Aims In spite of current medical treatment approaches, mortality of chronic heart failure (HF) remains high and novel treatment modalities are thus urgently needed. A recent theory proposes a possible impact of the intestinal microbiome on the incidence and clinical course of heart failure. This study sought to systematically investigate, if there are specific changes of the intestinal microbiome in heart failure patients. Methods and results The intestinal microbiome of 20 patients with heart failure with reduced ejection fraction due to ischemic or dilated cardiomyopathy was investigated by applying high‐throughput sequencing of the bacterial 16S rRNA gene. Microbial profiles were compared to those of matched controls in which heart failure was ruled out by clinical assessment and NT‐proBNP serum levels (n = 20). According to the Shannon diversity index (which measures the intra‐individual alpha‐diversity) based on the distribution of operational taxonomic units (OTUs), HF cases showed a nominally significantly lower diversity index compared to controls (P_nom. = 0.01), and testing for genera abundance showed a tendency towards a decreased alpha diversity of HF patients. Beta‐diversity measures (inter‐individual diversity) revealed a highly significant separation of HF cases and controls, (e.g. P_{weighted UniFracv} = 0.004). Assessing the individual abundance of core measurable microbiota (CMM), a significant decrease of Coriobacteriaceae, Erysipelotrichaceae and Ruminococcaceae was observed on the family level. In line with that, Blautia, Collinsella, uncl. Erysipelotrichaceae and uncl. Ruminococcaceae showed a significant decrease in HF cases compared to controls on the genus level. Conclusions Heart failure patients showed a significantly decreased diversity of the intestinal microbiome as well as a downregulation of key intestinal bacterial groups. Our data point to an altered intestinal microbiome as a potential player in the pathogenesis and progression of heart failure.

Introduction: Inflammatory, autoimmune and metabolic disorders have been associated with alterations in osteopontin (OPN) serum levels. Furthermore, elevated serum levels of OPN were reported from a small cohort of patients with sepsis. We therefore analyzed OPN serum concentrations in a large cohort of critically ill medical patients. Methods: A total of 159 patients (114 with sepsis, 45 without sepsis) were studied prospectively upon admission to the medical intensive care unit (ICU) as well as after 3 days of ICU treatment and compared to 50 healthy controls. Clinical data, various laboratory parameters as well as investigational inflammatory cytokine profiles were assessed. Patients were followed for approximately 1 year. Results: We found significantly elevated serum levels of OPN at admission to the ICU and after 3 days of treatment in critically ill patients compared to healthy controls. OPN concentrations were related to disease severity and significantly correlated with established prognosis scores and classical as well as experimental markers of inflammation and multi-organ failure. In the total cohort, OPN levels decreased from admission to day 3 of ICU treatment. However, persistently elevated OPN levels at day 3 of ICU treatment were a strong independent predictor for an unfavorable prognosis, with similar or better diagnostic accuracy than routinely used markers of organ failure or prognostic scoring systems such as SAPS2 or APACHE II score. Conclusions: Persistently elevated OPN serum concentrations are associated with an unfavourable outcome in patients with critical illness, independent of the presence of sepsis. Besides a possible pathogenic role of OPN in critical illness, our study indicates a potential value for OPN as a prognostic biomarker in critically ill patients during the early course of ICU treatment.

