2.0 ± 1.6 cm/s, CI 1.66–2.34, p < 0.001. CAV3: 1.3 ± 2.5 cm/s, CI 0.23–2.43, p < 0.017; 1.4 ± 2.8 cm/s, CI 0.21–2.66, p < 0.021). Lower Sm was associated with a threefold increase in all-cause mortality (hazard ratio (HR) 3.24, CI 1.2–8.76, p = 0.020; HR 2.92, CI 1.19–7.18, p = 0.019). Overall, Sm-triggered surveillance led to 0.75 invasive diagnostics per patient post-OHT year. Conclusions: Sm remained stable in the post-OHT course. Reductions indicated ISHLT1R, AMR1 and CAV3 and were associated with higher all-cause mortality. Sm-triggered surveillance may be referred to as a safe, high-yield screening modality in OHT aftercare.

Diagnosis and Risk Prediction of Dilated Cardiomyopathy in the Era of Big Data and Genomics

Dilated cardiomyopathy (DCM) is a leading cause of heart failure and life-threatening ventricular arrhythmias (LTVA). Work-up and risk stratification of DCM is clinically challenging, as there is great heterogeneity in phenotype and genotype. Throughout the last decade, improved genetic testing of patients has identified genotype-phenotype associations and enhanced evaluation of at-risk relatives leading to better patient prognosis. The field is now ripe to explore opportunities to improve personalised risk assessments. Multivariable risk models presented as "risk calculators" can incorporate a multitude of clinical variables and predict outcome (such as heart failure hospitalisations or LTVA). In addition, genetic risk scores derived from genome/exome-wide association studies can estimate an individual's lifetime genetic risk of developing DCM. The use of clinically granular investigations, such as late gadolinium enhancement on cardiac magnetic resonance imaging, is warranted in order to increase predictive performance. To this end, constructing big data infrastructures improves accessibility of data by using electronic health records, existing research databases, and disease registries. By applying methods such as machine and deep learning, we can model complex interactions, identify new phenotype clusters, and perform prognostic modelling. This review aims to provide an overview of the evolution of DCM definitions as well as its clinical work-up and considerations in the era of genomics. In addition, we present exciting examples in the field of big data infrastructures, personalised prognostic assessment, and artificial intelligence.

Waiting list mortality and the potential of donation after circulatory death heart transplantations in the Netherlands

Background

With more patients qualifying for heart transplantation (HT) and fewer hearts being transplanted, it is vital to look for other options. To date, only organs from brain-dead donors have been used for HT in the Netherlands. We investigated waiting list mortality in all Dutch HT centres and the potential of donation after circulatory death (DCD) HT in the Netherlands.

Methods

Two different cohorts were evaluated. One cohort was defined as patients who were newly listed or were already on the waiting list for HT between January 2013 and December 2017. Follow-up continued until September 2018 and waiting list mortality was calculated. A second cohort of all DCD donors in the Netherlands (lung, liver, kidney and pancreas) between January 2013 and December 2017 was used to calculate the potential of DCD HT.

Results

Out of 395 patients on the waiting list for HT, 196 (50%) received transplants after a median waiting time of 2.6 years. In total, 15% died while on the waiting list before a suitable donor heart became available. We identified 1006 DCD donors. After applying exclusion criteria and an age limit of 50 years, 122 potential heart donors remained. This number increased to 220 when the age limit was extended to 57 years.

Conclusion

Waiting list mortality in the Netherlands is high. HT using organs from DCD donors has great potential in the Netherlands and could lead to a reduction in waiting list mortality. Cardiac screening will eventually determine the true potential.

