34 Polk COVID-19 and Flu Response Clinical Trial
Ontology highlight
ABSTRACT:
SUBMITTER: Banerjee P
PROVIDER: S-EPMC8335489 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Clinical Trial of COVID-19 Convalescent Plasma in Outpatients (C3PO)
| PRJNA791978 | ENA
Project description:Clinical Trial of COVID-19 Convalescent Plasma in Outpatients (C3PO)
| PRJNA791979 | ENA
Project description:ObjectiveClinical trials are an essential part of the effort to find safe and effective prevention and treatment for COVID-19. Given the rapid growth of COVID-19 clinical trials, there is an urgent need for a better clinical trial information retrieval tool that supports searching by specifying criteria, including both eligibility criteria and structured trial information.Materials and methodsWe built a linked graph for registered COVID-19 clinical trials: the COVID-19 Trial Graph, to facilitate retrieval of clinical trials. Natural language processing tools were leveraged to extract and normalize the clinical trial information from both their eligibility criteria free texts and structured information from ClinicalTrials.gov. We linked the extracted data using the COVID-19 Trial Graph and imported it to a graph database, which supports both querying and visualization. We evaluated trial graph using case queries and graph embedding.ResultsThe graph currently (as of October 5, 2020) contains 3392 registered COVID-19 clinical trials, with 17 480 nodes and 65 236 relationships. Manual evaluation of case queries found high precision and recall scores on retrieving relevant clinical trials searching from both eligibility criteria and trial-structured information. We observed clustering in clinical trials via graph embedding, which also showed superiority over the baseline (0.870 vs 0.820) in evaluating whether a trial can complete its recruitment successfully.ConclusionsThe COVID-19 Trial Graph is a novel representation of clinical trials that allows diverse search queries and provides a graph-based visualization of COVID-19 clinical trials. High-dimensional vectors mapped by graph embedding for clinical trials would be potentially beneficial for many downstream applications, such as trial end recruitment status prediction and trial similarity comparison. Our methodology also is generalizable to other clinical trials.
| S-EPMC8135317 | biostudies-literature
Project description:Mesenchymal stromal cells are a potential therapeutic for Acute Respiratory Distress Syndrome due to COVID-19, with pleiotropic immunomodulatory and reparative properties.This study investigated the safety and efficacy of ORBCEL-C (CD362 enriched umbilical cord-derived Mesenchymal Stromal Cells) in this patient population.
2023-06-20 | GSE231660 | GEO
Project description:While incomplete non-medical data has been integrated into prediction models for epidemics, the accuracy and the generalizability of the data are difficult to guarantee. To comprehensively evaluate the ability and applicability of using social media data to predict the development of COVID-19, a new confirmed case prediction algorithm improving the Google Flu Trends algorithm is established, called Weibo COVID-19 Trends (WCT), based on the post dataset generated by all users in Wuhan on Sina Weibo. A genetic algorithm is designed to select the keyword set for filtering COVID-19 related posts. WCT can constantly outperform the highest average test score in the training set between daily new confirmed case counts and the prediction results. It remains to produce the best prediction results among other algorithms when the number of forecast days increases from one to eight days with the highest correlation score from 0.98 (P < 0.01) to 0.86 (P < 0.01) during all analysis period. Additionally, WCT effectively improves the Google Flu Trends algorithm's shortcoming of overestimating the epidemic peak value. This study offers a highly adaptive approach for feature engineering of third-party data in epidemic prediction, providing useful insights for the prediction of newly emerging infectious diseases at an early stage.
| S-EPMC8280378 | biostudies-literature
Project description: Not available
| S-BSST563 | biostudies-other
Project description:Background: Never before have clinical trials drawn as much public attention as those testing interventions for COVID-19. We aimed to describe the worldwide COVID-19 clinical research response and its evolution over the first 100 days of the pandemic. Methods: Descriptive analysis of planned, ongoing or completed trials by April 9, 2020 testing any intervention to treat or prevent COVID-19, systematically identified in trial registries, preprint servers, and literature databases. A survey was conducted of all trials to assess their recruitment status up to July 6, 2020. Results: Most of the 689 trials (overall target sample size 396,366) were small (median sample size 120; interquartile range [IQR] 60-300) but randomized (75.8%; n=522) and were often conducted in China (51.1%; n=352) or the USA (11%; n=76). 525 trials (76.2%) planned to include 155,571 hospitalized patients, and 25 (3.6%) planned to include 96,821 health-care workers. Treatments were evaluated in 607 trials (88.1%), frequently antivirals (n=144) or antimalarials (n=112); 78 trials (11.3%) focused on prevention, including 14 vaccine trials. No trial investigated social distancing. Interventions tested in 11 trials with >5,000 participants were also tested in 169 smaller trials (median sample size 273; IQR 90-700). Hydroxychloroquine alone was investigated in 110 trials. While 414 trials (60.0%) expected completion in 2020, only 35 trials (4.1%; 3,071 participants) were completed by July 6. Of 112 trials with detailed recruitment information, 55 had recruited <20% of the targeted sample; 27 between 20-50%; and 30 over 50% (median 14.8% [IQR 2.0-62.0%]). Conclusions: The size and speed of the COVID-19 clinical trials agenda is unprecedented. However, most trials were small investigating a small fraction of treatment options. The feasibility of this research agenda is questionable, and many trials may end in futility, wasting research resources. Much better coordination is needed to respond to global health threats.
| S-EPMC7539080 | biostudies-literature
Project description:A randomised control trial was done to assess clinical and immunological benefits of passive immunization using convalescent plasma therapy (CPT), compared with standard of care, in severe COVID-19 patients presenting with acute respiratory distress syndrome (ARDS). Plasma abundance of a large panel of cytokines was quantitated before and after intervention to assess the effect of CPT on the systemic hyper-inflammation encountered in these patients. Transfused convalescent plasma was characterized in terms of its neutralizing antibody content as well as proteome. While across all age-groups clinical outcomes were not significantly different, significant immediate mitigation of hypoxia, reduction in hospital stay as well as significant survival benefit were registered in severe COVID-19 patients with ARDS aged less than 67 years receiving CPT. In addition to its neutralizing antibody content, a significant effect of the anti-inflammatory proteome of convalescent plasma on attenuation of systemic cytokine deluge, contributed to the clinical benefits of CPT.
2022-02-17 | PXD025453 | Pride
Project description:Hundreds of interventional clinical trials have been launched in the United States to identify effective treatment strategies for combating the coronavirus disease 2019 (COVID-19) pandemic. However, to date, only a small fraction of these trials have completed enrollment, delaying the scientific investigation of COVID-19 and its treatment options. This study presents novel metrics to examine the geographic alignment between COVID-19 hotspots and interventional clinical trial sites and evaluate trial access over time during the evolving pandemic. Using temporal COVID-19 case data from USAFacts.org and trial data from ClinicalTrials.gov, U.S. counties were categorized based on their numbers of cases and trials. Our analysis suggests that alignment and access have worsened as the pandemic shifted over time. We recommend strategies and metrics to evaluate the alignment between cases and trials. Future studies are warranted to investigate the impact of the misalignment of cases and clinical trial sites on clinical trial recruitment.
| S-EPMC8385938 | biostudies-literature