bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characteristics of COVID-19 Clinical Trials in India Based on the Registration Data on CTRI (Clinical Trials Registry- India): a cross-sectional analysis
Authors: Sathiyarajeswaran P , Shree Devi MS , Kanakavalli K , Vinod NP 
Published: October 2020

AbstractObjectivesThe 2019 pandemic of coronavirus disease (COVID-19) has prompted several efforts to find safe and effective drugs, but little is understood as to where early efforts were centered. Several clinical trials, both Allopathy and AYUSH medicines have been registered in the Clinical Trial Registry of India (CTRI). We aimed to characterize and extract relevant data registered under CTRI for COVID-19.Materials and MethodsA cross-sectional analysis was performed of clinical trials for the treatment of COVID-19 that were registered in the Clinical Trial Registry of India (CTRI) from 1st March 2020 to 22nd June 2020. Relevant trial records were downloaded, deduplicated, and independently analyzed by three reviewers.Main outcomesTrial intervention, design, sponsorship, phase of the trial, and indicated outcomes.Results233 COVID-19 clinical trials, was registered from India in CTRI. Out of these, 146 were Interventional trials, 84 Observational trials, and three Post-marketing surveillance. Questionnaire and survey-based intervention occupy a significant portion. Randomized control trials are large in number 37.8% than non-randomized. 20% of the trials were recruiting patients, and the Research institution (34%) sponsored more than half of the trials. Global trials are minimal, occupying 3% of total trials and Indian trials were 97%. In most of the trials, the interventional agent is either multiple drug combinations or compound drug formulations compared to single drug administration. Among the trials, 46 Allopathic interventions, 41 Ayurveda interventions, 14 Homeopathy interventions, one in Unani, and 2 in yoga and Naturopathy.ConclusionThis study will provide a background of COVID-19 clinical trials registered in CTRI and provide specific issues observed related to clinical trial designs, which offer information to perform clinical trials on COVID-19
Reverse Transcription-Loop-Mediated Isothermal Amplification (RT-LAMP) is an effective alternative for SARS-CoV-2 molecular detection in middle-income countries
Authors: Escalante-Maldonado Oscar , Vidal-Anzardo Margot , Donaires Fernando , Solis-Sanchez Gilmer , Gallesi Italo , Pampa-Espinoza Luis , Huaringa Maribel , Serrano Nancy Rojas , García Coralith , Angles-Yanqui Eddie , Gavilán Ronnie Gustavo , Durães-Carvalho Ricardo , Cabezas Cesar , Simas Paulo Vitor Marques 
Published: October 2020

ABSTRACTMolecular diagnosis of SARS-CoV-2 in developing countries is still a big challenge. The reference standard, RT-qPCR, recommended by WHO, is not widely available, difficulting early identification of cases. Furthermore, the transport logistic between the sample collection point and the laboratory facilities can alter the samples, producing false negative results. RT-LAMP is a cheaper, simpler molecular technique that can be an interesting alternative to be offered in hospital laboratories. We present the evaluation of a RT-LAMP for diagnosis of SARS-CoV-2 in two steps: the laboratory standardization and the clinical validation, comparing it with the standard RT-qPCR. In the standardization phase, limit of detection and robustness values were obtained using RNA from a Peruvian SARS-CoV-2 strain. It presented 100% agreement between triplicates (RT-LAMP agreement with all RT-qPCR reactions that presented Ct ≤ 30) and robustness (RT-LAMP successful reactions with 80% reaction volume and 50% primer concentration). 384 nasal and pharyngeal swabs collected from symptomatic patients and stored in the INS biobank were tested and we obtained 98.75%, 87.41%, 97.65% and 92.96% for specificity, sensitivity, positive predictive value and negative predictive values respectively. Then, 383 samples from symptomatic patients with less than 15 days of disease, were tested both with the RT-LAMP and with the RT-qPCR, obtaining e 98.8%, 88.1%, 97.7% y 93.3% of specificity, sensitivity, positive predictive value and negative predictive values respectively. The laboratory standardization and the clinical validation presented the same value by Kappa-Cohen index (0.88) indicating an almost perfect agreement between RT-LAMP and RT-qPCR for molecular detection of SARS-CoV-2. We conclude that this RT-LAMP protocol presented high diagnostic performance values and can be an effective alternative for COVID-19 molecular diagnosis in hospitals, contributing to early diagnosis and reducing the spread of virus transmission in the Peruvian population.
Long term impact of coal mine fire smoke on lung mechanics in exposed adults
Authors: Holt Nicolette R , Gao Caroline X. , Borg Brigitte M , Brown David , Broder Jonathan C , Ikin Jillian , Makar Annie , McCrabb Thomas , Nilsen Kris , Thompson Bruce R , Abramson Michael J. 
Published: October 2020

AbstractIn 2014, a six-week long fire at the Hazelwood open cut coal mine exposed residents in the adjacent town of Morwell to high concentrations of fine particulate matter with an aerodynamic diameter <2.5μm (PM2.5). The long-term health consequences are being evaluated as part of the Hazelwood Health Study (HHS).Approximately 3.5 to 4 years after the mine fire, adults from Morwell (n=346) and the comparison town Sale (n=173) participated in the longitudinal Respiratory Stream of the HHS. Individual fire-related PM2.5exposure was retrospectively modelled. Lung mechanics were assessed using the forced oscillation technique (FOT), which utilises pressure waves to measure respiratory system resistance (Rrs) and reactance (Xrs). Multivariate linear regression was used to evaluate associations between PM2.5and transformed Rrs5, area under the reactance curve (AX5) and Xrs5 controlling for key confounding factors.There were clear dose-response relationships between increasing mine fire PM2.5and worsening lung mechanics, including a reduction in post-bronchodilator Xrs5 and an increase in AX5. A 10 μg/m3increase in mine fire related PM2.5was associated with a 0.015 (95%CI: 0.004, 0.027) reduction in exponential(Xrs5) post bronchodilator, which was comparable to 4.7 years of aging. Similarly, the effect of exposure was associated with a 0.072 (0.005, 0.138) increase in natural log(AX5) post-bronchodilator, equivalent to 3.9 years of aging.This is the first study using FOT in adults evaluating long term respiratory outcomes after a medium-term ambient PM2.5exposure to coal mine fire smoke. These results should inform public health policies and planning for future events.
Chronic Obstructive Pulmonary Disease in adults exposed to fine particles from a coal mine fire
Authors: Prasad Shivonne , Gao Caroline , Borg Brigitte , Broder Jonathan , Brown David , Ikin Jillian , Makar Annie , McCrabb Tom , Hoy Ryan , Thompson Bruce , Abramson Michael J. 
Published: October 2020

ABSTRACTIntroductionIn 2014 the Hazelwood open cut coal mine burned for six weeks, exposing nearby residents to fine particulate matter (PM2.5). The long-term health consequences are being evaluated as part of the Hazelwood Health Study (HHS). These analyses explore the association between PM2.5 and chronic obstructive pulmonary disease (COPD).MethodsA sample of 346 exposed, and 173 unexposed, adults participated in the longitudinal Respiratory Stream of the HHS. Participants underwent spirometry and gas transfer measurements and answered validated respiratory questionnaires 3.5-4 years after the fire. Individual level mine fire-related PM2.5 exposure was modelled. Multivariate linear regression and logistic models were fitted to analyse associations between mean and peak PM2.5 exposure and clinical outcomes, stratified by smoking status.ResultsA 10 μg/m3 increase in mean PM2.5 exposure was associated with a 69% (95%CI: 11% to 158%) increase in odds of spirometry consistent with COPD amongst non-smokers and increased odds of chest tightness (odds ratio; OR 1.30, 95%CI 1.03 to 1.64) and chronic cough (OR 1.24, 95%CI 1.02 to 1.51) in the previous 12 months in all participants. For current smokers, increments in mean PM2.5 exposure were associated with higher odds of chronic cough in the preceding 12 months (OR 2.13, 95%CI 1.24 to 3.65).DiscussionAlmost four years after a six-week period of coal fire PM2.5 exposure, we identified a dose-response association between exposure and COPD in non-smokers. With climate change a likely contributor to increased risk of landscape fires, the findings will inform policy decisions during future sustained smoke events.KEY MESSAGESWhat is the key question?Are there long-term impacts of a six-week mine fire event generating PM2.5 on COPD and related respiratory symptoms in adults?What is the bottom line?Almost 4 years after the mine fire, each 10 µg/m3 increase in PM2.5 exposure was associated with a 69% increase in odds of spirometry consistent with COPD amongst non-smokers, and a 30% increase in odds of chest tightness and 24% increase in odds of chronic cough amongst all participants. Amongst smokers, each 10 µg/m3 increase in PM2.5 was associated with a 113% increase in odds of chronic cough.Why read on?With the recent megafires in Australia and the United States exposing communities to smoke for weeks to months, evidence of the long-term health impacts of similar duration PM2.5 generating pollution events are needed to inform the public health response.
Quantification of different iron forms in the aceruloplasminemia brain to explore iron-related neurodegeneration
Authors: Vroegindeweij Lena H.P. , Bossoni Lucia , Boon Agnita J.W. , Wilson J.H. Paul , Bulk Marjolein , Huber Martina , Labra-Muñoz Jacqueline , Webb Andrew , van der Weerd Louise , Langendonk Janneke G. 
Published: October 2020

