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This review assesses the appropriateness of various imaging studies for adult major blunt trauma or polytrauma in the acute setting. Trauma is the leading cause of mortality for people in the United States The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

BackgroundAlthough convalescent plasma has been widely used to treat severe coronavirus disease 2019 (COVID-19), data from randomized controlled trials that support its efficacy are limited.ObjectiveTo evaluate the clinical efficacy and safety of convalescent plasma among adults hospitalized with severe and critical COVID-19.DesignRandomized, double-blind, controlled, multicenter, phase 2 trial conducted from April 21st to November 27th, 2020.SettingFive hospitals in New York City (NY, USA) and Rio de Janeiro (Brazil).ParticipantsHospitalized patients aged ≥18 years with laboratory-confirmed COVID-19, infiltrates on chest imaging and oxygen saturation ≤ 94% on room air or requirement for supplemental oxygen, invasive mechanical ventilation, or extracorporeal membrane oxygenation.InterventionParticipants were randomized 2:1 to a single transfusion of either 1 unit of convalescent or normal control plasma.MeasurementsThe primary outcome was clinical status at 28 days, measured using an ordinal scale and analyzed using a proportional odds model in the intention-to-treat population.ResultsOf 223 participants enrolled, 150 were randomized to receive convalescent plasma and 73 to normal control plasma. At 28 days, no significant improvement in clinical status was observed in participants randomized to convalescent plasma (with an odds ratio (OR) of a 1-point improvement in the scale: 1.50, 95% confidence interval (CI) 0.83-2.68, p=0.180).However, 28-day mortality was significantly lower in participants randomized to convalescent plasma versus control plasma (19/150 [12.6%] versus 18/73 [24.6%], OR 0.44, 95% CI 0.22-0.91, p=0.034). The median titer of anti-SARS-CoV-2 neutralizing antibody in infused convalescent plasma units was 1:160 (IQR 1:80-1:320). In a subset of nasopharyngeal swab samples (n=40) from Brazil that underwent genomic sequencing, no evidence of neutralization-escape mutants was detected. Serious adverse events occurred in 39/147 (27%) participants who received convalescent plasma and 26/72 (36%) participants who received control plasma.LimitationsSome participants did not receive high-titer convalescent plasma.ConclusionIn adults hospitalized with severe COVID-19, use of convalescent plasma was not associated with significant improvement in 28 days clinical status. The significant reduction in mortality associated with convalescent plasma, however, may warrant further evaluation.RegistrationClinicalTrials.gov, NCT04359810FundingAmazon FoundationClinical Trial RegistrationClinicalTrials.gov Identifier: NCT04359810

Many existing conditional Generative Adversarial Networks (cGANs) are limited to conditioning on pre-defined and fixed class-level semantic labels or attributes. We propose an open set GAN architecture (OpenGAN) that is conditioned per-input sample with a feature embedding drawn from a metric space. Using a state-of-the-art metric learning model that encodes both class-level and fine-grained semantic information, we are able to generate samples that are semantically similar to a given source image. The semantic information extracted by the metric learning model transfers to out-of-distribution novel classes, allowing the generative model to produce samples that are outside of the training distribution. We show that our proposed method is able to generate 256\(\times \)256 resolution images from novel classes that are of similar visual quality to those from the training classes. In lieu of a source image, we demonstrate that random sampling of the metric space also results in high-quality samples. We show that interpolation in the feature space and latent space results in semantically and visually plausible transformations in the image space. Finally, the usefulness of the generated samples to the downstream task of data augmentation is demonstrated. We show that classifier performance can be significantly improved by augmenting the training data with OpenGAN samples on classes that are outside of the GAN training distribution.

