bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of body mass index on SAPS3 prognostic performance in critically ill patients from Brazil
Authors: Ferreira Isabella B. B. , Menezes Rodrigo C. , Otero Matheus L. , Carmo Thomas A. , Telles Gabriel P. , Fahel Bruno V. B. , Barral-Netto Manoel , Arriaga Maria B. , Fukutani Kiyoshi F. , Neto Licurgo Pamplona , Agareno Gabriel A. , Agareno Sydney , Akrami Kevan M. , Filho Nivaldo M.Filgueiras , Andrade Bruno B. 
Published: May 2020

AbstractObesity has emerged as a significant global health problem, and its association with increased morbidity and mortality is well established. An obesity paradox has been extensively documented in the critically ill, appearing as a protective factor. Whether body mass index (BMI) impacts critical care severity scores has not been extensively studied previously, particularly in developing countries. This study aimed to evaluate the performance of severity scores across different BMI categories in a tertiary intensive care unit in Brazil. Observational and analytical cohort study in a general ICU in Northeastern Brazil between August 2015 and July 2018 that included all patients over 18 years of age admitted to the ICU. A total of 2,179 patients were included, with a mean age of 67.9 years and female predominance (53.1%). Similar to previous findings, those with overweight and obesity of any grade were not significantly associated with mortality, though for each additional 1kg/m2 there was a decrease of 0.04% in odds of death. The Simplified Acute Physiology Score III (SAPS3) accurately predicted mortality in all groups except in those underweight. Low weight appeared as an independent risk factor for mortality in the ICU. Furthermore, this is the first study to identify poor prognostic performance of a common ICU severity score in those with low weight, highlighting the need for alternative more precise metrics.
Incidence of COVID-19 in a cohort of adult and paediatric patients with rheumatic diseases treated with targeted biologic and synthetic disease-modifying anti-rheumatic drugs
Authors: Michelena Xabier , Borrell Helena , López-Corbeto Mireia , López-Lasanta María , Moreno Estefanía , Pascual-Pastor María , Erra Alba , Serrat Mayte , Espartal Esther , Antón Susana , Añez Gustavo Adolfo , Caparrós-Ruiz Raquel , Pluma Andrea , Trallero-Araguás Ernesto , Barceló-Bru Mireia , Almirall Miriam , De Agustín Juan José , Segura Jordi Lladós , Julià Antonio , Marsal Sara 
Published: May 2020

ABSTRACTOBJECTIVESTo investigate the incidence of COVID-19 in a cohort of adult and paediatric patients with rheumatic diseases receiving targeted biologic and synthetic disease modifying anti-rheumatic drugs (tDMARDs) and to explore the possible effect of these treatments in the clinical expression of COVID-19.METHODSA cross-sectional study comprising of a telephone survey and electronic health records review was performed including all adult and paediatric patients with rheumatic diseases treated with tDMARDs in a large rheumatology tertiary centre in Barcelona, Spain. Demographics, disease activity, COVID-19 related symptoms and contact history data were obtained from the start of the 2020 pandemic. Cumulative incidence of confirmed cases (SARS-CoV-2 positive PCR test) was compared to the population estimates for the same city districts from a governmental COVID-19 health database. Suspected cases were defined following WHO criteria and compared to those without compatible symptoms.RESULTS959 patients with rheumatic diseases treated with tDMARDs were included. We identified 11 confirmed SARS-CoV-2 positive cases in the adult cohort and no confirmed positive cases in the paediatric cohort. All patients had a successful recovery and only one patient required admission in the intensive care unit. When using the same classification criteria (only COVID-19 positive cases with pneumonia), COVID-19 incidence rates of the rheumatic patient cohort were very similar to that of the general population [(0.48% (95% CI 0.09 to 8.65%)] and [0.58% (95% CI 5.62 to 5.99%)], respectively. We found significant differences in tDMARDs proportions between the suspected and non-suspected cases (p=0.002).CONCLUSIONAdult and paediatric patients with rheumatic diseases on tDMARDs do not seem to present a higher risk of COVID-19 or a more severe disease outcome when compared to general population. Our exploratory analysis suggests that the proportion of COVID-19 suspected cases differs between tDMARDs.
A Simple Method for Estimating the Number of Unconfirmed COVID-19 Cases in a Local Area that Includes a Confidence Interval: A Case Study of Whatcom County, Washington
Authors: Swanson David A. , Cossman Ronald E. 
Published: May 2020

