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SARS-CoV-2 is causing the coronavirus disease 2019 (COVID-19) pandemic, for which effective pharmacological therapies are needed. SARS-CoV-2 induces a shift of the host cell metabolism towards glycolysis, and the glycolysis inhibitor 2-deoxy-d-glucose (2DG), which interferes with SARS-CoV-2 infection, is under development for the treatment of COVID-19 patients. The glycolytic pathway generates intermediates that supply the non-oxidative branch of the pentose phosphate pathway (PPP). In this study, the analysis of proteomics data indicated increased transketolase (TKT) levels in SARS-CoV-2-infected cells, suggesting that a role is played by the non-oxidative PPP. In agreement, the TKT inhibitor benfooxythiamine (BOT) inhibited SARS-CoV-2 replication and increased the anti-SARS-CoV-2 activity of 2DG. In conclusion, SARS-CoV-2 infection is associated with changes in the regulation of the PPP. The TKT inhibitor BOT inhibited SARS-CoV-2 replication and increased the activity of the glycolysis inhibitor 2DG. Notably, metabolic drugs like BOT and 2DG may also interfere with COVID-19-associated immunopathology by modifying the metabolism of immune cells in addition to inhibiting SARS-CoV-2 replication. Hence, they may improve COVID-19 therapy outcomes by exerting antiviral and immunomodulatory effects.
Background: Patients with rare diseases (RDs) are often diagnosed too late or not at all. Clinical decision support systems (CDSSs) could support the diagnosis in RDs. The MIRACUM (Medical Informatics in Research and Medicine) consortium, which is one of four funded consortia in the German Medical Informatics Initiative, will develop a CDSS for RDs based on distributed clinical data from ten university hospitals. This qualitative study aims to investigate (1) the relevant organizational conditions for the operation of a CDSS for RDs when diagnose patients (e.g. the diagnosis workflow), (2) which data is necessary for decision support, and (3) the appropriate user group for such a CDSS.
Methods: Interviews were carried out with RDs experts. Participants were recruited from staff physicians at the Rare Disease Centers (RDCs) at the MIRACUM locations, which offer diagnosis and treatment of RDs.
An interview guide was developed with a category-guided deductive approach. The interviews were recorded on an audio device and then transcribed into written form. We continued data collection until all interviews were completed. Afterwards, data analysis was performed using Mayring’s qualitative content analysis approach.
Results: A total of seven experts were included in the study. The results show that medical center guides and physicians from RDC B-centers (with a focus on different RDs) are involved in the diagnostic process. Furthermore, interdisciplinary case discussions between physicians are conducted.
The experts explained that RDs exist which cannot be fully differentiated, but rather described only by their overall symptoms or findings: diagnosis is dependent on the disease or disease group. At the end of the diagnostic process, most centers prepare a summary of the patient case. Furthermore, the experts considered both physicians and experts from the B-centers to be potential users of a CDSS. The experts also have different experiences with CDSS for RDs.
Conclusions: This qualitative study is a first step towards establishing the requirements for the development of a CDSS for RDs. Further research is necessary to create solutions by also including the experts on RDs.
Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).
In Baden-Württemberg sind in dem 30-jährigen Zeitraum einschließlich dervorliegenden insgesamt fünf Fassungen der Roten Liste der gefährdeten Vogelarten erschienen, die jeweils auf den neuesten Stand der Erforschung der Vogelwelt Baden-Württembergs gebracht wurden. Die einzelnen Fassungen der Roten Liste sind 1973 (1. Fassung, Berthold, Ertel & Hölzinger 1974, 1975), 1977 (2. Fassung, Berthold, Ertel, Hölzinger, Kalchreuter & Ruge 1977), 1981 (3. Fassung, Hölzinger, Berthold, Kroymann & Ruge 1981), 1996 (4. Fassung, Hölzinger, Berthold, König & Mahler 1996) und 2007 (5., vorliegende Fassung) herausgegeben worden. In diesem über 30-jährigen Zeitraum wurden die Kriterien für die Roten Listen entsprechend dem Fortschritt der ornithologischen Forschung zunehmend mehr auf quantitative Grundlagen gestellt. Die Roten Listen waren und sind das Ergebnis systematischer und programmatisch orientierter Bestandsaufnahmen der Vogelwelt abseits emotionaler und naturschutzpolitischer Beurteilung.
