Registro Español de Trasplante Cardiaco. XXXI Informe Oficial de la Asociación de Insuficiencia Cardiaca de la Sociedad Española de Cardiología

Introducción y objetivos Se presentan las características clínicas y los resultados de los trasplantes cardiacos realizados en España con la actualización correspondiente a 2019. Métodos Se describen las características clínicas y los resultados de los trasplantes cardiacos realizados en 2019, así como las tendencias de estos en el periodo 2010-2018. Resultados En 2019 se realizaron 300 trasplantes (8.794 desde 1984; 2.745 entre 2010 y 2019). Respecto a años previos, los cambios más llamativos son el descenso hasta el 38% de los trasplantes realizados en código urgente, y la consolidación en el cambio de asistencia circulatoria pretrasplante, con la práctica desaparición del balón de contrapulsación (0, 7%), la estabilización del uso del oxigenador extracorpóreo de membrana (9, 6%) y el aumento de los dispositivos de asistencia ventricular (29%). La supervivencia en el trienio 2016-2018 es similar a la del trienio 2013-2015 (p = 0, 34), y ambas mejores que la del trienio 2010-2012 (p = 0, 002 y p = 0, 01 respectivamente). Conclusiones Se mantienen estables tanto la actividad del trasplante cardiaco en España como los resultados en supervivencia en los últimos 2 trienios. Hay una tendencia a realizar menos trasplantes urgentes, la mayoría con dispositivos de asistencia ventricular. Introduction and objectives: The present report describes the clinical characteristics and outcomes of heart transplants in Spain and updates the data to 2019. Methods: We describe the clinical characteristics and outcomes of heart transplants performed in Spain in 2019, as well as trends in this procedure from 2010 to 2018. Results: In 2019, 300 transplants were performed (8794 since 1984; 2745 between 2010 and 2019). Compared with previous years, the most notable findings were the decreasing rate of urgent transplants (38%), and the consolidation of the type of circulatory support prior to transplant, with an almost complete disappearance of counterpulsation balloon (0.7%), stabilization in the use of extracorporeal membrane oxygenation (9.6%), and an increase in the use of ventricular assist devices (29.0%). Survival from 2016 to 2018 was similar to that from 2013 to 2015 (P = .34). Survival in both these periods was better than that from 2010 to 2012 (P = .002 and P = .01, respectively). Conclusions: Heart transplant activity has remained stable during the last few years, as have outcomes (in terms of survival). There has been a trend to a lower rate of urgent transplants and to a higher use of ventricular assist devices prior to transplant

Omecamtiv mecarbil in chronic heart failure with reduced ejection fraction, GALACTIC‐HF: baseline characteristics and comparison with contemporary clinical trials

Aims: The safety and efficacy of the novel selective cardiac myosin activator, omecamtiv mecarbil, in patients with heart failure with reduced ejection fraction (HFrEF) is tested in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC‐HF) trial. Here we describe the baseline characteristics of participants in GALACTIC‐HF and how these compare with other contemporary trials. Methods and Results: Adults with established HFrEF, New York Heart Association functional class (NYHA) ≥ II, EF ≤35%, elevated natriuretic peptides and either current hospitalization for HF or history of hospitalization/ emergency department visit for HF within a year were randomized to either placebo or omecamtiv mecarbil (pharmacokinetic‐guided dosing: 25, 37.5 or 50 mg bid). 8256 patients [male (79%), non‐white (22%), mean age 65 years] were enrolled with a mean EF 27%, ischemic etiology in 54%, NYHA II 53% and III/IV 47%, and median NT‐proBNP 1971 pg/mL. HF therapies at baseline were among the most effectively employed in contemporary HF trials. GALACTIC‐HF randomized patients representative of recent HF registries and trials with substantial numbers of patients also having characteristics understudied in previous trials including more from North America (n = 1386), enrolled as inpatients (n = 2084), systolic blood pressure < 100 mmHg (n = 1127), estimated glomerular filtration rate < 30 mL/min/1.73 m2 (n = 528), and treated with sacubitril‐valsartan at baseline (n = 1594). Conclusions: GALACTIC‐HF enrolled a well‐treated, high‐risk population from both inpatient and outpatient settings, which will provide a definitive evaluation of the efficacy and safety of this novel therapy, as well as informing its potential future implementation

