bluuebunny/crossref_metadata_2025_split huggingface dataset:
Surgical Morbidity and Mortality From the Multicenter Randomized Controlled NeoRes II Trial
Authors: Nilsson Klara , Klevebro Fredrik , Rouvelas Ioannis , Lindblad Mats , Szabo Eva , Halldestam Ingvar , Smedh Ulrika , Wallner Bengt , Johansson Jan , Johnsen Gjermund , Aahlin Eirik Kjus , Johannessen Hans-Olaf , Hjortland Geir Olav , Bartella Isabel , Schröder Wolfgang , Bruns Christiane , Nilsson Magnus 
Published: August 2020

Objective:
To investigate if prolonged TTS after completed nCRT improves postoperative outcomes for esophageal and esophagogastric junction cancer.

Summary of Background Data:
TTS has traditionally been 4–6 weeks after completed nCRT. However, the optimal timing is not known.

Methods:
A multicenter clinical trial was performed with randomized allocation of TTS of 4–6 or 10–12 weeks. The primary endpoint of this sub-study was overall postoperative complications defined as Clavien-Dindo grade II-V. Secondary endpoints included complication severity according to Clavien-Dindo grade IIIb-V, postoperative 90-day mortality, and length of hospital stay. The study was registered in Clinicaltrials.gov (NCT02415101).

Results:
In total 249 patients were randomized. There were no significant differences between standard TTS and prolonged TTS with regard to overall incidence of complications Clavien-Dindo grade II–V (63.2% vs 72.6%, P = 0.134) or regarding Clavien-Dindo grade IIIb–V complications (31.6% vs 34.9%, P = 0.603). There were no statistically significant differences between standard and prolonged TTS regarding anastomotic leak (P = 0.596), conduit necrosis (P = 0.524), chyle leak (P = 0.427), pneumonia (P = 0.548), and respiratory failure (P = 0.723). In the standard TTS arm 5 patients (4.3%) died within 90 days of surgery, compared to 4 patients (3.8%) in the prolonged TTS arm (P = 1.0). Median length of hospital stay was 15 days in the standard TTS arm and 17 days in the prolonged TTS arm (P = 0.234).

Conclusion:
The timing of surgery after completed nCRT for carcinoma of the esophagus or esophagogastric junction, is not of major importance with regard to short-term postoperative outcomes.
SARS-CoV-2 Infections Among Children in the Biospecimens from Respiratory Virus-Exposed Kids (BRAVE Kids) Study
Authors: Hurst Jillian H. , Heston Sarah M. , Chambers Hailey N. , Cunningham Hannah M. , Price Meghan J. , Suarez Liliana , Crew Carter G. , Bose Shree , Aquino Jhoanna N. , Carr Stuart T. , Griffin S. Michelle , Smith Stephanie H. , Jenkins Kirsten , Pfeiffer Trevor S. , Rodriguez Javier , DeMarco C. Todd , De Naeyer Nicole A. , Gurley Thaddeus C. , Louzao Raul , Cunningham Coleen K. , Steinbach William J. , Denny Thomas N. , Lugo Debra J. , Moody M. Anthony , Permar Sallie R. , Rotta Alexandre T. , Turner Nicholas A. , Walter Emmanuel B. , Woods Christopher W. , Kelly Matthew S. 
Published: August 2020

ABSTRACTBACKGROUNDChildren with SARS-CoV-2 infection typically have mild symptoms that do not require medical attention, leaving a gap in our understanding of the spectrum of illnesses that the virus causes in children.METHODSWe conducted a prospective cohort study of children and adolescents (<21 years of age) with a SARS-CoV-2-infected close contact. We collected nasopharyngeal or nasal swabs at enrollment and tested for SARS-CoV-2 using a real-time PCR assay.RESULTSOf 382 children, 289 (76%) were SARS-CoV-2-infected. SARS-CoV-2-infected children were more likely to be Hispanic (p<0.0001), less likely to have a history of asthma (p=0.009), and more likely to have an infected sibling contact (p=0.0007) than uninfected children. Children ages 6-13 years were frequently asymptomatic (38%) and had respiratory symptoms less often than younger children (30% vs. 49%; p=0.008) or adolescents (30% vs. 59%; p<0.0001). Compared to children ages 6-13 years, adolescents more frequently reported influenza-like (61% vs. 39%; p=0.002), gastrointestinal (26% vs. 9%; p=0.003), and sensory symptoms (43% vs. 9%; p<0.0001), and had more prolonged illnesses [median (IQR) duration: 7 (4, 12) vs. 4 (3, 8) days; p=0.004]. Despite the age-related variability in symptoms, we found no differences in nasopharyngeal viral load by age or between symptomatic and asymptomatic children.CONCLUSIONSHispanic ethnicity and an infected sibling close contact are associated with increased SARS-CoV-2 infection risk among children, while a history of asthma is associated with decreased risk. Age-related differences in the clinical manifestations of SARS-CoV-2 infection must be considered when evaluating children for COVID-19 and in developing screening strategies for schools and childcare settings.
Laboratory biomarkers associated with COVID-19 severity and management
Authors: Keddie S , Ziff O , Chou MKL , Taylor RL , Heslegrave A , Garr E , Lakdawala N , Church A , Ludwig D , Manson J , Scully M , Nastouli E , Chapman MD , Hart M , Lunn MP 
Published: August 2020

