A disordered rock salt anode for fast-charging lithium-ion batteries.

Rechargeable lithium-ion batteries with high energy density that can be safely charged and discharged at high rates are desirable for electrified transportation and other applications1-3. However, the sub-optimal intercalation potentials of current anodes result in a trade-off between energy density, power and safety. Here we report that disordered rock salt4,5 Li3+xV2O5 can be used as a fast-charging anode that can reversibly cycle two lithium ions at an average voltage of about 0.6 volts versus a Li/Li+ reference electrode. The increased potential compared to graphite6,7 reduces the likelihood of lithium metal plating if proper charging controls are used, alleviating a major safety concern (short-circuiting related to Li dendrite growth). In addition, a lithium-ion battery with a disordered rock salt Li3V2O5 anode yields a cell voltage much higher than does a battery using a commercial fast-charging lithium titanate anode or other intercalation anode candidates (Li3VO4 and LiV0.5Ti0.5S2)8,9. Further, disordered rock salt Li3V2O5 can perform over 1,000 charge-discharge cycles with negligible capacity decay and exhibits exceptional rate capability, delivering over 40 per cent of its capacity in 20 seconds. We attribute the low voltage and high rate capability of disordered rock salt Li3V2O5 to a redistributive lithium intercalation mechanism with low energy barriers revealed via ab initio calculations. This low-potential, high-rate intercalation reaction can be used to identify other metal oxide anodes for fast-charging, long-life lithium-ion batteries.

Diastereo- and Enantioselective Construction of Stereochemical Arrays Exploiting Non-Classical Hydrogen Bonding in Enolborates.

We report a copper-catalyzed reductive aldol addition to aldehydes and ketones, with pinacolborane as stoichiometric reductant, that results in the generation of stereodefined syn-aldol products.  Cyclic, acyclic, fused and spirocyclic aldols bearing contiguous stereocenters are obtained with excellent yields and diastereoselectivities.  Moreover, enantioselective reactions could be carried out with cycloalkenones to deliver aldols bearing three contiguous stereocenters and with up to 98% ee.  Computations reveal that the enolborate intermediate undergoes the syn-aldol reaction via a twist-boat transition state that is stabilized by non-classical hydrogen bonding interactions.

Fulminant sepsis secondary to severe lung contusion from the Lund University Cardiopulmonary Assist System device.

INTRODUCTION: Portable mechanical chest compression devices have been developed to improve upon many problems of manual compression, increase patient survival, and improve neurologic outcomes. However, the use of these devices is not without risk of harm to the patient. CASE REPORT: We describe a patient who received chest compressions from a mechanical compression device after cardiac arrest and subsequently developed fulminant sepsis secondary to lung contusions and a necrotizing pulmonary infection. DISCUSSION: Although injuries from the LUCAS have been reported, we believe this is the first reported fatal complication related to direct pulmonary injury from a mechanical compression device. CONCLUSION: More investigation is needed to determine the safety and efficacy of the LUCAS especially in obese patients.

Porous organic polymers for Li-chemistry-based batteries: functionalities and characterization studies.

Porous organic polymers (POPs), a versatile class of materials that possess many tunable properties such as high chemical absorptivity and ionic conductivity, are emerging candidate electrode materials, permselective membranes, ionic conductors, interfacial stabilizers and functional precursors to synthesize advanced porous carbon. Based on their crystal structure features, the emerging POPs can be classified into two subclasses: amorphous POPs (hyper cross-linked polymers, polymers with intrinsic microporosity, conjugated microporous polymers, porous aromatic frameworks, etc.) and crystalline POPs (covalent organic frameworks, etc.). This tutorial review provides a brief introduction of different types of POPs in terms of their classification and functions for tackling the remaining challenges in various types of Li-chemistry-based batteries. In situ and ex situ characterization studies are also discussed to highlight their importance and applicability for the structural investigation of POPs to reveal the underlying mechanism of POPs over the course of the electrochemical process. Although some revolutionary advances have been achieved, the development of POPs in Li-chemistry-based batteries is still in its infancy. Perspectives regarding future application and mechanistic insights of POPs in battery studies are outlined at the end.

A Convolutional Neural Network for Beamforming and Image Reconstruction in Passive Cavitation Imaging.