The title compound, C37H67NO13·2C2H6OS·1.43H2O, is a macrolide antibiotic with better solubility and better dermal penetration abilities than erythromycin A itself. The asymmetric unit of this form contains one erythromycin A molecule, two dimethyl sulfoxide (DMSO) solvent molecules, a fully occupied water molecule and a partially occupied water molecule with an occupancy factor of 0.432 (11). The 14-membered ring of the erythronolide fragment has a conformation which differs considerably from that in erythromycin A dihydrate [Stephenson, Stowell, Toma, Pfeiffer & Byrn (1997[Stephenson, G. A., Stowell, J. G., Toma, P. H., Pfeiffer, R. R. & Byrn, S. R. (1997). J. Pharm. Sci. 86, 1239-1244.]). J. Pharm. Sci. 86, 1239–1244]. One of the two DMSO molecules is disordered over two orientations; the orientation depends on the presence or absence of the second, partially occupied, water molecule. In the crystal, erythromycin molecules are connected by O—H⋯O hydrogen bonds involving the hydroxy groups and the fully occupied water molecule to form layers parallel to (010). These layers are connected along the b-axis direction only by a possible hydrogen-bonding contact involving the partially occupied water molecule.
Antisynthetase syndrome (ASSD) is a rare clinical condition that is characterized by the occurrence of a classic clinical triad, encompassing myositis, arthritis, and interstitial lung disease (ILD), along with specific autoantibodies that are addressed to different aminoacyl tRNA synthetases (ARS). Until now, it has been unknown whether the presence of a different ARS might affect the clinical presentation, evolution, and outcome of ASSD. In this study, we retrospectively recorded the time of onset, characteristics, clustering of triad findings, and survival of 828 ASSD patients (593 anti-Jo1, 95 anti-PL7, 84 anti-PL12, 38 anti-EJ, and 18 anti-OJ), referring to AENEAS (American and European NEtwork of Antisynthetase Syndrome) collaborative group’s cohort. Comparisons were performed first between all ARS cases and then, in the case of significance, while using anti-Jo1 positive patients as the reference group. The characteristics of triad findings were similar and the onset mainly began with a single triad finding in all groups despite some differences in overall prevalence. The “ex-novo” occurrence of triad findings was only reduced in the anti-PL12-positive cohort, however, it occurred in a clinically relevant percentage of patients (30%). Moreover, survival was not influenced by the underlying anti-aminoacyl tRNA synthetase antibodies’ positivity, which confirmed that antisynthetase syndrome is a heterogeneous condition and that antibody specificity only partially influences the clinical presentation and evolution of this condition.
Simple Summary: Pseudoprogression detection in glioblastoma patients remains a challenging task. Although pseudoprogression has only a moderate prevalence of 10–30% following first-line treatment of glioblastoma patients, it bears critical implications for affected patients. Non-invasive techniques, such as amino acid PET imaging using the tracer O-(2-[18F]-fluoroethyl)-L-tyrosine (FET), expose features that have been shown to provide useful information to distinguish tumor progression from pseudoprogression. The usefulness of FET-PET in IDH-wildtype glioblastoma exclusively, however, has not been investigated so far. Recently, machine learning (ML) algorithms have been shown to offer great potential particularly when multiparametric data is available. In this preliminary study, a Linear Discriminant Analysis-based ML algorithm was deployed in a cohort of newly diagnosed IDH-wildtype glioblastoma patients (n = 44) and demonstrated a significantly better diagnostic performance than conventional ROC analysis. This preliminary study is the first to assess the performance of ML in FET-PET for diagnosing pseudoprogression exclusively in IDH-wildtype glioblastoma and demonstrates its potential.
Abstract: Pseudoprogression (PSP) detection in glioblastoma remains challenging and has important clinical implications. We investigated the potential of machine learning (ML) in improving the performance of PET using O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) for differentiation of tumor progression from PSP in IDH-wildtype glioblastoma. We retrospectively evaluated the PET data of patients with newly diagnosed IDH-wildtype glioblastoma following chemoradiation. Contrast-enhanced MRI suspected PSP/TP and all patients underwent subsequently an additional dynamic FET-PET scan. The modified Response Assessment in Neuro-Oncology (RANO) criteria served to diagnose PSP. We trained a Linear Discriminant Analysis (LDA)-based classifier using FET-PET derived features on a hold-out validation set. The results of the ML model were compared with a conventional FET-PET analysis using the receiver-operating-characteristic (ROC) curve. Of the 44 patients included in this preliminary study, 14 patients were diagnosed with PSP. The mean (TBRmean) and maximum tumor-to-brain ratios (TBRmax) were significantly higher in the TP group as compared to the PSP group (p = 0.014 and p = 0.033, respectively). The area under the ROC curve (AUC) for TBRmax and TBRmean was 0.68 and 0.74, respectively. Using the LDA-based algorithm, the AUC (0.93) was significantly higher than the AUC for TBRmax. This preliminary study shows that in IDH-wildtype glioblastoma, ML-based PSP detection leads to better diagnostic performance.