Introduction: Patients with cardiovascular disease conditions are at high risk for direct and indirect impacts of COVID-19 on morbidity and mortality. In light of this, we aimed to assess the extent to which COVID-19-related anxiety in patients with a history of cardiac arrest (CA) correlates with the desire to change or discuss advanced directives. Methods: Between May 15-28, 2020, a month after the New York City (NYC) COVID-19 pandemic peak, CA survivors from a prospective cohort were invited to participate in a telephone-based assessment of the pandemic’s impact on psychological and other survivorship dimensions. COVID-19-related anxiety was measured by the Generalized Anxiety Disorder-3 scale, which asks how often respondents felt (1) anxious, (2) unable to stop worrying, and (3) excessively worried over two weeks, and was keyed to the COVID-19 pandemic. Desire to discuss or to change financial and/or health-related advanced directives were reported on a yes-or-no basis. Results: 100 approached, 69 CA survivors participated (53% male; age 61±15 years; 44% White, 20% Black, and 31% Latinx). A majority, 58 of 69 (84%), had no COVID-19 symptoms and/or were not tested. Only 12 of the 69 respondents (17%) showed interest in discussing or changing advanced directives. There were no significant differences in the age, sex, race, or COVID-19 symptoms status between those who showed desire versus those who did not. Desire to change advance directives was significantly associated with increased COVID-19-related anxiety (OR 1.5, CI 95% [1.2-1.9] p Conclusions: In CA survivors, a desire to change financial or healthcare-related advanced directives during the COVID-19 outbreak was associated with increased pandemic-related anxiety. The causality and directionality of this relationship require further, qualitative study.

An amendment to this paper has been published and can be accessed via the original article.

The fundamental changes in power supply and increasing decentralization require more active grid operation and an increased integration of ICT at all power system actors. This trend raises complexity and increasingly leads to interactions between primary grid operation and ICT as well as different power system actors. For example, virtual power plants control various assets in the distribution grid via ICT to jointly market existing flexibilities. Failures of ICT or targeted attacks can thus have serious effects on security of supply and system stability. This paper presents a holistic approach to providing methods specifically for actors in the power system for prevention, detection, and reaction to ICT attacks and failures. The focus of our measures are solutions for ICT monitoring, systems for the detection of ICT attacks and intrusions in the process network, and the provision of actionable guidelines as well as a practice environment for the response to potential ICT security incidents., 6 pages, 4 figures, to be published in Proceedings of the 2020 6th IEEE International Energy Conference (ENERGYCon)

Background Over 40 000 patients with COVID-19 have been hospitalised in New York City (NY, USA) as of April 28, 2020. Data on the epidemiology, clinical course, and outcomes of critically ill patients with COVID-19 in this setting are needed. Methods This prospective observational cohort study took place at two NewYork-Presbyterian hospitals affiliated with Columbia University Irving Medical Center in northern Manhattan. We prospectively identified adult patients (aged ≥18 years) admitted to both hospitals from March 2 to April 1, 2020, who were diagnosed with laboratory-confirmed COVID-19 and were critically ill with acute hypoxaemic respiratory failure, and collected clinical, biomarker, and treatment data. The primary outcome was the rate of in-hospital death. Secondary outcomes included frequency and duration of invasive mechanical ventilation, frequency of vasopressor use and renal replacement therapy, and time to in-hospital clinical deterioration following admission. The relation between clinical risk factors, biomarkers, and in-hospital mortality was modelled using Cox proportional hazards regression. Follow-up time was right-censored on April 28, 2020 so that each patient had at least 28 days of observation. Findings Between March 2 and April 1, 2020, 1150 adults were admitted to both hospitals with laboratory-confirmed COVID-19, of which 257 (22%) were critically ill. The median age of patients was 62 years (IQR 51-72), 171 (67%) were men. 212 (82%) patients had at least one chronic illness, the most common of which were hypertension (162 [63%]) and diabetes (92 [36%]). 119 (46%) patients had obesity. As of April 28, 2020, 101 (39%) patients had died and 94 (37%) remained hospitalised. 203 (79%) patients received invasive mechanical ventilation for a median of 18 days (IQR 9-28), 170 (66%) of 257 patients received vasopressors and 79 (31%) received renal replacement therapy. The median time to in-hospital deterioration was 3 days (IQR 1-6). In the multivariable Cox model, older age (adjusted hazard ratio [aHR] 1·31 [1·09-1·57] per 10-year increase), chronic cardiac disease (aHR 1·76 [1·08-2·86]), chronic pulmonary disease (aHR 2·94 [1·48-5·84]), higher concentrations of interleukin-6 (aHR 1·11 [95%CI 1·02-1·20] per decile increase), and higher concentrations of D-dimer (aHR 1·10 [1·01-1·19] per decile increase) were independently associated with in-hospital mortality. Interpretation Critical illness among patients hospitalised with COVID-19 in New York City is common and associated with a high frequency of invasive mechanical ventilation, extrapulmonary organ dysfunction, and substantial in-hospital mortality. Funding National Institute of Allergy and Infectious Diseases and the National Center for Advancing Translational Sciences, National Institutes of Health, and the Columbia University Irving Institute for Clinical and Translational Research.