Convolutional neural networks (CNNs), initially developed for image processing applications, have recently received significant attention within the field of medical ultrasound imaging. In this study, passive cavitation imaging/mapping (PCI/PAM), which is used to map cavitation sources based on the correlation of signals across an array of receivers, is evaluated. Traditional reconstruction techniques in PCI, such as delay-and-sum, yield high spatial resolution at the cost of a substantial computational time. This results from the resource-intensive process of determining sensor weights for individual pixels in these methodologies. Consequently, the use of conventional algorithms for image reconstruction does not meet the speed requirements that are essential for real-time monitoring. Here, we show that a three-dimensional (3D) convolutional network can learn the image reconstruction algorithm for a 16×16 element matrix probe with a receive frequency ranging from 256 kHz up to 1.0 MHz. The network was trained and evaluated using simulated data representing point sources, resulting in the successful reconstruction of volumetric images with high sensitivity, especially for single isolated sources (100% in the test set). As the number of simultaneous sources increased, the network's ability to detect weaker intensity sources diminished, although it always correctly identified the main lobe. Notably, however, network inference was remarkably fast, completing the task in approximately 178 s for a dataset comprising 650 frames of 413 volume images with signal duration of 20µs. This processing speed is roughly thirty times faster than a parallelized implementation of the traditional time exposure acoustics algorithm on the same GPU device. This would open a new door for PCI application in the real-time monitoring of ultrasound ablation.

Radiology Implementation Considerations for Artificial Intelligence (AI) Applied to COVID-19, From the AJR Special Series on AI Applications.

Hundreds of imaging-based artificial intelligence (AI) models have been developed in response to the COVID-19 pandemic. AI systems that incorporate imaging have shown promise in primary detection, severity grading, and prognostication of outcomes in COVID-19, and have enabled integration of imaging with a broad range of additional clinical and epidemiologic data. However, systematic reviews of AI models applied to COVID-19 medical imaging have highlighted problems in the field, including methodologic issues and problems in real-world deployment. Clinical use of such models should be informed by both the promise and potential pitfalls of implementation. How does a practicing radiologist make sense of this complex topic, and what factors should be considered in the implementation of AI tools for imaging of COVID-19? This critical review aims to help the radiologist understand the nuances that impact the clinical deployment of AI for imaging of COVID-19. We review imaging use cases for AI models in COVID-19 (e.g., diagnosis, severity assessment, and prognostication) and explore considerations for AI model development and testing, deployment infrastructure, clinical user interfaces, quality control, and institutional review board and regulatory approvals, with a practical focus on what a radiologist should consider when implementing an AI tool for COVID-19.

New Concepts in Electrolytes.

Over the past decades, Li-ion battery (LIB) has turned into one of the most important advances in the history of technology due to its extensive and in-depth impact on our life. Its omnipresence in all electric vehicles, consumer electronics and electric grids relies on the precisely tuned electrochemical dynamics and interactions among the electrolytes and the diversified anode and cathode chemistries therein. With consumers' demand for battery performance ever increasing, more and more stringent requirements are being imposed upon the established equilibria among these LIB components, and it became clear that the state-of-the-art electrolyte systems could no longer sustain the desired technological trajectory. Driven by such gap, researchers started to explore more unconventional electrolyte systems. From superconcentrated solvent-in-salt electrolytes to solid-state electrolytes, the current research realm of novel electrolyte systems has grown to unprecedented levels. In this review, we will avoid discussions on current state-of-the-art electrolytes but instead focus exclusively on unconventional electrolyte systems that represent new concepts.

Artificial intelligence applied to musculoskeletal oncology: a systematic review.