Background: The Catechol-O-methyltransferase (COMT) represents the key enzyme in catecholamine degradation. Recent studies suggest that the COMT rs4680 polymorphism is associated with the response to endogenous and exogenous catecholamines. There are, however, conflicting data regarding the COMT Met/Met phenotype being associated with an increased risk of acute kidney injury (AKI) after cardiac surgery. The aim of the current study is to prospectively investigate the impact of the COMT rs4680 polymorphism on the incidence of AKI in patients undergoing cardiac surgery.
Methods: In this prospective single center cohort study consecutive patients hospitalized for elective cardiac surgery including cardiopulmonary-bypass (CPB) were screened for participation. Demographic clinical data, blood, urine and tissue samples were collected at predefined time points throughout the clinical stay. AKI was defined according to recent recommendations of the Kidney Disease Improving Global Outcome (KDIGO) group. Genetic analysis was performed after patient enrolment was completed.
Results: Between April and December 2014, 150 patients were recruited. The COMT genotypes were distributed as follows: Val/Met 48.7%, Met/Met 29.3%, Val/Val 21.3%. No significant differences were found for demography, comorbidities, or operative strategy according to the underlying COMT genotype. AKI occurred in 35 patients (23.5%) of the total cohort, and no differences were evident between the COMT genotypes (20.5% Met/Met, 24.7% Val/Met, 25.0% Val/Val, p = 0.66). There were also no differences in the post-operative period, including ICU or in-hospital stay.
Conclusions: We did not find statistically significant variations in the risk for postoperative AKI, length of ICU or in-hospital stay according to the underlying COMT genotype.
Inositol, 1,2,3,4,5,6-hexahydroxycyclohexane, exists in nine stereoisomers with different crystal structures and melting points. In a previous paper on the relationship between the melting points of the inositols and the hydrogen-bonding patterns in their crystal structures [Simperler et al. (2006[Simperler, A., Watt, S. W., Bonnet, P. A., Jones, W. & Motherwell, W. D. S. (2006). CrystEngComm, 8, 589-600.]). CrystEngComm 8, 589], it was noted that although all inositol crystal structures known at that time contained 12 hydrogen bonds per molecule, their melting points span a large range of about 170 °C. Our preliminary investigations suggested that the highest melting point must be corrected for the effect of molecular symmetry, and that the three lowest melting points may need to be revised. This prompted a full investigation, with additional experiments on six of the nine inositols. Thirteen new phases were discovered; for all of these their crystal structures were examined. The crystal structures of eight ordered phases could be determined, of which seven were obtained from laboratory X-ray powder diffraction data. Five additional phases turned out to be rotator phases and only their unit cells could be determined. Two previously unknown melting points were measured, as well as most enthalpies of melting. Several previously reported melting points were shown to be solid-to-solid phase transitions or decomposition points. Our experiments have revealed a complex picture of phases, rotator phases and phase transitions, in which a simple correlation between melting points and hydrogen-bonding patterns is not feasible.
Background: This study assessed the ability of mid-regional proadrenomedullin (MR-proADM) in comparison to conventional biomarkers (procalcitonin (PCT), lactate, C-reactive protein) and clinical scores to identify disease severity in patients with sepsis.
Methods: This is a secondary analysis of a randomised controlled trial in patients with severe sepsis or septic shock across 33 German intensive care units. The association between biomarkers and clinical scores with mortality was assessed by Cox regression analysis, area under the receiver operating characteristic and Kaplan-Meier curves. Patients were stratified into three severity groups (low, intermediate, high) for all biomarkers and scores based on cutoffs with either a 90% sensitivity or specificity.