Objectives The aim of this study is to evaluate the efficacy and safety of human anti-SARS-CoV-2 convalescent plasma in hospitalized adults with severe SARS-CoV-2 infection. Trial Design This is a prospective, single-center, phase 2, randomized, controlled trial that is blinded to participants and clinical outcome assessor. Participants Eligible participants include adults (≥ 18 years) with evidence of SARS-CoV-2 infection by PCR test of nasopharyngeal or oropharyngeal swab within 14 days of randomization, evidence of infiltrates on chest radiography, peripheral capillary oxygen saturation (SpO2) ≤ 94% on room air, and/or need for supplemental oxygen, non-invasive mechanical ventilation, or invasive mechanical ventilation, who are willing and able to provide written informed consent prior to performing study procedures or who have a legally authorized representative available to do so. Exclusion criteria include participation in another clinical trial of anti-viral agent(s)* for coronavirus disease-2019 (COVID-19), receipt of any anti-viral agent(s)* with possible activity against SARS-CoV-2 *Use of remdesivir as treatment for COVID-19 is permitted. The study will be undertaken at Columbia University Irving Medical Center in New York, USA. Intervention and comparator The investigational treatment is anti-SARS-CoV-2 human convalescent plasma. To procure the investigational treatment, volunteers who recovered from COVID-19 will undergo testing to confirm the presence of anti-SARS-CoV-2 antibody to the spike trimer at a 1:400 dilution. Donors will also be screened for transfusion-transmitted infections (e.g. HIV, HBV, HCV, WNV, HTLV-I/II, T. cruzi, ZIKV). If donors have experienced COVID-19 symptoms within 28 days, they will be screened with a nasopharyngeal swab to confirm they are SARS-CoV-2 PCR-negative. Plasma will be collected using standard apheresis technology by the New York Blood Center. Study participants will be randomized in a 2:1 ratio to receive one unit (200 – 250 mL) of anti-SARS-CoV-2 plasma versus one unit (200 – 250 mL) of the earliest available control plasma. The control plasma cannot be tested for presence of anti-SARS-CoV-2 antibody prior to the transfusion, but will be tested for anti- SARS-CoV-2 antibody after the transfusion to allow for a retrospective per-protocol analysis. Main outcomes The primary endpoint is time to clinical improvement. This is defined as time from randomization to either discharge from the hospital or improvement by one point on the following seven-point ordinal scale, whichever occurs first. 1. Not hospitalized with resumption of normal activities 2. Not hospitalized, but unable to resume normal activities 3. Hospitalized, not requiring supplemental oxygen 4. Hospitalized, requiring supplemental oxygen 5. Hospitalized, requiring high-flow oxygen therapy or non-invasive mechanical ventilation 6. Hospitalized, requiring ECMO, invasive mechanical ventilation, or both 7. Death This scale, designed to assess clinical status over time, was based on that recommended by the World Health Organization for use in determining efficacy end-points in clinical trials in hospitalized patients with COVID-19. A recent clinical trial evaluating the efficacy and safety of lopinavir- ritonavir for patients hospitalized with severe COVID-19 used a similar ordinal scale, as have recent clinical trials of novel therapeutics for severe influenza, including a post-hoc analysis of a trial evaluating immune plasma. The primary safety endpoints are cumulative incidence of grade 3 and 4 adverse events and cumulative incidence of serious adverse events during the study period. Randomization Study participants will be randomized in a 2:1 ratio to receive anti-SARS-CoV-2 plasma versus control plasma using a web-based randomization platform. Treatment assignments will be generated using randomly permuted blocks of different sizes to minimize imbalance while also minimizing predictability. Blinding (masking) The study participants and the clinicians who will evaluate post-treatment outcomes will be blinded to group assignment. The blood bank and the clinical research team will not be blinded to group assignment. Numbers to be randomized (sample size) We plan to enroll 129 participants, with 86 in the anti-SARS-CoV-2 arm, and 43 in the control arm. Among the participants, we expect ~70% or n = 72 will achieve clinical improvement. This will yield an 80% power for a one-sided Wald test at 0.15 level of significance under the proportional hazards model with a hazard ratio of 1.5. Trial Status Protocol AAAS9924, Version 17APR2020, 4/17/2020 Start of recruitment: April 20, 2020 Recruitment is ongoing. Trial registration ClinicalTrials.gov: NCT04359810 Date of trial registration: April 24, 2020 Retrospectively registered Full protocol The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest of expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