Developments in artificial intelligence have the potential to improve the care of patients with musculoskeletal tumors. We performed a systematic review of the published scientific literature to identify the current state of the art of artificial intelligence applied to musculoskeletal oncology, including both primary and metastatic tumors, and across the radiology, nuclear medicine, pathology, clinical research, and molecular biology literature. Through this search, we identified 252 primary research articles, of which 58 used deep learning and 194 used other machine learning techniques. Articles involving deep learning have mostly involved bone scintigraphy, histopathology, and radiologic imaging. Articles involving other machine learning techniques have mostly involved transcriptomic analyses, radiomics, and clinical outcome prediction models using medical records. These articles predominantly present proof-of-concept work, other than the automated bone scan index for bone metastasis quantification, which has translated to clinical workflows in some regions. We systematically review and discuss this literature, highlight opportunities for multidisciplinary collaboration, and identify potentially clinically useful topics with a relative paucity of research attention. Musculoskeletal oncology is an inherently multidisciplinary field, and future research will need to integrate and synthesize noisy siloed data from across clinical, imaging, and molecular datasets. Building the data infrastructure for collaboration will help to accelerate progress towards making artificial intelligence truly useful in musculoskeletal oncology.

CoVA: An Acuity Score for Outpatient Screening that Predicts Coronavirus Disease 2019 Prognosis.

BACKGROUND: We sought to develop an automatable score to predict hospitalization, critical illness, or death for patients at risk for coronavirus disease 2019 (COVID-19) presenting for urgent care. METHODS: We developed the COVID-19 Acuity Score (CoVA) based on a single-center study of adult outpatients seen in respiratory illness clinics or the emergency department. Data were extracted from the Partners Enterprise Data Warehouse, and split into development (n = 9381, 7 March-2 May) and prospective (n = 2205, 3-14 May) cohorts. Outcomes were hospitalization, critical illness (intensive care unit or ventilation), or death within 7 days. Calibration was assessed using the expected-to-observed event ratio (E/O). Discrimination was assessed by area under the receiver operating curve (AUC). RESULTS: In the prospective cohort, 26.1%, 6.3%, and 0.5% of patients experienced hospitalization, critical illness, or death, respectively. CoVA showed excellent performance in prospective validation for hospitalization (expected-to-observed ratio [E/O]: 1.01; AUC: 0.76), for critical illness (E/O: 1.03; AUC: 0.79), and for death (E/O: 1.63; AUC: 0.93). Among 30 predictors, the top 5 were age, diastolic blood pressure, blood oxygen saturation, COVID-19 testing status, and respiratory rate. CONCLUSIONS: CoVA is a prospectively validated automatable score for the outpatient setting to predict adverse events related to COVID-19 infection.

In Situ Localized Polysulfide Injector for the Activation of Bulk Lithium Sulfide.

The activation of commercial Li2S remains to be one of the key challenges against its commercialization as a starting cathode material for a sulfur-based Li-ion battery system. In this work we take advantage of the lower oxidation potential of commercial Na2S (1-3 wt%) to serve as an in situ and local polysulfide injector for the activation of commercial Li2S (70 wt%). In contrast to applying pre-solvated redox mediators, this technique allows for the activation of commercial Li2S at lower voltages with an electrolyte content as low as 3 µL mg-1Li2S at 3 mgmgLi2S cm-2 and 4 µL mg-1Li2S at 6.5 mgLi2S cm-2 without any other material modification.

Oxygen-Based Anion Redox for Lithium Batteries.

ConspectusThe importance of current Li-ion batteries (LIBs) in modern society cannot be overstated. While the energy demands of devices increase, the corresponding enhancements in energy density of battery technologies are highly sought after. Currently, many different battery concepts, such as Li-S and metal-air among many others, have been investigated. However, their practical implementation has mostly been restricted to the prototyping stage. In fact, most of these technologies require rework of existing Li-ion battery manufacturing facilities and will naturally incur resistance to change from industry. For this reason, one specifically attractive technology, anionic redox in transition metal oxides, has gained much attention in the recent years. Its ability to be directly used in already established processes and higher energy density with similar electrolyte formulation make it a key materials research direction for next generation Li-ion batteries. In regular LIBs, the redox active centers are the transition metal cation. In anion redox, both the anion (typically O) and the transition metal cation are utilized as redox centers with enormous implications for increasing energy density. This new material can be highly competitive for replacing the current LIB technologies. However, much is still unknown about its cycling mechanism. Upon activating the O redox couples, most cationic and anionic redox active materials will either evolve O2 or undergo irreversible structural degradation with associated severe decreases in electrochemical performance. By understanding the transition from full anion redox to partial cationic and anionic redox, we hope readers can gain a deeper understanding of the topic.This Account will focus mainly on the work that was conducted by our group at Argonne National Laboratory. The phenomenon of cationic and anionic redox in a lithium-ion battery cathode will first be discussed. Our work in resonant inelastic X-ray scattering to investigate the spectroscopic features of O after delithiation has found potential "fingerprint" signals that could likely be used to identify and confirm reversible O redox if corroborated with other techniques. To follow, we will examine our work on Li-O2 batteries. While our group and the research community have had many significant contributions and improvements to the field of Li-O2 (such as decreasing overpotential and achieving cyclability in air environment), its practical application is still far from realization. Perhaps our most important contribution to this area is the discovery that Ir deposited on reduced graphene oxide can be used to halt the reduction of O2 at the LiO2 oxidation state. This not only significantly decreases the charge overpotential but also presents the important concept of oxidation-state controlled discharge. Subsequently, we will focus on our oxidation state-controlled redox-based charging of oxygen in a pure oxygen redox Li-ion battery. Future implications of this technology will be emphasized.