Aims The prognosis and quality of life of heart failure patients is determined to a significant extent by co-morbidities. New data suggest that heart failure may be associated with an increased incidence of cancer. The present retrospective study investigates this association in a large collective of outpatients with heart failure. Methods and results This retrospective cohort study assessed the incidence of cancer in patients with an initial diagnosis of heart failure and a matched non-heart failure cohort in 1274 general practices in Germany between January 2000 and December 2018. The study is based on the Disease Analyser database (IQVIA), which contains drug prescriptions, diagnoses, and basic medical and demographic data. Hazard regression models were used to study the association between heart failure and the incidences of different cancers. A total of 100 124 patients with heart failure and 100 124 patients without heart failure were included in the analysis. Patients were matched individually by sex, age, diabetes, obesity, and yearly consultation frequency. Within the 10 year observation period, 25.7% of patients with heart failure and 16.2% of patients without heart failure had been diagnosed with cancer (log-rank P < 0.001). These proportions were 28.6% vs. 18.8% in female and 23.2% vs. 13.8% in male patients. Heart failure was significantly associated with the incidence of cancer [hazard ratio (HR), 95% confidence interval: 1.76, 1.71–1.81; P < 0.001 in total; HR: 1.85, 1.77–1.92, P < 0.001 in women; HR: 1.69, 1.63–1.76, P < 0.001 in men]. A significant association was found between heart failure and all cancer sites assessed. The strongest association was observed for cancer of lip, oral cavity, and pharynx (HR: 2.10, 95% confidence interval: 1.66–2.17; P < 0.001), followed by respiratory organs (HR: 1.91, 1.74–2.10; P < 0.001) and genital organs of female patients (HR: 1.86, 1.56–2.17; P < 0.001). The association for skin tumours was 1.83 (1.72–1.94; P < 0.001), for cancer of lymphoid and haematopoietic tissue 1.77 (1.63–1.91; P < 0.001), for cancer of the digestive tract 1.75 (1.64–1. 87; P < 0.001), for breast cancer 1.67 (1.52–1.84; P < 0.001), for cancer of the genitourinary tract 1.64 (1.48–1.81; P < 0.001), and for male genital organ cancer 1.52 (1.40–1.66; P < 0.001). Conclusions Our study indicates that heart failure patients experience a significantly higher incidence of cancer during the course of the disease.

Aims: One of the most important complications of heart transplantation is organ rejection, which is diagnosed on endomyocardial biopsies by pathologists. Computer-based systems could assist in the diagnostic process and potentially improve reproducibility. Here, we evaluated the feasibility of using deep learning in predicting the degree of cellular rejection from pathology slides as defined by the International Society for Heart and Lung Transplantation (ISHLT) grading system. Methods and results: We collected 1079 histopathology slides from 325 patients from three transplant centres in Germany. We trained an attention-based deep neural network to predict rejection in the primary cohort and evaluated its performance using cross-validation and by deploying it to three cohorts. For binary prediction (rejection yes/no), the mean area under the receiver operating curve (AUROC) was 0.849 in the cross-validated experiment and 0.734, 0.729, and 0.716 in external validation cohorts. For a prediction of the ISHLT grade (0R, 1R, 2/3R), AUROCs were 0.835, 0.633, and 0.905 in the cross-validated experiment and 0.764, 0.597, and 0.913; 0.631, 0.633, and 0.682; and 0.722, 0.601, and 0.805 in the validation cohorts, respectively. The predictions of the artificial intelligence model were interpretable by human experts and highlighted plausible morphological patterns. Conclusion: We conclude that artificial intelligence can detect patterns of cellular transplant rejection in routine pathology, even when trained on small cohorts.

The prognosis of heart failure (HF) patients is determined to a decisive extent by comorbidities. The present study investigates the association between a broad spectrum of diseases and the occurrence of HF in a large collective of outpatients. This retrospective case control study assessed the prevalence of 37 cardiac and extracardiac diseases in patients with an initial diagnosis of heart failure (ICD-10: I50) in 1,274 general practices in Germany between January 2005 and December 2019. The study is based on the Disease Analyzer database (IQVIA), which contains drug prescriptions, diagnoses, and basic medical and demographic data. Patients with and without heart failure were matched by sex, age, and index year. Hazard regression models were conducted to evaluate the association between different disease entities and heart failure. The present study included 162,246 patients with heart failure and 162,246 patients without heart failure. Mean age [SD] was 73.7 [12.1] years; 52.6% were women. Out of 37 predefined diagnoses, 36 were more prevalent in HF patients. The highest prevalence was primary hypertension (63.4% in HF patients vs. 53.3% in controls, p < 0.001) followed by lipid metabolism disorders (34.6% in HF patients vs. 29.1% in HF patients p < 0.001) and diabetes mellitus type II (32.2% in HF patients vs. 25.2% in controls, p < 0.001). In the regression analysis, 19 diseases were significantly associated with heart failure. Non-cardiovascular diagnoses strongly associated with HF were obesity (HR = 1.46), chronic bronchitis and COPD (HR = 1.41), gout (HR: 1.41), and chronic kidney disease (HR = 1.27). In the present study, we identified a variety of cardiac and extracardiac diseases associated with heart failure. Our data underscore the immense importance of comorbidities, even as early as at the stage of initial diagnosis of heart failure.