Vaginal bleeding is not uncommon in the first trimester of pregnancy. The majority of such patients will have a normal intrauterine pregnancy (IUP), a nonviable IUP, or an ectopic pregnancy. Ultrasound (US) is the primary imaging modality in evaluation of these patients. US, along with clinical observations and serum human chorionic gonadotropin levels, can usually distinguish these causes. Although it is important to diagnose ectopic pregnancies and nonviable IUPs, one should also guard against injury to normal pregnancies due to inappropriate treatment with methotrexate or surgical intervention. Less common causes of first trimester vaginal bleeding include gestational trophoblastic disease and arteriovenous malformations. Pulsed methods of Doppler US should generally be avoided in the first trimester when there is a normal, or a potentially normal, IUP. Once a normal IUP has been excluded, Doppler US may be useful when other diagnoses such as retained products of conception or arteriovenous malformations are suspected. MRI may occasionally be helpful as a problem-solving tool. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

State-of-the-art deep neural network recognition systems are designed for a static and closed world. It is usually assumed that the distribution at test time will be the same as the distribution during training. As a result, classifiers are forced to categorise observations into one out of a set of predefined semantic classes. Robotic problems are dynamic and open world; a robot will likely observe objects that are from outside of the training set distribution. Classifier outputs in robotic applications can lead to real-world robotic action and as such, a practical recognition system should not silently fail by confidently misclassifying novel observations. We show how a deep metric learning classification system can be applied to such open set recognition problems, allowing the classifier to label novel observations as unknown. Further to detecting novel examples, we propose an open set active learning approach that allows a robot to efficiently query a user about unknown observations. Our approach enables a robot to improve its understanding of the true distribution of data in the environment, from a small number of label queries. Experimental results show that our approach significantly outperforms comparable methods in both the open set recognition and active learning problems., Comment: Accepted to the 2019 IEEE International Conference on Robotics and Automation (ICRA)

Stroke is the leading cause of long-term disability. Stroke patients can recover faster with personalized therapy treatments. This requires both clinical assessments and in-home assessments of daily activities. In this paper, we propose a daily activity recognition and assessment system for stroke patients. Our system is able to classify daily activities in real home environments and quantitatively evaluate upper body motions while preserving privacy by utilizing depth videos. Specifically, our system collects the depth videos and skeletal joint data of daily activities using a VicoVR sensor. It then recognizes and localizes clinically relevant actions from continuous untrimmed depth videos using a customized convolutional de-convolutional network. In addition, it assesses the extent of reach and speed metrics of both hands using skeletal joint data. The system has been tested on simulated cooking videos and real-life cooking videos in various kitchens with different room layouts and light conditions. The action recognition accuracies for simulated and real-life videos can reach 90.9% and 87.5%, respectively. With the valuable assessment feedback of our system, therapists can make better personalized treatments for stroke patients.