Results: 1089 patients with a 28-day mortality rate of 26.9% were analysed. According to the Sepsis-3 definition, 41.2% and 58.8% fulfilled the criteria for sepsis and septic shock, with respective mortality rates of 20.0% and 32.1%. MR-proADM had the strongest association with mortality across all Sepsis-1 and Sepsis-3 subgroups and could facilitate a more accurate classification of low (e.g. MR-proADM vs. SOFA: N = 265 vs. 232; 9.8% vs. 13.8% mortality) and high (e.g. MR-proADM vs. SOFA: N = 161 vs. 155; 55.9% vs. 41.3% mortality) disease severity. Patients with decreasing PCT concentrations of either ≥ 20% (baseline to day 1) or ≥ 50% (baseline to day 4) but continuously high MR-proADM concentrations had a significantly increased mortality risk (HR (95% CI): 19.1 (8.0–45.9) and 43.1 (10.1–184.0)).
Conclusions: MR-proADM identifies disease severity and treatment response more accurately than established biomarkers and scores, adding additional information to facilitate rapid clinical decision-making and improve personalised sepsis treatment.
Background: Despite limited effectiveness of short-term psychotherapy for chronic depression, there is a lack of trials of long-term psychotherapy. Our study is the first to determine the effectiveness of controlled long-term psychodynamic and cognitive-behavioral (CBT) treatments and to assess the effects of preferential vs. randomized assessment.
Methods/design: Patients are assigned to treatment according to their preference or randomized (if they have no clear preference). Up to 80 sessions of psychodynamic or psychoanalytically oriented treatments (PAT) or up to 60 sessions of CBT are offered during the first year in the study. After the first year, PAT can be continued according to the ‘naturalistic’ usual method of treating such patients within the system of German health care (normally from 240 up to 300 sessions over two to three years). CBT therapists may extend their treatment up to 80 sessions, but focus mainly maintenance and relapse prevention. We plan to recruit a total of 240 patients (60 per arm). A total of 11 assessments are conducted throughout treatment and up to three years after initiation of treatment. The primary outcome measures are the Quick Inventory of Depressive Symptoms (QIDS, independent clinician rating) and the Beck Depression Inventory (BDI) after the first year.
Discussion: We combine a naturalistic approach with randomized controlled trials(RCTs)to investigate how effectively chronic depression can be treated on an outpatient basis by the two forms of treatment reimbursed in the German healthcare system and we will determine the effects of treatment preference vs. randomization.
The turnover time of terrestrial ecosystem carbon is an emergent ecosystem property that quantifies the strength of land surface on the global carbon cycle–climate feedback. However, observation- and modeling-based estimates of carbon turnover and its response to climate are still characterized by large uncertainties. In this study, by assessing the apparent whole ecosystem carbon turnover times (τ) as the ratio between carbon stocks and fluxes, we provide an update of this ecosystem level diagnostic and its associated uncertainties in high spatial resolution (0.083∘) using multiple, state-of-the-art, observation-based datasets of soil organic carbon stock (Csoil), vegetation biomass (Cveg) and gross primary productivity (GPP). Using this new ensemble of data, we estimated the global median τ to be 43+7−7 yr (median+difference to percentile 75−difference to percentile 25) when the full soil is considered, in contrast to limiting it to 1 m depth. Only considering the top 1 m of soil carbon in circumpolar regions (assuming maximum active layer depth is up to 1 m) yields a global median τ of 37+3−6 yr, which is longer than the previous estimates of 23+7−4 yr (Carvalhais et al., 2014). We show that the difference is mostly attributed to changes in global Csoil estimates. Csoil accounts for approximately 84 % of the total uncertainty in global τ estimates; GPP also contributes significantly (15 %), whereas Cveg contributes only marginally (less than 1 %) to the total uncertainty. The high uncertainty in Csoil is reflected in the large range across state-of-the-art data products, in which full-depth Csoil spans between 3362 and 4792 PgC. The uncertainty is especially high in circumpolar regions with an uncertainty of 50 % and a low spatial correlation between the different datasets (0.2<r<0.5) when compared to other regions (0.6<r<0.8). These uncertainties cast a shadow on current global estimates of τ in circumpolar regions, for which further geographical representativeness and clarification on variations in Csoil with soil depth are needed. Different GPP estimates contribute significantly to the uncertainties of τ mainly in semiarid and arid regions, whereas Cveg causes the uncertainties of τ in the subtropics and tropics. In spite of the large uncertainties, our findings reveal that the latitudinal gradients of τ are consistent across different datasets and soil depths. The current results show a strong ensemble agreement on the negative correlation between τ and temperature along latitude that is stronger in temperate zones (30–60∘ N) than in the subtropical and tropical zones (30∘ S–30∘ N). Additionally, while the strength of the τ–precipitation correlation was dependent on the Csoil data source, the latitudinal gradients also agree among different ensemble members. Overall, and despite the large variation in τ, we identified robust features in the spatial patterns of τ that emerge beyond the differences stemming from the data-driven estimates of Csoil, Cveg and GPP. These robust patterns, and associated uncertainties, can be used to infer τ–climate relationships and for constraining contemporaneous behavior of Earth system models (ESMs), which could contribute to uncertainty reductions in future projections of the carbon cycle–climate feedback. The dataset of τ is openly available at https://doi.org/10.17871/bgitau.201911 (Fan et al., 2019).
