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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.
Background: Clinical trial registries increase transparency in medical research by making information and results of planned, ongoing, and completed studies publicly available. However, the registration of clinical trials remains a time-consuming manual task complicated by the fact that the same studies often need to be registered in different registries with different data entry requirements and interfaces.
Objective: This study investigates how Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) may be used as a standardized format for exchanging and storing clinical trial records.
Methods: We designed and prototypically implemented an open-source central trial registry containing records from university hospitals, which are automatically exported and updated by local study management systems.
Results: We provided an architecture and implementation of a multisite clinical trials registry based on HL7 FHIR as a data storage and exchange format.
Conclusions: The results show that FHIR resources establish a harmonized view of study information from heterogeneous sources by enabling automated data exchange between trial centers and central study registries.
The ARMADILLO bunch compressor currently being designed at IAP is capable of reaching a longitudinal pulse compression ratio of 45 for proton beams of 150 mA at 2 MeV. It will provide one nanosecond proton pulses with a peak current of 7.7 A. The system guides nine linacμbunches deflected by a 5 MHz rf kicker and uses four dipole magnets - two homogeneous and two with field gradients - to merge them on the target. For longitudinal focusing and an energy variation of ±200 keV two multitrack rf cavities are included. ARMADILLO will be installed at the end of the Frankfurt Neutron Source FRANZ making use of the unique 250 kHz time structure. This contribution will provide an overview of the layout of the system as well as recent advances in component design and beam dynamics of the compressor.
Space charge lenses use a confined electron cloud for the focusing of ion beams. The focusing strength is given by the electron density whereas the density distribution influences the mapping quality of the space charge lens and is related to the confinement. The plasma parameters, loss as well as production mechanisms have a strong impact on plasma beam interactions. A scaled up space charge lens was constructed to investigate the properties of a nonneutral plasmas in detail. New non-interceptive diagnostic has been developed to characterize the collective behaviour of the confined nonneutral plasma in terms of an optimized lens design and parameters. Experimental results will be presented in comparison with numerical simulations.
Chopper systems are used to pulse charged particle beams. In most cases, electric deflection systems are used to generate beam pulses of defined lengths and appropriate repetition rates. At high beam intensities, the field distribution of the chopper system needs to be adapted precisely to the beam dynamics in order to avoid aberrations. An additional challenge is a robust design which guarantees reliable operation. For the Frankfurt Neutron Source FRANZ, an E×B chopper system is being developed which combines static magnetic deflection with a pulsed electric field in a Wien filter configuration. It will generate proton pulses with a flat top of 50 ns at a repetition rate of 250 kHz for 120 keV, 200 mA beams. For the electric deflection, pre-experiments with static and pulsed fields were performed using a helium ion beam. In pulsed mode operation, ion beams of different energies were deflected with voltages of up to ±6 kV and the resulting response was measured using a beam current transformer. A comparison between experiments and theoretical calculations as well as numerical simulations are presented.
Experimental results and theoretical predictions in laser acceleration of protons achieved energies of ten to several tens of MeV. The LIGHT project (Laser Ion Generation, Handling and Transport) is proposed to use the PHELIX laser accelerated protons and to provide transport, focusing and injection into a conventional accelerator. This study demonstrates transport and focusing of laser-accelerated 10 MeV protons by a pulsed 18 T magnetic solenoid. The effect of co-moving electrons on the beam dynamics is investigated. The unique features of the proton distribution like small emittances and high yield of the order of 1013 protons per shot open new research area. The possibility of creating laser based injectors for ion accelerators is addressed. With respect to transit energies, direct matching into DTL's seems adequate. The bunch injection into a proposed CH− structure is under investigation at IAP Frankfurt. Options and simulation tools are presented.
Space charge lenses using a stable electron cloud for focusing low energy heavy ion beams are an alternative concept to conventional ion optics. Due to external fields electrons are confined inside the lens’ volume. In case of a homogeneously distributed electron cloud the linear electric space charge field enables beam focusing free of aberration. Since the mapping quality of the lens is related to the confinement, non-destructive diagnostics has been developed to determine the plasma parameters and to characterize the collective behavior of the confined nonneutral plasma. Moreover, a scaled up space charge lens was constructed for a detailed investigation of the nonneutral plasma properties as well as beam interactions with a stable confined electron cloud. Experimental results will be presented in comparison with numerical simulations.