AbstractThe heterogeneous disease course of COVID-19 is unpredictable, ranging from mild self-limiting symptoms to cytokine storms, acute respiratory distress syndrome (ARDS), multi-organ failure and death. Identification of high-risk cases will enable appropriate intervention and escalation. This study investigates the routine laboratory tests and cytokines implicated in COVID-19 for their potential application as biomarkers of disease severity, respiratory failure and need of higher-level care.From analysis of 203 samples, CRP, IL-6, IL-10 and LDH were most strongly correlated with the WHO ordinal scale of illness severity, the fraction of inspired oxygen delivery, radiological evidence of ARDS and level of respiratory support (p≤0.001). IL-6 levels of ≥3.27pg/ml provide a sensitivity of 0.87 and specificity of 0.64 for a requirement of ventilation, and a CRP of ≥37mg/L of 0.91 and 0.66.Reliable stratification of high-risk cases has significant implications on patient triage, resource management and potentially the initiation of novel therapies in severe patients.
Clinical and molecular heterogeneity of pineal parenchymal tumors: a consensus study
Authors: Liu Anthony P.Y. , Li Bryan K. , Pfaff Elke , Gudenas Brian , Vasiljevic Alexandre , Orr Brent A. , Dufour Christelle , Snuderl Matija , Karajannis Matthias A. , Rosenblum Marc K. , Hwang Eugene I. , Ng Ho-Keung , Hansford Jordan R. , Szathmari Alexandru , Faure-Conter Cécile , Merchant Thomas E. , von Hoff Katja , Mynarek Martin , Rutkowski Stefan , Sahm Felix , Hawkins Cynthia , Robinson Giles W. , Gajjar Amar , Pfister Stefan M. , Bouffet Eric , Northcott Paul A. , Jones David T.W. , Huang Annie 
Published: August 2020

AbstractBackgroundRecent genomic studies have shed light on the biology and inter-tumoral heterogeneity underlying pineal parenchymal tumors, in particular pineoblastomas (PBs) and pineal parenchymal tumors of intermediate differentiation (PPTIDs). Previous reports, however, had modest sample sizes and lacked power to integrate molecular and clinical findings. The different proposed subgroup structures also highlighted a need to reach consensus on a robust and relevant classification system.MethodsWe performed a meta-analysis on 221 patients with molecularly characterized PBs and PPTIDs. DNA methylation profiles were analyzed through complementary bioinformatic approaches and molecular subgrouping was harmonized. Demographic, clinical and genomic features of patients and samples from these pineal tumor subgroups were annotated.FindingsFour clinically and biologically relevant consensus PB subgroups were defined: PB-miRNA1 (n=96), PB-miRNA2 (n=23), PB-MYC/FOXR2 (n=34) and PB-RB1 (n=25); with PPTID (n=43) remaining as a molecularly distinct entity. Genomic and transcriptomic profiling allowed the characterization of oncogenic drivers for individual subgroups, specifically, alterations in the microRNA processing pathway in PB-miRNA1/2,MYCamplification andFOXR2overexpression in PB-MYC/FOXR2,RB1alteration in PB-RB1, andKBTBD4insertion in PPTID. Age at diagnosis, sex predilection and metastatic status varied significantly among tumor subgroups. While patients with PB-miRNA2 and PPTID had superior outcome, survival was intermediate for patients with PB-miRNA1, and dismal for those with PB-MYC/FOXR2 and PB-RB1.InterpretationWe systematically interrogated the clinical and molecular heterogeneity within pineal parenchymal tumors and proposed a consensus nomenclature for disease subgroups, laying the groundwork for future studies as well as routine use in tumor classification.
The Prognostic Value of Eosinophil Recovery in COVID-19: A Multicentre, Retrospective Cohort Study on Patients Hospitalised in Spanish Hospitals
Authors: González María Mateos , Gonzalo Elena Sierra , Lopez Irene Casado , Fernández Francisco Arnalich , Pérez José Luis Beato , Monge Daniel Monge , Núñez Juan Antonio Vargas , Fenoll Rosa García , Fernández Carmen Suárez , Castro Santiago Jesús Freire , Bailon Manuel Mendez , Fraile Isabel Perales , Madrazo Manuel , Fontan Paula Maria Pesqueira , Gamboa Jeffrey Oskar Magallanes , García Andrés González , Vieitez Anxela Crestelo , Aizpuru Eva María Fonseca , Arostegui Asier Aranguren , Erdozain Ainara Coduras , Cilleros Carmen Martinez , Amigo Jose Loureiro , Epelde Francisco , Bermejo Carlos Lumbreras , Santos Juan Miguel Antón ,   for the SEMI-COVID-19 Network
Published: August 2020