Yttrium-90 Hepatic Radioembolization for Advanced Chemorefractory Metastatic Colorectal Cancer: Survival Outcomes Based on Right- Versus Left-Sided Primary Tumor Location.

BACKGROUND. Primary colon cancer location affects survival of patients with metastatic colorectal cancer (mCRC). Outcomes based on primary tumor location after salvage hepatic radioembolization with 90Y resin microspheres are not well studied. OBJECTIVE. The objectives of this study are to assess the survival outcomes of patients with advanced chemorefractory mCRC treated with 90Y radioembolization, as stratified by primary tumor location, and to explore potential factors that are predictive of survival. METHODS. A total of 99 patients who had progressive mCRC liver metastases while receiving systemic therapy and who were treated with 90Y radioembolization at a single center were retrospectively analyzed. For 89 patients, tumor response on the first imaging follow-up examination (CT or MRI performed at a mean [± SD] of 1.9 ± 0.9 months after 90Y radioembolization) was evaluated using RECIST. Overall survival (OS), OS after 90Y radioembolization, and hepatic progression-free survival (PFS) were calculated using the Kaplan-Meier method. Outcomes and associations of outcomes with tumor response were compared between patients with left- and right-sided tumors. RESULTS. A total of 74 patients had left-sided colon cancer, and 25 patients had right-sided colon cancer. Median OS from the time of mCRC diagnosis was 37.2 months, median OS after 90Y radioembolization was 5.8 months, and median hepatic PFS was 3.3 months. Based on RECIST, progressive disease on first imaging follow-up was observed in 38 patients (43%) after 90Y radioembolization and was associated with shorter OS after 90Y radioembolization compared with observation of disease control on first imaging follow-up (4.0 vs 10.5 months; p < .001). Patients with right-sided primary tumors showed decreased median OS after 90Y radioembolization compared with patients with left-sided primary tumors (5.4 vs 6.2 months; p = .03). Right- and left-sided primary tumors showed no significant difference in RECIST tumor response, hepatic PFS, or extrahepatic disease progression (p > .05). Median survival after 90Y radioembolization was significantly lower among patients with progressive disease than among those with disease control in the group with left-sided primary tumors (4.2 vs 13.9 months; p < .001); however, this finding was not observed in the group with right-sided primary tumors (3.3 vs 7.2 months; p = .05). CONCLUSION. Right-sided primary tumors were independently associated with decreased survival among patients with chemorefractory mCRC after 90Y radioembolization, despite these patients having a similar RECIST tumor response, hepatic PFS, and extrahepatic disease progression compared with patients with left-sided primary tumors. CLINICAL IMPACT. Primary colon cancer location impacts outcomes after salvage 90Y radioembolization and may help guide patient selection.

Right Ventricular Strain Is Common in Intubated COVID-19 Patients and Does Not Reflect Severity of Respiratory Illness.