We present a Gaussian kernel loss function and training algorithm for convolutional neural networks that can be directly applied to both distance metric learning and image classification problems. Our method treats all training features from a deep neural network as Gaussian kernel centres and computes loss by summing the influence of a feature's nearby centres in the feature embedding space. Our approach is made scalable by treating it as an approximate nearest neighbour search problem. We show how to make end-to-end learning feasible, resulting in a well formed embedding space, in which semantically related instances are likely to be located near one another, regardless of whether or not the network was trained on those classes. Our approach outperforms state-of-the-art deep metric learning approaches on embedding learning challenges, as well as conventional softmax classification on several datasets., Accepted in the International Conference on Image Processing (ICIP) 2018. Formerly titled Nearest Neighbour Radial Basis Function Solvers for Deep Neural Networks

Vaginal bleeding is not uncommon in the first trimester of pregnancy. The majority of such patients will have a normal intrauterine pregnancy (IUP), a nonviable IUP, or an ectopic pregnancy. Ultrasound (US) is the primary imaging modality in evaluation of these patients. US, along with clinical observations and serum human chorionic gonadotropin levels, can usually distinguish these causes. Although it is important to diagnose ectopic pregnancies and nonviable IUPs, one should also guard against injury to normal pregnancies due to inappropriate treatment with methotrexate or surgical intervention. Less common causes of first trimester vaginal bleeding include gestational trophoblastic disease and arteriovenous malformations. Pulsed methods of Doppler US should generally be avoided in the first trimester when there is a normal, or a potentially normal, IUP. Once a normal IUP has been excluded, Doppler US may be useful when other diagnoses such as retained products of conception or arteriovenous malformations are suspected. MRI may occasionally be helpful as a problem-solving tool. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Conventional approaches to semantic segmentation are inappropriate for robotic applications, as they focus on pixel-level performance and give little significance to spurious object detections. This paper presents a region-based conditional random field model for semantic segmentation that focuses on object-level performance, recognising that in a robotics context, false object detections can have costly consequences. We show how optimising at the semantic regionlevel results in significantly fewer false positive object detections than conventional approaches. We further show how both object and pixel-level performance can be improved over conventional methods by combining region random fields with dense pixel random fields in a hierarchical manner. An object-aware performance metric is introduced that heavily penalises false positive and false negative object detections, as appropriate for robotic applications. Our approach is evaluated on the challenging NYU v2 and Pascal VOC datasets, outperforming comparable conventional methods in terms of object and pixellevel performance.

Although there is limited evidence that antepartum testing decreases the risk for fetal death in low-risk pregnancies, women with high-risk factors for stillbirth should undergo antenatal fetal surveillance. The strongest evidence supporting antepartum testing pertains to pregnancies complicated by intrauterine fetal growth restriction secondary to uteroplacental insufficiency. The main ultrasound-based modalities to determine fetal health are the biophysical profile, modified biophysical profile, and duplex Doppler velocimetry. In patients at risk for cardiovascular compromise, fetal echocardiography may also be indicated to ensure fetal well-being. Although no single antenatal test has been shown to be superior, all have high negative predictive values. Weekly or twice-weekly fetal testing has become the standard practice in high-risk pregnancies. The timing for the initiation of assessments of fetal well-being should be tailored on the basis of the risk for stillbirth and the likelihood of survival with intervention. The ACR Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer-reviewed journals and the application of well-established methodologies (the RAND/UCLA Appropriateness Method and the Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances in which evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Acute pelvic pain in premenopausal women frequently poses a diagnostic dilemma. These patients may exhibit nonspecific signs and symptoms such as nausea, vomiting and leukocytosis. The cause of pelvic pain includes a myriad of diagnostic possibilities such as obstetric, gynecologic, urologic, gastrointestinal, and vascular etiologies. The choice of the imaging modality is usually determined by a suspected clinical differential diagnosis. Thus the patient should undergo careful evaluation and the suspected differential diagnosis should be narrowed before an optimal imaging modality is chosen. Transvaginal and transabdominal pelvic sonography is the modality of choice, to assess for pelvic pain, when an obstetric or gynecologic etiology is suspected and computed tomography is often more useful when gastrointestinal or genitourinary pathology is thought to be more likely. Magnetic resonance imaging, when available in the acute setting, is favored over computed tomography for assessing pregnant patients for nongynecologic etiologies owing to its lack of ionizing radiation.The American College of Radiology Appropriateness Criteria® are evidence-based guidelines for specific clinical conditions that are reviewed every three years by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances where evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment.