bluuebunny/crossref_metadata_2025_split huggingface dataset:
Appealing for Efficient, Well Organized Clinical Trials on COVID-19
Authors: Zhao Yang , Wei Yongyue , Shen Sipeng , Zhang Mingzhi , Chen Feng 
Published: March 2020

ABSTRATCThe rapid emergence of clinical trials on COVID-19 stimulated a wave of discussion in scientific community. We reviewed the characteristics of interventional trials from Chinese Clinical Trial Registration (ChiCTR) and ClinicalTrials.gov. A total of 171 COVID-19-related interventional trials were identified on Feb 22nd, 2020. These trials are classified into 4 categories based on treatment modalities, including chemical drugs, biological therapies, traditional Chinese medicine treatments and other therapies. Our analysis focused on the issues of stage, design, randomization, blinding, primary endpoints definition and sample size of these trials. We found some studies with potential defects including unreasonable design, inappropriate primary endpoint definition, insufficient sample size and ethical issue. Clinical trials on COVID-19 should be designed based on scientific rules, ethics and benefits for patients.
Acute Myocardial Injury of Patients with Coronavirus Disease 2019
Authors: Xu Huayan , Hou Keke , Xu Hong , Li Zhenlin , Chen Huizhu , Zhang Na , Xu Rong , Fu Hang , Sun Ran , Wen Lingyi , Xie Linjun , Liu Hui , Zhang Kun , Selvanayagam Joseph B. , Fu Chuan , Zhao Shihua , Yang Zhigang , Yang Ming , Guo Yingkun 
Published: March 2020

AbstractBackgroundSince the outbreak of the Coronavirus Disease 2019 (COVID-19) in China, respiratory manifestations of the disease have been observed. However, as a fatal comorbidity, acute myocardial injury (AMI) in COVID-19 patients has not been previously investigated in detail. We investigated the clinical characteristics of COVID-19 patients with AMI and determined the risk factors for AMI in them.MethodsWe analyzed data from 53 consecutive laboratory-confirmed and hospitalized COVID-19 patients (28 men, 25 women; age, 19–81 years). We collected information on epidemiological and demographic characteristics, clinical features, routine laboratory tests (including cardiac injury biomarkers), echocardiography, electrocardiography, imaging findings, management methods, and clinical outcomes.ResultsCardiac complications were found in 42 of the 53 (79.25%) patients: tachycardia (n=15), electrocardiography abnormities (n=11), diastolic dysfunction (n=20), elevated myocardial enzymes (n=30), and AMI (n=6). All the six AMI patients were aged >60 years; five of them had two or more underlying comorbidities (hypertension, diabetes, cardiovascular diseases, and chronic obstructive pulmonary disease). Novel coronavirus pneumonia (NCP) severity was higher in the AMI patients than in patients with non-definite AMI (p<0.001). All the AMI patients required care in intensive care unit; of them, three died, two remain hospitalized. Multivariate analyses showed that C-reactive protein (CRP) levels, NCP severity, and underlying comorbidities were the risk factors for cardiac abnormalities in COVID-19 patients.ConclusionsCardiac complications are common in COVID-19 patients. Elevated CRP levels, underlying comorbidities, and NCP severity are the main risk factors for cardiac complications in COVID-19 patients.
Meconium androgens are correlated with ASD-related phenotypic traits in early childhood
Authors: Terloyeva Dina , Frey Alexander J. , Park Bo Y. , Kauffman Elizabeth M. , Mathew Leny , Bostwick Anna , Varner Erika L. , Lee Brian K. , Croen Lisa A. , Fallin Margaret D. , Hertz-Picciotto Irva , Newschaffer Craig J. , Lyall Kristen , Snyder Nathaniel W. 
Published: March 2020