ABSTRACTObjectivesA decrease in blood cell counts, especially lymphocytes and eosinophils, has been described in patients with severe SARS-CoV-2 (COVID-19), but there is no knowledge of the potential role of their recovery in these patients’ prognosis. This article aims to analyse the effect of blood cell depletion and blood cell recovery on mortality due to COVID-19.DesignThis work is a multicentre, retrospective, cohort study of 9,644 hospitalised patients with confirmed COVID-19 from the Spanish Society of Internal Medicine’s SEMI-COVID-19 Registry.SettingThis study examined patients hospitalised in 147 hospitals throughout Spain.ParticipantsThis work analysed 9,644 patients (57.12% male) out of a cohort of 12,826 patients ≥18 years of age hospitalised with COVID-19 in Spain included in the SEMI-COVID-19 Registry as of 29 May 2020.Main outcome measuresThe main outcome measure of this work is the effect of blood cell depletion and blood cell recovery on mortality due to COVID-19. Univariate analysis was performed to determine possible predictors of death and then multivariate analysis was carried out to control for potential confounders.ResultsAn increase in the eosinophil count on the seventh day of hospitalisation was associated with a better prognosis, including lower mortality rates (5.2% vs 22.6% in non-recoverers, OR 0.234 [95% CI, 0.154 to 0.354]) and lower complication rates, especially regarding to development of acute respiratory distress syndrome (8% vs 20.1%, p=0.000) and ICU admission (5.4% vs 10.8%, p=0.000). Lymphocyte recovery was found to have no effect on prognosis. Treatment with inhaled or systemic glucocorticoids was not found to be a confounding factor.ConclusionEosinophil recovery in patients with COVID-19 is a reliable marker of a good prognosis that is independent of prior treatment. This finding could be used to guide discharge decisions.
Machine learning and AI aided tool to differentiate COVID 19 and non-COVID 19 lung CXR
Authors: Adwibowo Andrio 
Published: August 2020

AbstractOne of the main challenges in dealing with the current COVID 19 pandemic is how to detect and distinguish between the COVID 19 and non COVID 19 cases. This problem arises since COVID 19 symptoms resemble with other cases. One of the golden standards is by examining the lung using the chest X ray radiograph (CXR). Currently there is growing COVID 19 cases followed by the CXR images waiting to be analyzed and this may outnumber the health capacity. Learning from that current situation and to fulfill the demand for CXRs analysis, a novel solution is required. The tool is expected can detect and distinguish the COVID 19 case lung rely on CXR. Respectively, this study aims to propose the use of AI and machine learning aided tool to distinguish the COVID 19 and non COVID 19 cases based on the CXR lung image. The compared non COVID 19 CXR cases in this study include normal (healthy), influenza A, tuberculosis, and active smoker. The results confirm that the machine learning tool is able to distinguish the COVID 19 CXR lungs based on lung consolidation. Moreover, the tool is also able to recognize an abnormality of COVID 19 lung in the form of patchy ground glass opacity.To conclude, AI and machine learning may be considered as a detection tool to identify and distinguish between COVID 19 and non COVID 19 cases in particular epidemic areas.
Covid-19 transmission dynamics during the unlock phase and significance of testing
Authors: Paul Abhijit , Chatterjee Samrat , Bairagi Nandadulal 
Published: August 2020