BACKGROUND: Right ventricular (RV) dysfunction is common and associated with worse outcomes in patients with coronavirus disease 2019 (COVID-19). In non-COVID-19 acute respiratory distress syndrome, RV dysfunction develops due to pulmonary hypoxic vasoconstriction, inflammation, and alveolar overdistension or atelectasis. Although similar pathogenic mechanisms may induce RV dysfunction in COVID-19, other COVID-19-specific pathology, such as pulmonary endothelialitis, thrombosis, or myocarditis, may also affect RV function. We quantified RV dysfunction by echocardiographic strain analysis and investigated its correlation with disease severity, ventilatory parameters, biomarkers, and imaging findings in critically ill COVID-19 patients. METHODS: We determined RV free wall longitudinal strain (FWLS) in 32 patients receiving mechanical ventilation for COVID-19-associated respiratory failure. Demographics, comorbid conditions, ventilatory parameters, medications, and laboratory findings were extracted from the medical record. Chest imaging was assessed to determine the severity of lung disease and the presence of pulmonary embolism. RESULTS: Abnormal FWLS was present in 66% of mechanically ventilated COVID-19 patients and was associated with higher lung compliance (39.6 vs 29.4 mL/cmH2O, P = 0.016), lower airway plateau pressures (21 vs 24 cmH2O, P = 0.043), lower tidal volume ventilation (5.74 vs 6.17 cc/kg, P = 0.031), and reduced left ventricular function. FWLS correlated negatively with age (r = -0.414, P = 0.018) and with serum troponin (r = 0.402, P = 0.034). Patients with abnormal RV strain did not exhibit decreased oxygenation or increased disease severity based on inflammatory markers, vasopressor requirements, or chest imaging findings. CONCLUSIONS: RV dysfunction is common among critically ill COVID-19 patients and is not related to abnormal lung mechanics or ventilatory pressures. Instead, patients with abnormal FWLS had more favorable lung compliance. RV dysfunction may be secondary to diffuse intravascular micro- and macro-thrombosis or direct myocardial damage. TRIAL REGISTRATION: National Institutes of Health #NCT04306393. Registered 10 March 2020, https://clinicaltrials.gov/ct2/show/NCT04306393.

Automated tracking of emergency department abdominal CT findings during the COVID-19 pandemic using natural language processing.

PURPOSE: During the COVID-19 pandemic, emergency department (ED) volumes have fluctuated. We hypothesized that natural language processing (NLP) models could quantify changes in detection of acute abdominal pathology (acute appendicitis (AA), acute diverticulitis (AD), or bowel obstruction (BO)) on CT reports. METHODS: This retrospective study included 22,182 radiology reports from CT abdomen/pelvis studies performed at an urban ED between January 1, 2018 to August 14, 2020. Using a subset of 2448 manually annotated reports, we trained random forest NLP models to classify the presence of AA, AD, and BO in report impressions. Performance was assessed using 5-fold cross validation. The NLP classifiers were then applied to all reports. RESULTS: The NLP classifiers for AA, AD, and BO demonstrated cross-validation classification accuracies between 0.97 and 0.99 and F1-scores between 0.86 and 0.91. When applied to all CT reports, the estimated numbers of AA, AD, and BO cases decreased 43-57% in April 2020 (first regional peak of COVID-19 cases) compared to 2018-2019. However, the number of abdominal pathologies detected rebounded in May-July 2020, with increases above historical averages for AD. The proportions of CT studies with these pathologies did not significantly increase during the pandemic period. CONCLUSION: Dramatic decreases in numbers of acute abdominal pathologies detected by ED CT studies were observed early on during the COVID-19 pandemic, though these numbers rapidly rebounded. The proportions of CT cases with these pathologies did not increase, which suggests patients deferred care during the first pandemic peak. NLP can help automatically track findings in ED radiology reporting.

Cationic and anionic redox in lithium-ion based batteries.

Lithium-ion batteries have proven themselves to be indispensable among modern day society. Demands stemming from consumer electronics and renewable energy systems have pushed researchers to strive for new electrochemical technologies. To this end, the advent of anionic redox, that is, the sequential or simultaneous redox of the cation and anion in a transition metal oxide based cathode for a Li-ion battery, has garnered much attention due to the enhanced specific capacities. Unfortunately, the higher energy densities are plagued with problems associated with the irreversibility of anionic redox. Much effort has been placed on finding a suitable composition of transition metal oxide, with some groups identifying the underlying features and relationship for anion redox and cationic redox to occur reversibly. Accordingly, it is timely to review anionic redox in terms of what anionic redox is with emphasis on the mechanism and the evidence underlying its discovery and validation. To follow will be a section defining the nature of the transition metal and oxygen bond accompanied by three subsequent sections bridging the redox spectrum from pure anionic, to a mix of cationic and anionic and pure cationic.