AbstractPrenatal exposure to increased androgens has been suggested as a risk factor for autism spectrum disorder (ASD). This hypothesis has been examined by measurement of steroids in amniotic fluid and cord blood, with mixed results. To provide an orthogonal measure of fetal exposure, this study used meconium, the first stool of a newborn, to measure prenatal androgen exposure from infants in the Early Autism Risk Longitudinal Investigation (EARLI). EARLI is a familial-enriched risk cohort that enrolled pregnant mothers who already had a child with an ASD diagnosis. In the younger child, we investigated the association between meconium unconjugated (u) and total (t) concentrations of major androgens testosterone (T), dehydroepiandrosterone (DHEA) and androstenedione (A4), and ASD-related traits at 12 and 36 months of age. Autism traits were measured at 12 months with Autism Observation Scale for Infants (AOSI) and at 36 months with total score on the Social Responsiveness Scale (SRS). 137 children (61 males, 76 females) had data on both outcomes and meconium androgen measurements. Separate robust linear regressions between each of the log-transformed androgens and log-transformed AOSI and SRS scores revealed three-way interaction between sex of the child, sex of the proband, and androgen concentration. In the adjusted analyses; t-T, u-A4, and u-DHEA (P ≤ 0.01) were positively associated with AOSI scores while u-T (P=0.004) and u-DHEA (P=0.007) were positively associated with SRS total score among females with female probands. Additionally, higher concentrations of u-T (P=0.01) and t-T (P=0.01) predicted higher SRS total score in males with male probands.SignificanceUsing a prospective pregnancy cohort enriched for autism risk, we investigated prenatal androgen exposure measured from meconium as a risk factor for autism-related traits. Several meconium androgens were positively correlated with autism-related traits. In addition, we found a strong positive association between autism traits in the sub-group of individuals with an older female sibling with autism extending a previous finding based on cord blood measures in the same cohort. This study supports the utility of meconium for studies of endogenous fetal metabolism and suggests the sex of the proband should be considered as a biological variable in relevant studies.
Which assessments are used to analyze neuromuscular control by electromyography after an anterior cruciate ligament injury to determine readiness to return to sports? A systematic review
Authors: Blasimann Angela , Koenig Irene , Baert Isabel , Baur Heiner , Vissers Dirk 
Published: March 2020

AbstractBackgroundAdequate neuromuscular control of the knee could be one element to prevent secondary injuries after an anterior cruciate ligament (ACL) injury. To assess neuromuscular control in terms of time, amplitude and activity, electromyography (EMG) is used. However, it is unclear which assessments using EMG could be used for a safe return to sports (RTS). Therefore, we aimed to summarize EMG-related assessments for neuromuscular control of the knee in adult patients after an ACL injury to decide upon readiness for RTS.MethodsThis systematic review followed guidelines of Preferred Reporting of Items for Systematic Reviews and Meta-Analyses (PRISMA) and Cochrane recommendations. MEDLINE/PubMed, EMBASE, CINAHL, Cochrane Library, Physiotherapy Evidence Database (PEDro), SPORTDiscus and the Web of Science were searched from inception to March 2019 and updated in November 2020. Studies identifying electromyographic assessments for neuromuscular control during dynamic tasks in adult, physically active patients with an anterior cruciate ligament injury were eligible and qualitatively synthesized. Two independent reviewers used a modified Downs and Black checklist to assess risk of bias of included studies.ResultsFrom initially 1388 hits, 38 mainly cross-sectional, case-controlled studies were included for qualitative analysis. Most studies provided EMG outcomes of thigh muscles during jumping, running or squatting. Outcomes measures described neuromuscular control of the knee in domains of time, amplitude or activity. Risk of bias was medium to high due to an unclear description of participants and prior interventions, confounding factors and incompletely reported results.ConclusionsDespite a wide range of EMG outcome measures for neuromuscular control, none was used to decide upon return to sports in these patients. Additional studies are needed to define readiness towards RTS by assessing neuromuscular control in adult ACL patients with EMG. Further research should aim at finding reliable and valid, EMG-related variables to be used as diagnostic tool for neuromuscular control. Moreover, future studies should aim at more homogenous groups including adequately matched healthy subjects, evaluate gender separately and use sport-specific tasks.RegistrationThe protocol for this systematic review was indexed beforehand in the International Prospective Register of Systematic Reviews (PROSPERO) and registered as CRD42019122188.
Estimating the generation interval for COVID-19 based on symptom onset data
Authors: Tapiwa Ganyani , Cécile Kremer , Dongxuan Chen , Andrea Torneri , Christel Faes , Jacco Wallinga , Niel Hens 
Published: March 2020