AbstractAlong with many other data problems affecting the unfolding of the COVID-10 pandemic in the United States, virtually nothing is known about the number of positive, unconfirmed cases, especially in local areas. We show that it is possible to estimate the number of positive, unconfirmed COVID-19 cases using a simple, long-established method employed by demographers to estimate a population in the absence of a census count. We go on to show how a confidence interval can be constructed around an estimate of positive, unconfirmed COVID-19 cases constructed from this method, using Whatcom County, Washington as a case study.
The distribution and spread of susceptible and resistantNeisseria gonorrhoeaeacross demographic groups in a major metropolitan center
Authors: Mortimer Tatum D. , Pathela Preeti , Crawley Addie , Rakeman Jennifer L. , Lin Ying , Harris Simon R. , Blank Susan , Schillinger Julia A. , Grad Yonatan H. 
Published: May 2020

AbstractBackgroundGenomic epidemiology studies of gonorrhea in the United States have primarily focused on national surveillance for antibiotic resistance, and patterns of local transmission between demographic groups of resistant and susceptible strains are unknown.MethodsWe analyzed a convenience sample of genome sequences, antibiotic susceptibility, and patient data from 897 gonococcal isolates cultured at the NYC Public Health Laboratory from NYC Department of Health and Mental Hygiene (DOHMH) Sexual Health Clinic (SHC) patients, primarily in 2012-13. We reconstructed the gonococcal phylogeny, defined transmission clusters using a 10 non-recombinant single nucleotide polymorphism threshold, tested for clustering of demographic groups, and placed NYC isolates in a global phylogenetic context.ResultsThe NYC gonococcal phylogeny reflected global diversity with isolates from 22/23 of the prevalent global lineages (96%). Isolates clustered on the phylogeny by patient sexual behavior (p<0.001) and race/ethnicity (p<0.001).Minimum inhibitory concentrations were higher across antibiotics in isolates from men who have sex with men compared to heterosexuals (p<0.001) and white heterosexuals compared to black heterosexuals (p<0.01). In our dataset, all large transmission clusters (≥10 samples) ofN. gonorrhoeaewere susceptible to ciprofloxacin, ceftriaxone, and azithromycin and comprised isolates from patients across demographic groups.ConclusionsAll large transmission clusters were susceptible to gonorrhea therapies, suggesting that resistance to empiric therapy was not a main driver of spread, even as risk for resistance varied across demographic groups. Further study of local transmission networks is needed to identify drivers of transmission.
Early evidence of a higher incidence of COVID-19 in the air-polluted regions of eight severely affected countries
Authors: Pansini Riccardo , Fornacca Davide 
Published: May 2020

AbstractCOVID-19 has spread in all continents in a span of just over three months, escalating into a pandemic that poses several humanitarian as well as scientific challenges. We here investigated the geographical character of the infection and correlate it with several annual satellite and ground indexes of air quality in: China, the United States, Italy, Iran, France, Spain, Germany, and the United Kingdom. Controlling for population size, we found more viral infections in those areas afflicted by high PM 2.5 and Nitrogen Dioxide values. Higher mortality was also correlated with relatively poor air quality. In Italy, the correspondence between the Po valley pollution and SARS-CoV-2 infections and induced mortality was the starkest, originating right in the most polluted European area. Air pollution appears to be for this disease a risk factor similar to smoking. This suggests the detrimental impact climate change will have on the trajectory of future respiratory epidemics.
Novel Spatiotemporal Feature Extraction Parallel Deep Neural Network for Forecasting Confirmed Cases of Coronavirus Disease 2019
Authors: Huang Chiou-Jye , Shen Yamin , Kuo Ping-Huan , Chen Yung-Hsiang 
Published: May 2020