Developing high safety Li-metal anodes for future high-energy Li-metal batteries: strategies and perspectives.

Developing high-safety Li-metal anodes (LMAs) is extremely important for the application of high-energy Li-metal batteries (LMBs), especially Li-S and Li-O2 battery systems. However, the notorious Li-dendrite growth problem results in serious safety concerns for any energy storage application. Through a recent combination of interface-based science, nanotechnology-based solutions and characterization methods, the LMA is now primed for a technological boom. In this review, the recent emerging strategies and perspectives on LMAs are summarized, following which the current huge evolution in interfacial chemistry regulation, optimizing electrolyte components, designing a rational 'host' for lithium metal, optimizing "solid-state electrolytes" and other emerging strategies for developing high-safety LMAs is highlighted. Furthermore, several state-of-the-art in situ/operando synchrotron-based X-ray techniques for high safety LMB research are introduced. With the further development of LMAs in the future, subsequent application in high energy LMBs is to be expected.

A review of composite solid-state electrolytes for lithium batteries: fundamentals, key materials and advanced structures.

All-solid-state lithium ion batteries (ASSLBs) are considered next-generation devices for energy storage due to their advantages in safety and potentially high energy density. As the key component in ASSLBs, solid-state electrolytes (SSEs) with non-flammability and good adaptability to lithium metal anodes have attracted extensive attention in recent years. Among the current SSEs, composite solid-state electrolytes (CSSEs) with multiple phases have greater flexibility to customize and combine the advantages of single-phase electrolytes, which have been widely investigated recently and regarded as promising candidates for commercial ASSLBs. Based on existing investigations, herein, we present a comprehensive overview of the recent developments in CSSEs. Initially, we introduce the historical development from solid-state ionic conductors to CSSEs, and then summarize the fundamentals including mechanisms of lithium ion transport, key evaluation parameters, design principles, and key materials. Four main types of advanced structures for CSSEs are classified and highlighted according to the recent progress. Moreover, advanced characterization and computational simulation techniques including machine learning are reviewed for the first time, and the main challenges and perspectives of CSSEs are also provided for their future development.

Strain-Modulated Platinum-Palladium Nanowires for Oxygen Reduction Reaction.

Electrocatalytic activity of alloy nanocatalytsts can be manipulated effectively by tuning their physical properties (ensemble, geometric, and ligand effects) to afford optimal surface structure and compositions for proton exchange membrane fuel cell (PEMFC) application. Herein, highly catalytic platinum-palladium nanowires (PtnPd100-n NWs) with a subtle lattice strain and Boerdijk-Coxeter helix type morphology are synthesized through a surfactant-free, thermal single phase solvent method. X-ray diffraction results show that PtnPd100-n NWs are exposed through the (111) facets and their shrinking or expanding lattice parameters can be modulated by the alloy compositions. Electrochemical results reveal that their high catalytic activity correlates with the lattice shrinking, facets, and bimetallic compositions, showing higher activity when the ratio of Pt and Pd is ∼78:22, which is further supported by DFT results. Compared to the nanoparticle type platinum-palladium alloyed catalysts with similar metal compositions (PtnPd100-n NPs), the PtnPd100-n NWs exhibit significantly improved electrocatalytic activity and stability for the oxygen reduction reaction. These findings open new strategies to design the highly active and stable alloy nanocatalysts with controllable compositions.

Racial and Ethnic Disparities in Disease Severity on Admission Chest Radiographs among Patients Admitted with Confirmed Coronavirus Disease 2019: A Retrospective Cohort Study.