The role of long-term mechanical circulatory support in patients with advanced heart failure

In patients with end-stage heart failure, advanced therapies such as heart transplantation and long-term mechanical circulatory support (MCS) with a left ventricular assist device (LVAD) have to be considered. LVADs can be implanted as a bridge to transplantation or as an alternative to heart transplantation: destination therapy. In the Netherlands, long-term LVAD therapy is gaining importance as a result of increased prevalence of heart failure together with a low number of heart transplantations due to shortage of donor hearts. As a result, the difference between bridge to transplantation and destination therapy is becoming more artificial since, at present, most patients initially implanted as bridge to transplantation end up receiving extended LVAD therapy. Following LVAD implantation, survival after 1, 2 and 3 years is 83%, 76% and 70%, respectively. Quality of life improves substantially despite important adverse events such as device-related infection, stroke, major bleeding and right heart failure. Early referral of potential candidates for long-term MCS is of utmost importance and positively influences outcome. In this review, an overview of the indications, contraindications, patient selection, clinical outcome and optimal time of referral for long-term MCS is given.

Ventricular assist device implantation in patients with a failing systemic right ventricle: a call to expand current practice

Ventricular assist device (VAD) implantation is an established treatment modality for patients with end-stage heart failure, and improves symptoms and survival. In the Netherlands, it is not yet routinely considered in patients with congenital heart disease and failing systemic right ventricle (SRV). Recently, a VAD was implanted in 2 SRV patients, one who underwent a Mustard procedure during infancy for transposition of the great arteries (male, 47 years old) and one with a congenitally corrected transposition of the great arteries (male, 54 years old). The first patient is doing well >1 year after implantation; the second patient will be discharged home soon. These examples and other reports demonstrate the feasibility of adopting VAD implantation into routine care for SRV failure. In conclusion, patients with SRV failure may be suitable candidates for VAD implantation: they are relatively young, usually have a preserved subpulmonary left ventricular function, and their specific anatomical and physiological characteristics often make them unsuitable for cardiac transplantation. Therefore it is important to recognise the possibility of VAD implantation early in the process of SRV failure, and to timely refer these patients to a heart failure clinic with experience in VAD implantation in this group of patients for optimisation, screening, and implantation.

Applying genomics in heart transplantation

While advances in patient care and immunosuppressive pharmacotherapies have increased the lifespan of heart allograft recipients, there are still significant comorbidities post-transplantation and 5-year survival rates are still significant, at approximately 70%. The last decade has seen massive strides in genomics and other omics fields, including transcriptomics, with many of these advances now starting to impact heart transplant clinical care. This review summarizes a number of the key advances in genomics which are relevant for heart transplant outcomes, and we highlight the translational potential that such knowledge may bring to patient care within the next decade.

Systems analysis of dilated cardiomyopathy in the next generation sequencing era

Dilated cardiomyopathy (DCM) is a form of severe failure of cardiac muscle caused by a long list of etiologies ranging from myocardial infarction, DNA mutations in cardiac genes, to toxics. Systems analysis integrating next-generation sequencing (NGS)-based omics approaches, such as the sequencing of DNA, RNA, and chromatin, provide valuable insights into DCM mechanisms. The outcome and interpretation of NGS methods can be affected by the localization of cardiac biopsy, level of tissue degradation, and variable ratios of different cell populations, especially in the presence of fibrosis. Heart tissue composition may even differ between sexes, or siblings carrying the same disease causing mutation. Therefore, before planning any experiments, it is important to fully appreciate the complexities of DCM, and the selection of samples suitable for given research question should be an interdisciplinary effort involving clinicians and biologists. The list of NGS omics datasets in DCM to date is short. More studies have to be performed to contribute to public data repositories and facilitate systems analysis. In addition, proper data integration is a difficult task requiring complex computational approaches. Despite these complications, there are multiple promising implications of systems analysis in DCM. By combining various types of datasets, for example, RNA-seq, ChIP-seq, or 4C, deep insights into cardiac biology, and possible biomarkers and treatment targets, can be gained. Systems analysis can also facilitate the annotation of noncoding mutations in cardiac-specific DNA regulatory regions that play a substantial role in maintaining the tissue- and cell-specific transcriptional programs in the heart. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Laboratory Methods and Technologies > Genetic/Genomic Methods Laboratory Methods and Technologies > RNA Methods.