Incidence, risk factors, and outcomes of Fusobacterium species bacteremia

Background: Fusobacterium species (spp.) bacteremia is uncommon and has been associated with a variety of clinical presentations. We conducted a retrospective, population based study to determine the relative proportion of species in this genus causing bacteremia and the risk factors for infection and adverse clinical outcomes. Methods: All cases of Fusobacterium spp. bacteremia detected at a regional microbiology laboratory serving outpatient and acute care for a population of approximately 1.3 million people over 11 years were identified from a computerized database. Clinical data on these cases was extracted from an administrative database and analyzed to determine underlying risk factors for and outcomes of infection. Results: There were 72 incident cases of Fusobacterium spp. bacteremia over the study period (0.55 cases/100,000 population per annum). F. nucleatum was the most frequent species (61%), followed by F. necrophorum (25%). F. necrophorum bacteremia occurred in a younger population without underlying comorbidities and was not associated with mortality. F. nucleatum bacteremia was found in an older population and was associated with underlying malignancy or receiving dialysis. Death occurred in approximately 10% of F. nucleatum cases but causality was not established in this study. Conclusions: Fusobacterium spp. bacteremia in our community is uncommon and occurs in approximately 5.5 cases per million population per annum. F. necrophorum occurred in an otherwise young healthy population and was not associated with any mortality. F. nucleatum was found primarily in older patients with chronic medical conditions and was associated with a mortality of approximately 10%. Bacteremias from other Fusobacterium spp. were rare.</p

ABATACEPT in rheumatoid arthritis with interstitial lung disease. A multicenter study of 181 patients

Background Interstitial Lung Disease (ILD) is a severe extraarticular manifestation of rheumatoid arthritis (RA). Objectives Our aim was to assess the efficacy of abatacept (ABA) in RA patients with ILD. Methods Retrospective multicenter study of RA patients with ILD treated with ABA. ILD was diagnosed by HRCT. We have analyzed the following variables: a) 1-point change the Modified Medical Research Council (MMRC); b) FVC improvement ≥10%; and improvement ≥10% in DLCO; c) radiological improvement in HRCT scan, d) changes in DAS28 score. Values were compared with baseline e) prednisone doses Results We studied 181 patients (94women/87 men) with ILD associated to RA. The follow-up was 12.1[6.2-24.1] months. The mean age was 64.54 ± 9.7 years. The median to progression of ILD was 12 [3-43.75] months. 81 patients were treated in monotherapy, 100 patients in combination therapy. The most frequent pattern was UIP 45,3%. The most of patients who did not have dyspnea remained asymptomatic. See results in Figure1. DAS28 also improved. We appreciate a decrease in the dose of prednisone compared to the initial dose. Conclusion ABA seems to be effective. However, should be verified in prospective and randomized studies

Pilot multi-omic analysis of human bile from benign and malignant biliary strictures: A machine-learning approach

Cholangiocarcinoma (CCA) and pancreatic adenocarcinoma (PDAC) may lead to the development of extrahepatic obstructive cholestasis. However, biliary stenoses can also be caused by benign conditions, and the identification of their etiology still remains a clinical challenge. We performed metabolomic and proteomic analyses of bile from patients with benign (n = 36) and malignant conditions, CCA (n = 36) or PDAC (n = 57), undergoing endoscopic retrograde cholangiopancreatography with the aim of characterizing bile composition in biliopancreatic disease and identifying biomarkers for the differential diagnosis of biliary strictures. Comprehensive analyses of lipids, bile acids and small molecules were carried out using mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (1H-NMR) in all patients. MS analysis of bile proteome was performed in five patients per group. We implemented artificial intelligence tools for the selection of biomarkers and algorithms with predictive capacity. Our machine-learning pipeline included the generation of synthetic data with properties of real data, the selection of potential biomarkers (metabolites or proteins) and their analysis with neural networks (NN). Selected biomarkers were then validated with real data. We identified panels of lipids (n = 10) and proteins (n = 5) that when analyzed with NN algorithms discriminated between patients with and without cancer with an unprecedented accurac

Pilot multi-omic analysis of human bile from benign and malignant biliary strictures: A machine-learning approach

Cholangiocarcinoma (CCA) and pancreatic adenocarcinoma (PDAC) may lead to the development of extrahepatic obstructive cholestasis. However, biliary stenoses can also be caused by benign conditions, and the identification of their etiology still remains a clinical challenge. We performed metabolomic and proteomic analyses of bile from patients with benign (n = 36) and malignant conditions, CCA (n = 36) or PDAC (n = 57), undergoing endoscopic retrograde cholangiopancreatography with the aim of characterizing bile composition in biliopancreatic disease and identifying biomarkers for the differential diagnosis of biliary strictures. Comprehensive analyses of lipids, bile acids and small molecules were carried out using mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (1H-NMR) in all patients. MS analysis of bile proteome was performed in five patients per group. We implemented artificial intelligence tools for the selection of biomarkers and algorithms with predictive capacity. Our machine-learning pipeline included the generation of synthetic data with properties of real data, the selection of potential biomarkers (metabolites or proteins) and their analysis with neural networks (NN). Selected biomarkers were then validated with real data. We identified panels of lipids (n = 10) and proteins (n = 5) that when analyzed with NN algorithms discriminated between patients with and without cancer with an unprecedented accurac