AbstractThe pandemic disease Covid-19 caused by SARS-COV-2, which emerged from Wuhan, China, has established itself as the most devastating disease in the history of infectious disease, affecting 216 countries/territories across the world. Different countries have developed and adopted various policies to contain this epidemic and the most common were the social distancing and lockdown. Though some countries have come out of this pandemic, the infection is still increasing and remains very serious in the rest of the world. Even when the disease is not under control, many countries have withdrawn the lockdown and going through the phase-wise unlocking process, causing a further increment in the infection rate. In such a scenario, the role of the undetected class of infected individuals has become very crucial. The present study is an attempt to understand and estimate the possible epidemic burden during the unlock phase in the presence of an undetected class. We proposed a modified SEIR model and dissected the epidemiological status of different countries with the available data. With the initial establishment of the model with the epidemic data of four countries, which have already attained the epidemic peak, the study focused more on countries like India and the USA, where the epidemic curve is still growing, but the unlock process has started. As a straightforward result, we noticed a significant increase in the undetected and detected infected cases under the ongoing unlock phase. Under such conditions, our recalibration exercise showed that an increase in the testing could revert the existing growth rate of the infected cases to the lower growth rate of the lockdown period. Our present study emphasizes on the implementation of 3T principles, trace, test, and treat, to contain the epidemic. The significance of large scale testing in controlling the epidemic is true for both India and the USA though they have different socio-economic conditions. The use of repurposing drugs may further decrease the infected cases and help the disease controlling process. We believe our proposed strategy obtained through a mathematical model will help to make a better policy for the unlock phase.
COSTS ASSOCIATED WITH TRANSRADIAL ACCESS AND SAME-DAY DISCHARGE AFTER PERCUTANEOUS CORONARY INTERVENTION: A SYSTEMATIC REVIEW AND META-ANALYSIS
Authors: Kulkarni Hemant , Thangam Manoj , Lindner Samuel , McNeely Christian , Amin Amit P. 
Published: August 2020

AbstractIntroductionTransradial access for PCI (TRI) along with same day discharge (SDD) is associated with varying estimates of cost savings depending on the population studied, the clinical scenario and application to low-risk vs high-risk patients. A summary estimate of the true cost savings of TRI and SDD are unknown.MethodsWe searched the PubMed, EMBASE®, CINAHL® and Google Scholar® databases for published studies on hospitalization costs of TRI and SDD. Primary outcome of interest in all included studies was the cost saving with TRI (or SDD), inflation-corrected US$ 2018 values using the medical consumer price index. For meta-analytic synthesis, we used Hedges’ summary estimate (g) in a random-effects framework of the DerSimonian and Laird model, with inverse variance weights. Heterogeneity was quantified using the 12 statistic.ResultsThe cost savings of TRI from four US studies reported a consistent and significant cost saving associated with TRI after accounting for currency inflation, of US$ 992 (95% CI US$ 8501,134). The cost savings of SDD from six US studies, after inflation-correcting to the year 2018, were US$ 3,567.58 (95% CI US$ 2,303 –4,832).ConclusionsIn conclusion, this meta-analysis demonstrates that TRI and SDD are associated with mean cost reductions of by approximately US$1,000/patient and US$ 3,600/patient, respectively, albeit with wide heterogeneity in the cost estimates. When combined with the safety of TRI and SDD, this meta-analysis underscores the value of combining TRI and SDD pathways and calls for a wide-ranging practice change in the direction of TRI and SDD.
Individualizing deep dynamic models for psychological resilience data
Authors: Köber Göran , Pooseh Shakoor , Engen Haakon , Chmitorz Andrea , Kampa Miriam , Schick Anita , Sebastian Alexandra , Tüscher Oliver , Wessa Michèle , Yuen Kenneth S.L. , Walter Henrik , Kalisch Raffael , Timmer Jens , Binder Harald 
Published: August 2020

ABSTRACTDeep learning approaches can uncover complex patterns in data. In particular, variational autoencoders (VAEs) achieve this by a non-linear mapping of data into a low-dimensional latent space. Motivated by an application to psychological resilience in the Mainz Resilience Project (MARP), which features intermittent longitudinal measurements of stressors and mental health, we propose an approach for individualized, dynamic modeling in this latent space. Specifically, we utilize ordinary differential equations (ODEs) and develop a novel technique for obtaining person-specific ODE parameters even in settings with a rather small number of individuals and observations, incomplete data, and a differing number of observations per individual. This technique allows us to subsequently investigate individual reactions to stimuli, such as the mental health impact of stressors. A potentially large number of baseline characteristics can then be linked to this individual response by regularized regression, e.g., for identifying resilience factors. Thus, our new method provides a way of connecting different kinds of complex longitudinal and baseline measures via individualized, dynamic models. The promising results obtained in the exemplary resilience application indicate that our proposal for dynamic deep learning might also be more generally useful for other application domains.
Persistence of SARS-CoV-2 in the first trimester placenta leading to vertical transmission and fetal demise from an asymptomatic mother
Authors: Shende Prajakta , Gaikwad Pradip , Gandhewar Manisha , Ukey Pawankumar , Bhide Anshul , Patel Vainav , Bhagat Sharad , Bhor Vikrant , Mahale Smita , Gajbhiye Rahul , Modi Deepak 
Published: August 2020