Background Disease severity on chest radiographs has been associated with higher risk of disease progression and adverse outcomes from coronavirus disease 2019 (COVID-19). Few studies have evaluated COVID-19-related racial and/or ethnic disparities in radiology. Purpose To evaluate whether non-White minority patients hospitalized with confirmed COVID-19 infection presented with increased severity on admission chest radiographs compared with White or non-Hispanic patients. Materials and Methods This single-institution retrospective cohort study was approved by the institutional review board. Patients hospitalized with confirmed COVID-19 infection between March 17, 2020, and April 10, 2020, were identified by using the electronic medical record (n = 326; mean age, 59 years ±17 [standard deviation]; male-to-female ratio: 188:138). The primary outcome was the severity of lung disease on admission chest radiographs, measured by using the modified Radiographic Assessment of Lung Edema (mRALE) score. The secondary outcome was a composite adverse clinical outcome of intubation, intensive care unit admission, or death. The primary exposure was the racial and/or ethnic category: White or non-Hispanic versus non-White (ie, Hispanic, Black, Asian, or other). Multivariable linear regression analyses were performed to evaluate the association between mRALE scores and race and/or ethnicity. Results Non-White patients had significantly higher mRALE scores (median score, 6.1; 95% confidence interval [CI]: 5.4, 6.7) compared with White or non-Hispanic patients (median score, 4.2; 95% CI: 3.6, 4.9) (unadjusted average difference, 1.8; 95% CI: 0.9, 2.8; P < .01). For both White (adjusted hazard ratio, 1.3; 95% CI: 1.2, 1.4; P < .001) and non-White (adjusted hazard ratio, 1.2; 95% CI: 1.1, 1.3; P < .001) patients, increasing mRALE scores were associated with a higher likelihood of experiencing composite adverse outcome with no evidence of interaction (P = .16). Multivariable linear regression analyses demonstrated that non-White patients presented with higher mRALE scores at admission chest radiography compared with White or non-Hispanic patients (adjusted average difference, 1.6; 95% CI: 0.5, 2.7; P < .01). Adjustment for hypothesized mediators revealed that the association between race and/or ethnicity and mRALE scores was mediated by limited English proficiency (P < .01). Conclusion Non-White patients hospitalized with coronavirus disease 2019 infection were more likely to have a higher severity of disease on admission chest radiographs than White or non-Hispanic patients, and increased severity was associated with worse outcomes for all patients. © RSNA, 2020 Online supplemental material is available for this article.

Abdominal Imaging Findings in COVID-19: Preliminary Observations.

Background Angiotensin-converting enzyme 2, a target of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), demonstrates its highest surface expression in the lung, small bowel, and vasculature, suggesting abdominal viscera may be susceptible to injury. Purpose To report abdominal imaging findings in patients with coronavirus disease 2019. Materials and Methods In this retrospective cross-sectional study, patients consecutively admitted to a single quaternary care center from March 27 to April 10, 2020, who tested positive for SARS-CoV-2 were included. Abdominal imaging studies performed in these patients were reviewed, and salient findings were recorded. Medical records were reviewed for clinical data. Univariable analysis and logistic regression were performed. Results A total of 412 patients (average age, 57 years; range, 18 to >90 years; 241 men, 171 women) were evaluated. A total of 224 abdominal imaging studies were performed (radiography, n = 137; US, n = 44; CT, n = 42; MRI, n = 1) in 134 patients (33%). Abdominal imaging was associated with age (odds ratio [OR], 1.03 per year of increase; P = .001) and intensive care unit (ICU) admission (OR, 17.3; P < .001). Bowel-wall abnormalities were seen on 31% of CT images (13 of 42) and were associated with ICU admission (OR, 15.5; P = .01). Bowel findings included pneumatosis or portal venous gas, seen on 20% of CT images obtained in patients in the ICU (four of 20). Surgical correlation (n = 4) revealed unusual yellow discoloration of the bowel (n = 3) and bowel infarction (n = 2). Pathologic findings revealed ischemic enteritis with patchy necrosis and fibrin thrombi in arterioles (n = 2). Right upper quadrant US examinations were mostly performed because of liver laboratory findings (87%, 32 of 37), and 54% (20 of 37) revealed a dilated sludge-filled gallbladder, suggestive of bile stasis. Patients with a cholecystostomy tube placed (n = 4) had negative bacterial cultures. Conclusion Bowel abnormalities and gallbladder bile stasis were common findings on abdominal images of patients with coronavirus disease 2019. Patients who underwent laparotomy often had ischemia, possibly due to small-vessel thrombosis. © RSNA, 2020.