AbstractIntroductionAceruloplasminemia is an ultra-rare neurodegenerative disorder associated with massive brain iron accumulation. It is unknown which molecular forms of iron accumulate in the brain of patients with aceruloplasminemia. As the disease is associated with at least a fivefold increase in brain iron concentration compared to the healthy brain, it offers a unique model to study the role of iron in neurodegeneration and the molecular basis of iron-sensitive MRI contrast.MethodsThe iron-sensitive MRI metrics inhomogeneous transverse relaxation rate (R2*) and magnetic susceptibility obtained at 7T were combined with Electron Paramagnetic Resonance (EPR) and Superconducting Quantum Interference Device (SQUID) magnetometry to specify and quantify the different iron forms per gram wet-weight in a post-mortem aceruloplasminemia brain, with focus on the basal ganglia, thalamus, red nucleus, dentate nucleus, superior-and middle temporal gyrus and white matter. MRI, EPR and SQUID results that had been previously obtained from the temporal cortex of healthy controls were included for comparison.ResultsThe brain iron pool in aceruloplasminemia consisted of EPR-detectable Fe3+ ions, magnetic Fe3+ embedded in the core of ferritin and hemosiderin (ferrihydrite-iron), and magnetic Fe3+ embedded in oxidized magnetite/maghemite minerals (maghemite-iron). Of all the studied iron pools, above 90% was made of ferrihydrite-iron, of which concentrations up to 1065 µg/g were detected in the red nucleus. Although deep gray matter structures in the aceruloplasminemia brain were three times richer in ferrihydrite-iron than the temporal cortex, ferrihydrite-iron in the temporal cortex of the patient with aceruloplasminemia was already six times more abundant compared to the healthy situation (162 µg/g vs. 27 µg/g). The concentration of Fe3+ ions and maghemite-iron were 1.7 times higher in the temporal cortex in aceruloplasminemia than in the control subjects. Of the two quantitative MRI metrics, R2* was the most illustrative of the pattern of iron accumulation and returned relaxation rates up to 0.49 ms-1, which were primarily driven by the abundance of ferrihydrite-iron. Maghemite-iron did not follow the spatial distribution of ferrihydrite-iron and did not significantly contribute to MRI contrast in most of the studied regions.ConclusionsEven in extremely iron-loaded cases, iron-related neurodegeneration remains primarily associated with an increase in ferrihydrite-iron, with ferrihydrite-iron being the major determinant of iron-sensitive MRI contrast.
Linking microstructural integrity and motor cortex excitability in multiple sclerosis
Authors: Radetz Angela , Mladenova Kalina , Ciolac Dumitru , Gonzalez-Escamilla Gabriel , Fleischer Vinzenz , Ellwardt Erik , Krämer Julia , Bittner Stefan , Meuth Sven G. , Muthuraman Muthuraman , Groppa Sergiu 
Published: October 2020

AbstractMotor skills are frequently impaired in multiple sclerosis (MS) patients following grey (GM) and white matter (WM) damage with cortical excitability abnormalities. We performed advanced diffusion imaging for neurite orientation dispersion and density modeling and diffusion tensor imaging within the motor system of 50 MS patients and 49 age-matched healthy controls. To assess excitability, we determined resting motor thresholds using non-invasive transcranial magnetic stimulation. A hierarchical regression model revealed that lower neurite density index (NDI), suggestive for axonal loss in the GM, predicted higher motor thresholds, i.e. reduced excitability in MS patients. Furthermore, lower NDI was indicative of decreased cognitive-motor performance. Interconnected motor WM tracts of patients were characterized by overlapping clusters of lowered fractional anisotropy and NDI, with NDI exclusively capturing a higher amount of abnormally appearing voxels. Our work outlines the potential of microstructure imaging using advanced biophysical models to forecast neurodegeneration and excitability alterations in neuroinflammation.
Impact of SARS-CoV-2 on Seasonal Respiratory Viruses: A Tale of Two Large Metropolitan Centers in the United States
Authors: Sherman Amy C. , Babiker Ahmed , Sieben Andrew J. , Pyden Alexander , Steinberg James , Kraft Colleen S. , Koelle Katia , Kanjilal Sanjat 
Published: October 2020