AbstractBackgroundEstimating key infectious disease parameters from the COVID-19 outbreak is quintessential for modelling studies and guiding intervention strategies. Whereas different estimates for the incubation period distribution and the serial interval distribution have been reported, estimates of the generation interval for COVID-19 have not been provided.MethodsWe used outbreak data from clusters in Singapore and Tianjin, China to estimate the generation interval from symptom onset data while acknowledging uncertainty about the incubation period distribution and the underlying transmission network. From those estimates we obtained the proportions pre-symptomatic transmission and reproduction numbers.ResultsThe mean generation interval was 5.20 (95%CI 3.78-6.78) days for Singapore and 3.95 (95%CI 3.01-4.91) days for Tianjin, China when relying on a previously reported incubation period with mean 5.2 and SD 2.8 days. The proportion of pre-symptomatic transmission was 48% (95%CI 32-67%) for Singapore and 62% (95%CI 50-76%) for Tianjin, China. Estimates of the reproduction number based on the generation interval distribution were slightly higher than those based on the serial interval distribution.ConclusionsEstimating generation and serial interval distributions from outbreak data requires careful investigation of the underlying transmission network. Detailed contact tracing information is essential for correctly estimating these quantities.
3D Deep Neural Network Segmentation of Intracerebral Hemorrhage: Development and Validation for Clinical Trials
Authors: Sharrock Matthew F. , Mould W. Andrew , Ali Hasan , Hildreth Meghan , Awad Issam A. , Hanley Daniel F. , Muschelli John 
Published: March 2020

AbstractIntracranial hemorrhage (ICH) occurs when a blood vessel ruptures in the brain. This leads to significant morbidity and mortality, the likelihood of which is predicated on the size of the bleeding event. X-ray computed tomography (CT) scans allow clinicians and researchers to qualitatively and quantitatively diagnose hemorrhagic stroke, guide interventions and determine inclusion criteria of patients in clinical trials. There is no currently available open source, validated tool to quickly segment hemorrhage. Using an automated pipeline and 2D and 3D deep neural networks, we show that we can quickly and accurately estimate ICH volume with high agreement with time-consuming manual segmentation. The training and validation datasets include significant heterogeneity in terms of pathology, such as the presence of intraventricular (IVH) or subdural hemorrhages (SDH) as well as variable image acquisition parameters. We show that deep neural networks trained with an appropriate anatomic context in the network receptive field, can effectively perform ICH segmentation, but those without enough context will overestimate hemorrhage along the skull and around calcifications in the ventricular system. We trained with all data from a multi-center phase II study (n = 112) achieving a best mean and median Dice coefficient of 0.914 and 0.919, a volume correlation of 0.979 and an average volume difference of 1.7ml and root mean squared error of 4.7ml in 500 out-of-sample scans from the corresponding multi-center phase III study. 3D networks with appropriate anatomic context outperformed both 2D and random forest models. Our results suggest that deep neural network models, when carefully developed can be incorporated into the workflow of an ICH clinical trial series to quickly and accurately segment ICH, estimate total hemorrhage volume and minimize segmentation failures. The model, weights and scripts for deployment are located at https://github.com/msharrock/deepbleed. This is the first publicly available neural network model for segmentation of ICH, the only model evaluated with the presence of both IVH and SDH and the only model validated in the workflow of a series of clinical trials.
A mathematical model for estimating the age-specific transmissibility of a novel coronavirus
Authors: Zhao Ze-Yu , Zhu Yuan-Zhao , Xu Jing-Wen , Hu Qing-Qing , Lei Zhao , Rui Jia , Liu Xing-Chun , Wang Yao , Yang Meng , Luo Li , Yu Shan-Shan , Li Jia , Liu Ruo-Yun , Xie Fang , Su Ying-Ying , Chiang Yi-Chen , Su Yan-Hua , Zhao Ben-Hua , Chen Tian-Mu 
Published: March 2020