AbstractThe coronavirus disease 2019 pandemic continues as of March 26 and spread to Europe on approximately February 24. A report from April 29 revealed 1.26 million confirmed cases and 125 928 deaths in Europe. This study proposed a novel deep neural network framework, COVID-19Net, which parallelly combines a convolutional neural network (CNN) and bidirectional gated recurrent units (GRUs). Three European countries with severe outbreaks were studied—Germany, Italy, and Spain—to extract spatiotemporal feature and predict the number of confirmed cases. The prediction results acquired from COVID-19Net were compared to those obtained using a CNN, GRU, and CNN-GRU. The mean absolute error, mean absolute percentage error, and root mean square error, which are commonly used model assessment indices, were used to compare the accuracy of the models. The results verified that COVID-19Net was notably more accurate than the other models. The mean absolute percentage error generated by COVID-19Net was 1.447 for Germany, 1.801 for Italy, and 2.828 for Spain, which were considerably lower than those of the other models. This indicated that the proposed framework can accurately predict the accumulated number of confirmed cases in the three countries and serve as a crucial reference for devising public health strategies.
Social Media Platforms for Health Communication and Research in the Face of COVID-19 Pandemic: A Cross Sectional Survey in Uganda
Authors: Olum Ronald , Bongomin Felix 
Published: May 2020

ABSTRACTObjectives(1) To examine the usage of social media and other forms of media among medical students (MS) and healthcare professionals (HCPs) in Uganda. (2) To assess the perceived usefulness of social media and other forms of media for COVID-19 public health campaigns.DesignA descriptive WhatsApp messenger-based cross-sectional survey in April 2020.SettingMakerere University Teaching Hospitals (MUTH) and 9 of the 10 medical schools in Uganda.ParticipantsHCPs at MUTH and MS in the 9 medical schools in Uganda.Main outcome measuresWe collected data on sociodemographic characteristics, sources of information on COVID-19, preferences of social media platform and perceived usefulness of the different media platforms for acquisition of knowledge on COVID-19.ResultOverall, response rate was 21.5% for both MS and HCPs. In total, 877 (HCPS [136, 15.5%], MS [741, 85.5%]) were studied. Majority (n=555, 63.3%) were male with a median age of 24 (range: 18-66) years. Social media was a source of information for 665 (75.8%) participants. Usage was similar among MS and HCPs (565/741 (76.2%) vs. 100/136 (73.5%), p=0.5). Among the MS, commonly used social media were: WhatsApp (n=705, 95.1%) Facebook (n=405, 54.8%), Twitter (n=290, 39.1%), Instagram (n=178, 24.0) and Telegram (n=80, 10.8%). Except for WhatsApp, male MS we more likely to use the other social media platforms (p= <0.001 − 0.01). Mass media (television and radio) and social media were preferred the most useful tools for dissemination of COVID-19 related information.ConclusionMore than two-thirds of MS and HCPs are routinely using social media in Uganda. Social media platforms may be used for dissemination of information as well as a research tool among MS and HCPs. Social media alongside other media platforms can also be used as sources of reliable information on COVID-19 as well as for dissemination of research findings and guidelines.Strengths and limitationsThis is the first study in sub Saharan Africa on the use of social media for research during the COVID-19 pandemic.The study also explores perceived usefulness of different media for COVID-19 public health campaigns.Diversity of the participants consisting both healthcare professionals and medical students.A relatively large sample size was enrolled in the survey despite a low response rate.
Perspectives of Cancer Patients and Their Health during the COVID-19 Pandemic
Authors: Lou Emil , Teoh Deanna , Brown Katherine , Blaes Anne , Holtan Shernan G. , Jewett Patricia , Parsons Helen , Mburu E. Waruiru , Thomaier Lauren , Hui Jane Yuet Ching , Nelson Heather H. , Vogel Rachel I. 
Published: May 2020

ABSTRACTIntroductionThe immunosuppressive nature of some cancers and many cancer-directed treatments may increase the risk of infection with and severe sequelae from Coronavirus Disease 2019 (COVID-19). The objective of this study was to compare concerns about COVID-19 among individuals undergoing cancer treatment to those with a history of cancer not currently receiving therapy and to those without a cancer history.MethodsWe conducted a cross-sectional anonymous online survey study of adults currently residing in the United States. Participants were recruited over a one-week period (April 3-11, 2020) using promoted advertisements on Facebook and Twitter. Groups were compared using chi-squared tests, Fisher’s exact tests, and t-tests.Results543 respondents from 47 states provided information on their cancer history and were included in analyses. Participants receiving active treatment reported greater concern about coronavirus infection (p<0.0001), higher levels of family distress caused by the COVID-19 pandemic (p=0.004), and greater concern that the general public does not adequately understand the seriousness of COVID-19 (p=0.04). Those with metastatic disease were more likely to indicate that COVID-19 had negatively affected their cancer care compared to patients with non-metastatic cancer (50.8% vs. 31.0%; p=0.02). The most commonly reported treatment modifications included chemotherapy delays.ConclusionsPatients undergoing active treatment for cancer were most concerned about the short-term effects of the COVID-19 pandemic on the logistics as well as potential efficacy of ongoing cancer treatment, longer term effects, and overarching societal concerns that the population at large is not as concerned about the public health implications of the coronavirus.
Modeling the COVID-19 outbreak in the United States
Authors: Narayanan Charit Samyak 
Published: May 2020

AbstractThe COVID-19 contagion has developed at an alarming rate in the US and as of April 24, 2020, tens of thousands of people have already died from the disease. In the event of an outbreak like such, forecasting the extent of the mortality that will occur is crucial to aid the implementation of effective interventions. Mortality depends on two factors: the case fatality rate and the case incidence. We combine a cohort-based model that determines case fatality rates along with a modified logistic model that evaluates the case incidence to determine the number of deaths in all the US states over time; the model is also able to include the impact of interventions. Both models yield exceptional goodness-of-fit. The model predicted a range of death outcomes (79k to 246k) all of which are considerably greater than the figures presented in mainstream media. This model can be used more effectively than current models to estimate the number of deaths during an outbreak, allowing for better planning.
Dopamine firing plays a double role in coding reward prediction errors and signaling motivation in a working memory task
Authors: Sarno Stefania , Beirán Manuel , Falcó-Roget Joan , Diaz-deLeon Gabriel , Rossi-Pool Román , Romo Ranulfo , Parga Néstor 
Published: May 2020

AbstractLittle is known about how dopamine (DA) neuron firing rates behave in cognitively demanding decision-making tasks. Here we investigated midbrain DA activity in monkeys performing a discrimination task in which the animal had to use working memory (WM) to report which of two sequentially applied vibrotactile stimuli had the higher frequency. We found that perception was altered by an internal bias, likely generated by deterioration of the representation of the first frequency during the WM period. This bias greatly controlled the DA phasic response during the two stimulation periods, confirming that DA reward prediction errors reflected subjective stimulus perception. Contrastingly, tonic dopamine activity during WM was not affected by the bias and did not encode the stored frequency. More interestingly, both WM activity and phasic responses before the second stimulus negatively correlated with reaction times of the animal after the trial start cue and thus represented motivated behavior on a trial-by-trial basis. During WM, this motivation signal underwent a ramp-like increase. At the same time, motivation reduced noise in perception and, by decreasing the effect of the bias, improved performance, especially in difficult trials. Overall, our results show that DA activity was simultaneously involved in reward prediction, motivation and WM. Also, the ramping activity during the WM period suggests a possible DA role in stabilizing sustained cortical activity, hypothetically by increasing the gain communicated to prefrontal neurons in a motivation-dependent way.
The development trends of antineoplastics targeting PD-1/PD-L1 based on scientometrics and patentometrics
Authors: Zhang Ting , Chen Juan , Lu Yan , Ouyang Zhaolian 
Published: May 2020

AbstractBackgroundThis paper aims to show the scientific research and technological development trends of antineoplastics targeting PD-1/PD-L1 based on scientometrics and patentometrics.Methodology/Principal FindingsPublications and patents related to antineoplastics targeting PD-1/PD-L1were searched and collected from the Web of Science (WoS) and the Derwent Innovation Index (DII) respectively. Totally, 11244 publications and 5501 patents were obtained. The publications were analyzed from the annual number, the top countries/regions and organizations to describe the scientific research trends in this field. The patents were analyzed from the annual number, the top priority countries and patent assignees to reveal the characteristics and status of technological development. As well as the identification of scientific research focus and technological development focus was based on the title and abstract of the publications and patents, using the freely available computer program VOSviewer for clustering and visualization analysis. The number of scientific publications and patent applications showed obvious increase of 29.84% and 33.46% in recent ten years (2009-2018), respectively. Results suggested that the most productive countries/regions publishing on antineoplastics targeting PD-1/PD-L1 were USA and China, and the top three productive organizations were all from USA, including Harvard University, VA Boston Healthcare System (VA BHS) and University Of California System. There were four scientific research focus: (1) immune escape mechanism, (2) biomarkers related to efficacy and prognosis, (3) immune-related adverse event, and (4) drug design and preparation, and five technological development focus: (1) testing methods and apparatus, (2) indications related to carcinoma, (3) biomarkers related to diagnosis and prognosis, (4) small molecule inhibitors, and (5) indications other than carcinoma.Conclusions/SignificanceThe results of this study presents an overview of the characteristics of research status and trends of antineoplastics targeting PD-1/PD-L1, which could help readers broaden innovative ideas and discover new technological opportunities, and also serve as important indicators for government policymaking.
A Susceptible-Infected-Removed (SIR) model of COVID-19 epidemic trend in Malaysia under Movement Control Order (MCO) using a data fitting approach
Authors: Arifin Wan Nor , Chan Weng Howe , Amaran Safiya , Musa Kamarul Imran 
Published: May 2020

AbstractBackgroundIn this work, we presented a Susceptible-Infected-Removed (SIR) epidemiological model of COVID-19 epidemic in Malaysia post- and pre-Movement Control Order (MCO). The proposed SIR model was fitted to confirmed COVID-19 cases from the official press statements to closely reflect the observed epidemic trend in Malaysia. The proposed model is aimed to provide an accurate predictive information for decision makers in assessing the public health and social measures related to COVID-19 epidemic.MethodsThe SIR model was fitted to the data by minimizing a weighted loss function; the sum of the residual sum of squares (RSS) of infected, removed and total cases. Optimized beta (β),), gamma (γ) parameter values) parameter values and the starting value of susceptible individuals (N) were obtained.ResultsThe SIR model post-MCO indicates the peak of infection on 10 April 2020, less than 100 active cases by 8 July 2020, less than 10 active cases by 29 August 2020, and close to zero daily new case by 22 July 2020, with a total of 6562 infected cases. In the absence of MCO, the model predicts the peak of infection on 1 May 2020, less than 100 active cases by 14 February 2021, less than 10 active cases by 26 April 2021 and close to zero daily new case by 6 October 2020, with a total of 1.6 million infected cases. Conclusion: The results suggest that the present MCO has significantly reduced the number of susceptible population and the total number of infected cases. The method to fit the SIR model used in this study was found to be accurate in reflecting the observed data. The method can be used to predict the epidemic trend of COVID-19 in other countries.
Characteristics of lymphocyte subsets and their predicting values for the severity of COVID-19 patients
Authors: Wang Jingrong , Dong Xingqi , Zhang Boting , Yang Xinping , Li Zhi , Wang Xicheng , Zuo Shuguang 
Published: May 2020

AbstractSevere COVID-19 patients showed worse clinical outcomes compared to mild and moderate patients. However, effective indicators are still lacking to predict the severity of the disease. In the present study, we retrospectively analyzed the clinical and laboratory data of 16 COVID-19 patients and found that the absolute counts of three T-cells (CD3+, CD4+, and CD8+) were significantly lower in the moderate and severe patients than those in mild patients and were significantly lower in severe patients than in moderate patients on admission. With the recovery of the COVID-19, serum levels of inflammatory biomarkers (CRP, PCT, and IL6) of moderate and severe patients gradually decreased. In contrast, the counts of lymphocytes and their subsets including CD3+, CD4+, and CD8+T cells gradually increased in severe patients, and eventually showed comparable levels with moderate patients. ROC analysis showed that the counts of CD3+, CD4+, and CD8+T-cells with AUC > 0.9 have potential values for predicting the severity of COVID-19 patients. In conclusion, the reduction of CD3+, CD4+, and CD8+T-cells is related to the severity of COVID-19 and dynamic detection of these T-lymphocyte subsets may help predict the outcome of the patients.