AbstractTo assess the impact of the SARS-CoV-2 pandemic on seasonal respiratory viruses, absolute case counts and viral reproductive rates from 2019-2020 were compared against previous seasons. Our findings suggest that the public health measures implemented to reduce SARS-CoV-2 transmission significantly reduced the transmission of other respiratory viruses.
Effective Deep Learning Approaches for Predicting COVID-19 Outcomes from Chest Computed Tomography Volumes
Authors: Trivedi Anusua , Ortiz Anthony , Desbiens Jocelyn , Robinson Caleb , Blazes Marian , Gupta Sunil , Dodhia Rahul , Bhatraju Pavan , Liles W. Conrad , Lee Aaron , Ferres Juan M. Lavista 
Published: October 2020

AbstractThe rapid evolution of the novel coronavirus SARS-CoV-2 pandemic has resulted in an urgent need for effective clinical tools to reduce transmission and manage severe illness. Numerous teams are quickly developing artificial intelligence approaches to these problems, including using deep learning to predict COVID-19 diagnosis and prognosis from computed tomography (CT) imaging data. In this work, we assess the value of aggregated chest CT data for COVID-19 prognosis compared to clinical metadata alone. We develop a novel patient-level algorithm to aggregate the chest CT volume into a 2D representation that can be easily integrated with clinical metadata to distinguish Novel Coronavirus Pneumonia (COVID-19+) from other cases of viral pneumonia and normal healthy chest CT volumes with state-of-the-art performance. Furthermore, we present a multitask model for joint segmentation of different classes of pulmonary lesions present in COVID-19 infected lungs that can outperform individual segmentation models for each task. We directly compare this multitask segmentation approach to combining feature-agnostic volumetric CT classification feature maps with clinical metadata for predicting mortality. These approaches enable the automated extraction of clinically relevant features from chest CT volumes for risk stratification of COVID-19+ patients.
Lessons from applied large-scale pooling of 133,816 SARS-CoV-2 RT-PCR tests
Authors: Barak Netta , Ben-Ami Roni , Sido Tal , Perri Amir , Shtoyer Aviad , Rivkin Mila , Licht Tamar , Peretz Ayelet , Magenheim Judith , Fogel Irit , Livneh Ayala , Daitch Yutti , Oiknine-Djian Esther , Benedek Gil , Dor Yuval , Wolf Dana G. , Yassour Moran ,   The Hebrew University-Hadassah COVID-19 diagnosis team
Published: October 2020

AbstractPooling multiple swab samples prior to RNA extraction and RT-PCR analysis was proposed as a strategy to reduce costs and increase throughput of SARS-CoV-2 tests. However, reports on practical large-scale group testing for SARS-CoV-2 have been scant. Key open questions concern reduced sensitivity due to sample dilution; the rate of false positives; the actual efficiency (number of tests saved by pooling) and the impact of infection rate in the population on assay performance. Here we report analysis of 133,816 samples collected at April-September 2020, tested by pooling for the presence of SARS-CoV-2. We spared 76% of RNA extraction and RT-PCR tests, despite the reality of frequently changing prevalence rate (0.5%-6%). Surprisingly, we observed pooling efficiency and sensitivity that exceed theoretical predictions, which resulted from non-random distribution of positive samples in pools. Overall, the findings strongly support the use of pooling for efficient large high throughput SARS-CoV-2 testing.
Different mutations in SARS-CoV-2 associate with severe and mild outcome
Authors: Nagy Ádám , Pongor Sándor , Győrffy Balázs 
Published: October 2020