AbstractBackgroundA novel coronavirus named as “SARS-CoV-2” has spread widely in many countries since December 2019, especially in China. This study aimed to quantify the age-specific transmissibility by using a mathematical model.MethodsAn age-specific susceptible – exposed – symptomatic – asymptomatic – recovered – seafood market (SEIARW) model was developed based on two suspected transmission routes (from market to person and person to person). The susceptible people from Wuhan City were divided into different age groups. We used the subscript i and j to represent age group 1 to 4 (i ≠ j; 1: ≤ 14 years; 2: 15-44 years; 3: 45-64 years; 4: ≥ 65 years) and 1 to 5 (i ≠ j; 1: ≤ 5 years; 2: 6-14 years; 3: 15-24 years; 4: 25-59 years; 4: ≥ 60 years), respectively. Data of reported COVID-19 cases were collected from one published literature from 26 November to 22 December, 2019 in Wuhan City, China. The age-specific transmissibility of the virus was estimated accordingly secondary attack rate (SAR).ResultsThe age-specific SEIARW model fitted with the reported data well by dividing the population into four age groups (χ2 = 4.99 × 10−6, P > 0.999), and five age groups (χ2 = 4.85 × 10−6, P > 0.999). Based on the four-age-group SEIARW model, the highest transmissibility occurred from age group 2 to 3 (SAR23 = 17.56 per 10 million persons), followed by from age group 3 to 2 (SAR32 = 10.17 per 10 million persons). The lowest transmissibility occurred from age group 1 to 2 (SAR12 = 0.002 per 10 million persons). Based on the five-age-group SEIARW model, the highest transmissibility occurred from age group 4 to 5 (SAR45 = 12.40 per 10 million persons), followed by from age group 5 to 4 (SAR54 = 6.61 per 10 million persons). The lowest transmissibility occurred from age group 3 to 4 (SAR34 = 0.0002 per 10 million persons).ConclusionsSARS-CoV-2 has high transmissibility among adults and elder people but low transmissibility among children and young people.
Role of temperature and humidity in the modulation of the doubling time of COVID-19 cases
Authors: Oliveiros B , Caramelo L , Ferreira N C , Caramelo F 
Published: March 2020

AbstractCOVID-19 is having a great impact on public health, mortality and economy worldwide, in spite of the efforts to prevent its epidemy. The SARS-CoV-2 genome is different from that of MERS-CoV and SARS-CoV, although also expected to spread differently according to meteorological conditions. Our main goal is to investigate the role of some meteorological variables on the expansion of this outbreak.In this study, an exponential model relating the number of accumulated confirmed cases and time was considered. The rate of COVID-19 spread, using as criterion the doubling time of the number of confirmed cases, was used as dependent variable in a linear model that took four independent meteorological variables: temperature, humidity, precipitation and wind speed. Only China cases were considered, to control both cultural aspects and containment policies. Confirmed cases and the 4 meteorological variables were gathered between January 23 and March 1 (39 days) for the 31 provinces of Mainland China. Several periods of time were sampled for each province, obtaining more than one value for the rate of disease progression. Two different periods of time were tested, of 12 and 15 days, along with 3 and 5 different starting points in time, randomly chosen. The median value for each meteorological variable was computed, using the same time period; models with were selected. The rate of progression and doubling time were computed and used to fit a linear regression model. Models were evaluated using α = 0.05.Results indicate that the doubling time correlates positively with temperature and inversely with humidity, suggesting that a decrease in the rate of progression of COVID-19 with the arrival of spring and summer in the north hemisphere. A 20°C increase is expected to delay the doubling time in 1.8 days. Those variables explain 18% of the variation in disease doubling time; the remaining 82% may be related to containment measures, general health policies, population density, transportation or cultural aspects.
Emotional responses and coping strategies of nurses and nursing college students during COVID-19 outbreak
Authors: Huang Long , Xu Fuming , Liu Hairong 
Published: March 2020