SummaryCoronaviruses infect the respiratory tract and are known to survive in these tissues during the clinical course of infection. However, how long can SARS-CoV-2 survive in the tissues is hitherto unknown. Herein, we report a case where the virus is detected in the first trimester placental cytotrophoblast and syncytiotrophoblasts five weeks after the asymptomatic mother cleared the virus from the respiratory tract. This first trimester placental infection was vertically transmitted as the virus was detected in the amniotic fluid and fetal membranes. This congenitally acquired SARS-CoV-2 infection was associated with hydrops and fetal demise. This is the first study providing concrete evidences towards persistent tissue infection of SARS-CoV-2, its congenital transmission in early pregnancy leading to intrauterine fetal death.
OxCOVID19 Database, a multimodal data repository for better understanding the global impact of COVID-19
Authors: Mahdi Adam , Błaszczyk Piotr , Dłotko Paweł , Salvi Dario , Chan Tak-Shing , Harvey John , Gurnari Davide , Wu Yue , Farhat Ahmad , Hellmer Niklas , Zarebski Alexander , Hogan Bernie , Tarassenko Lionel 
Published: August 2020

ABSTRACTOxford COVID-19 Database (OxCOVID19 Database) is a comprehensive source of information related to the COVID-19 pandemic. This relational database contains time-series data on epidemiology, government responses, mobility, weather and more across time and space for all countries at the national level, and for more than 50 countries at the regional level. It is curated from a variety of (wherever available) official sources. Its purpose is to facilitate the analysis of the spread of SARS-CoV-2 virus and to assess the effects of non-pharmaceutical interventions to reduce the impact of the pandemic. Our database is a freely available, daily updated tool that provides unified and granular information across geographical regions.
SARS-CoV-2 Serologic Assays in Control and Unknown Populations Demonstrate the Necessity of Virus Neutralization Testing
Authors: Rathe Jennifer A. , Hemann Emily A. , Eggenberger Julie , Li Zhaoqi , Knoll Megan L. , Stokes Caleb , Hsiang Tien-Ying , Netland Jason , Takehara Kennidy , Pepper Marion , Gale Michael 
Published: August 2020

AbstractBackgroundTo determine how serologic antibody testing outcome links with virus neutralization of SARS-CoV-2 to ascertain immune protection status, we evaluated a unique set of individuals for SARS-CoV-2 antibody detection and viral neutralization.MethodsHerein, we compare several analytic platforms with 15 positive and 30 negative SARS-CoV-2 infected controls followed by viral neutralization assessment. We then applied these platforms in a clinically relevant population: 114 individuals with unknown histories of SARS-CoV-2 infection.ResultsIn control populations, the best performing antibody detection assays were SARS-CoV-2 receptor binding domain (RBD) IgG (specificity 87%, sensitivity 100%, PPV 100%, NPV 93%), spike IgG3 (specificity 93%, sensitivity 97%, PPV 93%, NPV 97%), and nucleocapsid (NP) protein IgG (specificity 93%, sensitivity 97%, PPV 93%, NPV 97%). Neutralization of positive and negative control sera showed 100% agreement. 20 unknown individuals had detectable SARS-CoV-2 antibodies with 16 demonstrating virus neutralization. The antibody assays that best predicted virus neutralization were RBD IgG (misidentified 2), spike IgG3 (misidentified 1), and NP IgG (misidentified 2).ConclusionThese data suggest that meaningful evaluation of antibody assay performance requires testing in an unknown population. Further, these results indicate coupling of virus neutralization analysis to a positive antibody test is required to categorize patients based on SARS-CoV-2 immune protection status following virus exposure or vaccine administration. One of the antibody detection platforms identified in this study followed by the pseudoneutralization or focus reduction assay would provide a practical testing strategy to assess for SARS-CoV-2 antibodies with optimal prediction of correlates to neutralizing immunity.FundingSupported by NIH grants AI148684, AI151698, AI145296, and UW funds to the Center for Innate Immunity and Immune Disease.