The turnover time of terrestrial carbon (τ) controls the global carbon cycle – climate feedback and, yet, is poorly simulated by the current Earth System Models (ESMs). In this study, by assessing apparent carbon turnover time as the ratio between carbon stocks and fluxes, we provide a new, updated ensemble of diagnostic terrestrial carbon turnover times and associated uncertainties on a global scale using multiple, state-of-the-art, observation-based datasets of soil organic carbon stock (Csoil), vegetation biomass (Cveg) and gross primary productivity (GPP). Using this new ensemble, we estimated the global average τ to be 42$% &' years when the full soil depth is considered, longer than the previous estimates of 23$) &* years. Only considering the top 1 m (assuming maximum active layer depth is up to 1 meter) of soil carbon in circumpolar regions yields a global τ of 35$) &' years. Csoil in circumpolar regions account for two thirds of the total uncertainty in global τ estimates, whereas Csoil in non-circumpolar contributes merely 9.38%. GPP (2.25%) and Cveg (0.05%) contribute even less to the total uncertainty. Therefore, the high uncertainty in Csoil is the main factor behind the uncertainty in global τ, as reflected in the larger range of full-depth Csoil (3152-4372 PgC). The uncertainty is especially high in circumpolar regions with a behaviour of ESMs which could contribute to uncertainty reductions in future projections of the carbon cycle - climate feedback. The dataset of the terrestrial turnover time ensemble (DOI: 10.17871/bgitau.201911) is openly available from the data portal: https://doi.org/10.17871/bgitau.201911 (Fan et al., 2019) uncertainty of 50% and the spatial correlations among different datasets are also low compared to other regions. Overall, we argue that current global datasets do not support robust estimates of τ globally, for which we need clarification on variations of Csoil with soil depth and stronger estimates of Csoil in circumpolar regions. Despite the large variation in both magnitude and spatial patterns of τ, we identified robust features in the spatial patterns of τ that emerge regardless of soil depth and differences in data sources of Csoil, Cveg and GPP. Our findings show that the latitudinal gradients of τ are consistent across different datasets and soil depth. Furthermore, there is a strong consensus on the negative correlation between τ and temperature along latitude that is stronger in temperate zones (30ºN-60ºN) than in subtropical and tropical zones (30ºS30ºN). The identified robust patterns can be used to infer the response of τ to climate and for constraining contemporaneous behaviour of ESMs which could contribute to uncertainty reductions in future projections of the carbon cycle - climate feedback. The dataset of the terrestrial turnover time ensemble (DOI:10.17871/bgitau.201911) is openly available from the data portal: https://doi.org/10.17871/bgitau.201911 (Fan et al., 2019).
Aim: To assess the prevalence and severity of periodontitis in patients with moderate chronic kidney disease (CKD) and comparing the results with the self‐reported periodontitis awareness of the study subjects.
Material and methods: The periodontal status of 270 patients with moderate CKD randomly selected from a cohort of 5,217 subjects participating in the prospective observational German Chronic Kidney Disease (GCKD) project was analysed by recording bleeding on probing (BOP), probing pocket depth (PPD) and clinical attachment level (CAL). Furthermore, the awareness of the study subjects of their periodontal conditions was evaluated by a self‐reported questionnaire.
Results: 24.4% of the CKD study patients showed no or only mild signs of periodontal disease, 47.6% displayed moderate and 27% severe periodontitis. Questionnaire data revealed that 62.3% of the study subjects with severe periodontitis were not aware of the presence of the disease, 44.4% denied having received any systematic periodontal therapy so far, although 50% of them indicated to visit their dentist regularly for professional tooth cleanings.
Conclusion: While the clinical study data confirm an increased prevalence of periodontitis in CKD patients, their self‐reported awareness of periodontitis was low.
The bile acid pool with its individual bile acids (BA) is modulated in the enterohepatic circulation by the liver as the primary site of synthesis, the motility of the gallbladder and of the intestinal tract, as well as by bacterial enzymes in the intestine. The nuclear receptor farnesoid X receptor (FXR) and Gpbar1 (TGR5) are important set screws in this process. Bile acids have a vasodilatory effect, at least according to in vitro studies. The present review examines the question of the extent to which the increase in bile acids in plasma could be responsible for the hyperdynamic circulatory disturbance of liver cirrhosis and whether modulation of the bile acid pool, for example, via administration of ursodeoxycholic acid (UDCA) or via modulation of the dysbiosis present in liver cirrhosis could influence the hemodynamic disorder of liver cirrhosis. According to our analysis, the evidence for this is limited. Long-term studies on this question are lacking.
Background: Since there is no standardized and effective treatment for advanced uveal melanoma (UM), the prognosis is dismal once metastases develop. Due to the availability of immune checkpoint blockade (ICB) in the real-world setting, the prognosis of metastatic UM has improved. However, it is unclear how the presence of hepatic and extrahepatic metastasis impacts the response and survival after ICB. Methods: A total of 178 patients with metastatic UM treated with ICB were included in this analysis. Patients were recruited from German skin cancer centers and the German national skin cancer registry (ADOReg). To investigate the impact of hepatic metastasis, two cohorts were compared: patients with liver metastasis only (cohort A, n = 55) versus those with both liver and extra-hepatic metastasis (cohort B, n = 123). Data were analyzed in both cohorts for response to treatment, progression-free survival (PFS), and overall survival (OS). The survival and progression probabilities were calculated with the Kaplan–Meier method. Log-rank tests, χ2 tests, and t-tests were performed to detect significant differences between both cohorts. Results: The median OS of the overall population was 16 months (95% CI 13.4–23.7) and the median PFS, 2.8 months (95% CI 2.5–3.0). The median OS was longer in cohort B than in cohort A (18.2 vs. 6.1 months; p = 0.071). The best objective response rate to dual ICB was 13.8% and to anti-PD-1 monotherapy 8.9% in the entire population. Patients with liver metastases only had a lower response to dual ICB, yet without significance (cohort A 8.7% vs. cohort B 16.7%; p = 0.45). Adverse events (AE) occurred in 41.6%. Severe AE were observed in 26.3% and evenly distributed between both cohorts. Conclusion: The survival of this large cohort of patients with advanced UM was more favorable than reported in previous benchmark studies. Patients with both hepatic and extrahepatic metastasis showed more favorable survival and higher response to dual ICB than those with hepatic metastasis only.
Although chest radiograph (CXR) is commonly used in diagnosing pediatric community acquired pneumonia (pCAP), limited data on interobserver agreement among radiologists exist. PedCAPNETZ is a prospective, observational, and multicenter study on pCAP. N = 233 CXR from patients with clinical diagnosis of pCAP were retrieved and n = 12 CXR without pathological findings were added. All CXR were interpreted by a radiologist at the site of recruitment and by two external, blinded pediatric radiologists. To evaluate interobserver agreement, the reporting of presence or absence of pCAP in CXR was analyzed, and prevalence and bias-adjusted kappa (PABAK) statistical testing was applied. Overall, n = 190 (82%) of CXR were confirmed as pCAP by two external pediatric radiologists. Compared with patients with pCAP negative CXR, patients with CXR-confirmed pCAP displayed higher C-reactive protein levels and a longer duration of symptoms before enrollment (p < .007). Further parameters, that is, age, respiratory rate, and oxygen saturation showed no significant difference. The interobserver agreement between the onsite radiologists and each of the two independent pediatric radiologists for the presence of pCAP was poor to fair (69%; PABAK = 0.39% and 76%; PABAK = 0.53, respectively). The concordance between the external radiologists was fair (81%; PABAK = 0.62). With regard to typical CXR findings for pCAP, chance corrected interrater agreement was highest for pleural effusions, infiltrates, and consolidations and lowest for interstitial patterns and peribronchial thickening. Our data show a poor interobserver agreement in the CXR-based diagnosis of pCAP and emphasized the need for harmonized interpretation standards.
Background: Rare Diseases (RDs) are difficult to diagnose. Clinical Decision Support Systems (CDSS) could support the diagnosis for RDs. The Medical Informatics in Research and Medicine (MIRACUM) consortium developed a CDSS for RDs based on distributed clinical data from eight German university hospitals. To support the diagnosis for difficult patient cases, the CDSS uses data from the different hospitals to perform a patient similarity analysis to obtain an indication of a diagnosis. To optimize our CDSS, we conducted a qualitative study to investigate usability and functionality of our designed CDSS. Methods: We performed a Thinking Aloud Test (TA-Test) with RDs experts working in Rare Diseases Centers (RDCs) at MIRACUM locations which are specialized in diagnosis and treatment of RDs. An instruction sheet with tasks was prepared that the participants should perform with the CDSS during the study. The TA-Test was recorded on audio and video, whereas the resulting transcripts were analysed with a qualitative content analysis, as a ruled-guided fixed procedure to analyse text-based data. Furthermore, a questionnaire was handed out at the end of the study including the System Usability Scale (SUS). Results: A total of eight experts from eight MIRACUM locations with an established RDC were included in the study. Results indicate that more detailed information about patients, such as descriptive attributes or findings, can help the system perform better. The system was rated positively in terms of functionality, such as functions that enable the user to obtain an overview of similar patients or medical history of a patient. However, there is a lack of transparency in the results of the CDSS patient similarity analysis. The study participants often stated that the system should present the user with an overview of exact symptoms, diagnosis, and other characteristics that define two patients as similar. In the usability section, the CDSS received a score of 73.21 points, which is ranked as good usability. Conclusions: This qualitative study investigated the usability and functionality of a CDSS of RDs. Despite positive feedback about functionality of system, the CDSS still requires some revisions and improvement in transparency of the patient similarity analysis.
Severe acute respiratory syndrome virus 2 (SARS-CoV-2) is the cause of the current coronavirus disease 19 (COVID-19) pandemic. Protease inhibitors are under consideration as virus entry inhibitors that prevent the cleavage of the coronavirus spike (S) protein by cellular proteases. Herein, we showed that the protease inhibitor aprotinin (but not the protease inhibitor SERPINA1/alpha-1 antitrypsin) inhibited SARS-CoV-2 replication in therapeutically achievable concentrations. An analysis of proteomics and translatome data indicated that SARS-CoV-2 replication is associated with a downregulation of host cell protease inhibitors. Hence, aprotinin may compensate for downregulated host cell proteases during later virus replication cycles. Aprotinin displayed anti-SARS-CoV-2 activity in different cell types (Caco2, Calu-3, and primary bronchial epithelial cell air–liquid interface cultures) and against four virus isolates. In conclusion, therapeutic aprotinin concentrations exert anti-SARS-CoV-2 activity. An approved aprotinin aerosol may have potential for the early local control of SARS-CoV-2 replication and the prevention of COVID-19 progression to a severe, systemic disease.
Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and other services that advance population health and wellbeing. However, the use of AI in healthcare also brings potential risks that may cause unintended harm. To guide future developments in AI, the High-Level Expert Group on AI set up by the European Commission (EC), recently published ethics guidelines for what it terms “trustworthy” AI. These guidelines are aimed at a variety of stakeholders, especially guiding practitioners toward more ethical and more robust applications of AI. In line with efforts of the EC, AI ethics scholarship focuses increasingly on converting abstract principles into actionable recommendations. However, the interpretation, relevance, and implementation of trustworthy AI depend on the domain and the context in which the AI system is used. The main contribution of this paper is to demonstrate how to use the general AI HLEG trustworthy AI guidelines in practice in the healthcare domain. To this end, we present a best practice of assessing the use of machine learning as a supportive tool to recognize cardiac arrest in emergency calls. The AI system under assessment is currently in use in the city of Copenhagen in Denmark. The assessment is accomplished by an independent team composed of philosophers, policy makers, social scientists, technical, legal, and medical experts. By leveraging an interdisciplinary team, we aim to expose the complex trade-offs and the necessity for such thorough human review when tackling socio-technical applications of AI in healthcare. For the assessment, we use a process to assess trustworthy AI, called 1Z-Inspection® to identify specific challenges and potential ethical trade-offs when we consider AI in practice.