AbstractBackgroundAffected by a Corona Virus Disease 2019 (COVID-19) outbreak, Since December 2019, there have been more than 76,000 cases of COVID-19 in China, causing more than 3,000 medical staff infections. Due to COVID-19 spreads quickly, is highly contagious, and can be fatal in severe cases, and there are no specific medicines, it poses a huge threat to the life and health of nurses and has a large impact on their emotional responses and coping strategies.MethodsThis study conducted an online questionnaire survey from February 1 to 9, 2020 to investigate the current state of emotional responses and coping strategies of nurses and college nursing students in Anhui Province. This study used a modified Brief COPE (Carver, 1997) and a emotional responses scale.ResultsThe results found that women showed more severe anxiety and fear than men. Participants from cities showed more anxiety and fear than participants from rural, but rural participants showed more sadness than urban participants. The closer COVID-19 is to the participants, the stronger the anxiety and anger. Compared with Nursing college students, nurses have stronger emotional responses and are more willing to use Problem-focused coping. People may have a cycle of “the more fear, the more problem-focused coping”. And people may “The more angry, the more emotion-focused coping”, “the more problem-focused coping, the more anxious, the more angry, the more sadness”.ConclusionCOVID-19 is a pressure source with great influence, both for individuals and for the social public groups. Different individuals and groups may experience different levels of psychological crisis, and those nurses at the core of the incident are affected. Hospitals should focus on providing psychological support to nurses and providing timely psychological assistance and training in coping strategies.Improving nurses’ ability to regulate emotions and effective coping strategies, providing a strong guarantee for resolutely winning the battle against epidemic prevention and control.
COVID-19 early warning score: a multi-parameter screening tool to identify highly suspected patients
Authors: Song Cong-Ying , Xu Jia , He Jian-Qin , Lu Yuan-Qiang 
Published: March 2020

ABSTRACTBACKGROUNDCorona Virus Disease 2019 (COVID-19) is spreading worldwide. Effective screening for patients is important to limit the epidemic. However, some defects make the currently applied diagnosis methods are still not very ideal for early warning of patients. We aimed to develop a diagnostic model that allows for the quick screening of highly suspected patients using easy-to-get variables.METHODSA total of 1,311 patients receiving severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleicacid detection were included, whom with a positive result were classified into COVID-19 group. Multivariate logistic regression analyses were performed to construct the diagnostic model. Receiver operating characteristic (ROC) curve analysis were used for model validation.RESULTSAfter analysis, signs of pneumonia on CT, history of close contact, fever, neutrophil-to-lymphocyte ratio (NLR), Tmax and sex were included in the diagnostic model. Age and meaningful respiratory symptoms were enrolled into COVID-19 early warning score (COVID-19 EWS). The areas under the ROC curve (AUROC) indicated that both of the diagnostic model (training dataset 0.956 [95%CI 0.935-0.977, P < 0.001]; validation dataset 0.960 [95%CI 0.919-1.0, P < 0.001]) and COVID-19 EWS (training dataset 0.956 [95%CI 0.934-0.978, P < 0.001]; validate dataset 0.966 [95%CI 0.929-1, P < 0.001]) had good discrimination capacity. In addition, we also obtained the cut-off values of disease severity predictors, such as CT score, CD8+ T cell count, CD4+ T cell count, and so on.CONCLUSIONSThe new developed COVID-19 EWS was a considerable tool for early and relatively accurately warning of SARS-CoV-2 infected patients.
Impact of direct-to-consumer genetic testing on Australian clinical genetics services
Authors: Millward Michael , Tiller Jane , Bogwitz Michael , Kincaid Helen , Taylor Shelby , Trainer Alison H , Lacaze Paul 
Published: March 2020

AbstractPurposeThe increasing popularity of direct-to-consumer genetic testing (DTCGT) is thought to be creating a burden on clinical genetic health services worldwide. However, no studies have collected recent evidence regarding the extent of this impact in Australia.MethodsWe administered an online survey to Australian clinical genetics services, asking questions related to DTCGT-related referrals received and outcomes over the past 10 years.ResultsEleven publicly-funded clinical genetics services completed the survey, reporting over 100 DTCGT-related referrals. Most referrals (83%) were made by general practitioners seeking interpretation of DTCGT results. More than 30% of referrals related to imputed genetic risk estimates generated from third-party web-based software tools. Services reported low validation rates for DTCGT results (<10%). Procedures for managing DTCGT referrals and granting appointments were variable between services, with most services (8/11) lacking specific procedures.ConclusionOur study helps quantify the impact of DTCGT on clinical genetics services, and highlights the impact of imputed genetic risk estimates generated from third-party software.