ABSTRACTIntroductionGenomic alterations in a viral genome can lead to either better or worse outcome and identifying these mutations is of utmost importance. Here, we correlated protein-level mutations in the SARS-CoV-2 virus to clinical outcome.MethodsMutations in viral sequences from the GISAID virus repository were evaluated by using “hCoV-19/Wuhan/WIV04/2019” as the reference. Patient outcomes were classified as mild disease, hospitalization and severe disease (death or documented treatment in an intensive-care unit). Chi-square test was applied to examine the association between each mutation and patient outcome. False discovery rate was computed to correct for multiple hypothesis testing and results passing a FDR cutoff of 5% were accepted as significant.ResultMutations were mapped to amino acid changes for 2,120 non-silent mutations. Mutations correlated to mild outcome were located in the ORF8, NSP6, ORF3a, NSP4, and in the nucleocapsid phosphoprotein N. Mutations associated with inferior outcome were located in the surface (S) glycoprotein, in the RNA dependent RNA polymerase, in the 3’-to5’ exonuclease, in ORF3a, NSP2 and N. Mutations leading to severe outcome with low prevalence were found in the surface (S) glycoprotein and in NSP7. Five out of 17 of the most significant mutations mapped onto a 10 amino acid long phosphorylated stretch of N indicating that in spite of obvious sampling restrictions the approach can find functionally relevant sites in the viral genome.ConclusionsWe demonstrate that mutations in the viral genes may have a direct correlation to clinical outcome. Our results help to quickly identify SARS-CoV-2 infections harboring mutations related to severe outcome.
Impact of the COVID-19 pandemic on Suicide and Self Harm among Patients Presenting to the Emergency Department of a Teaching Hospital in Nepal
Authors: Shrestha Roshana , Siwakoti Shisir , Singh Saumya , Shrestha Anmol Purna 
Published: October 2020

ABSTRACTBackgroundThe COVID-19 pandemic is a global challenge that is not just limited to the physical consequences but also a significant degree of a mental health crisis. Self-harm (SH) and suicide are its extreme effects. The aim of this study was to provide an overview of the impact of the COVID-19 pandemic on the occurrence and clinical profile of suicide and SH in our ED.MethodsThis is a cross-sectional observational study conducted in the ED of a tertiary care center. Records of all fatal and nonfatal SH patients presenting to the ED during the lockdown period (March 24-June 23, 2020; Period1), matching periods in the previous year (March 24-June 23,2019; Period 2) and 3 months period prior (December 24 2019-March 23, 2020; Period 3) was included by searching the electronic medical record (EMR) system. The prevalence and the clinical profile of the patients were compared between these three periods.ResultsA total of 125 (periods 1=55, 2=38, and 3=32) suicide and SH cases were analyzed. The cases of suicide/SH had increased by 44% and 71.9% during the lockdown period in comparison to the period 2 and 3. Organophosphate poisoning was the most common mode. Females were predominant in all three periods with a mean age of 32 (95%CI: 29.3-34.7). There was a significant delay in arrival of the patients in period 1 (p-value=0.045) with increased hospital admission (p-value =0.009) and in-hospital mortality (18.2% vs 2.6 % and 3.1%) (p-value=.001).ConclusionWe found an increase in patients presenting with suicide and SH in our ED during the pandemic which is likely to reflect an increased prevalence of mental illness in the community. We hope that the result will prime all mental health care stakeholders to initiate mental health screening and intervention for the vulnerable population during this period of crisis.
Concurrent comorbidities substantially alter long-term health behaviours and outcomes of headache patients
Authors: Nash Anthony , Goodday Sarah , Liu Qiang , Fuller Alice , Bankhead Clare , Webber Caleb , Nevado-Holgado Alejo J. , Cader M. Zameel 
Published: October 2020

AbstractObjectivesTo investigate factors affecting the long-term health behaviours and outcomes of headache patients and to design a risk-stratification tool.MethodsA population based observational-longitudinal cohort study using primary care electronic healthcare records from the UK Clinical Practice Research Datalink. 550,103 participants with a headache or migraine diagnosis of which 170,336 patients were identified as having recurrent headache-related events. Univariate and multivariable survival analysis was performed to determine factors influencing remission and a neural network classifier was developed.ResultsThere were almost twice as many female patients (352,330) as males (197,802). The median age at which a patient first saw their GP in males was 38 years, and in females was 37 years. Whilst age, gender and social deprivation significantly influenced the likelihood of seeing a GP, these factors had little effect on likelihood of remission from a period of recurrent headache-related events. In contrast, a comorbidity during the recurrent headache period reduced the risk of remission and increased median survival time from approximately 400-days up 1600. Increasing numbers of comorbidities progressively reduced the hazard risks for remission. The prediction models on remission within two and five years, demonstrated high precision and recall, with an F1 score of 0.795 and 0.887, respectively.InterpretationHeadache patients who suffer comorbidities have a substantively reduced likelihood of remission, highlighting an opportunity to considerably improve health outcomes in recurrent headache patients through addressing multi-morbidity more effectively. The prediction model could be used to help stratify patients most at risk of poor long-term outcomes.