|drug3423||SARS-CoV-2 Specific T Cells Wiki||0.71|
|drug3420||SARS-CoV-2 IgG Antibody Testing Kit Wiki||0.71|
|D045169||Severe Acute Respiratory Syndrome NIH||0.06|
|D018352||Coronavirus Infections NIH||0.05|
There are 2 clinical trials
Infection with SARS-CoV-2 causes Corona Virus Disease (COVID-19). The most standard diagnostic method is reverse transcription-polymerase chain reaction (RT-PCR) on a nasopharyngeal and/or an oropharyngeal swab. The high occurrence of false-negative results due to the non-presence of SARS-CoV-2 in the oropharyngeal environment renders this sampling method not ideal. Therefore, a new sampling device is desirable. This proof-of-principle study investigates the possibility to train machine-learning classifiers with an electronic nose (Aeonose) to differentiate between COVID-19 positive- and negative persons based on volatile organic compounds (VOCs) analysis. Methods: between April and June 2020, participants were invited for breath analysis when a swab for RT-PCR was collected. If the RT-PCR resulted negative, presence of SARS-CoV-2 specific antibodies was checked to confirm the negative result. All participants breathed through the Aeonose for five minutes. This device contains metal-oxide sensors that change in conductivity upon reaction with VOCs in exhaled breath. These conductivity changes are input data for machine-learning and used for pattern recognition. The result is a value between -1 and +1, indicating the infection probability.
Description: Ability of the eNose to distinguish COVID-19 positive from COVID-19 negative persons based on VOC patterns.Measure: COVID 19 positive vs negative Time: 3 months
Corona Virus Disease (COVID-19), spread worldwide and has become an emergency of major international concern. In March 2020, the WHO declared the COVID-19 outbreak a global pandemic. Accurate and fast diagnosis is crucial in managing the pandemic. Current diagnostic approaches raise several difficulties: they are time-consuming, expensive, invasive, and most important lacking high sensitivity. The gold standard diagnostic test for COVID-19, reverse transcription polymerase chain reaction (RT-PCR), is highly dependent on adequate deep sampling of the swab in the naso- and oropharynx. A new diagnostic test that can correctly and rapidly identify infected patients and asymptomatic carriers is urgently required to prevent further virus transmission and thus reduce mortality rates. Aim: This proof-of-principle study aims to investigate if an electronic nose (Aeonose) can distinguish individuals with antibodies from individuals without antibodies against COVID-19 based on analysis of volatile organic compounds (VOCs). Methods: between April and July 2020, persons undergoing RT-PCR and a serology test for COVID-19 were recruited at Maastricht UMC+ for breath analysis. All participants had to breathe through the Aeonose for five consecutive minutes. The VOC pattern in their exhaled breath was then linked to the matching RT-PCR and serological test results.
Description: Ability of the electronic nose (Aeonose) to distinguish individuals with antibodies from individuals without antibodies against COVID-19 based on analysis of volatile organic compounds (VOCs).Measure: COVID-19 antibodies vs COVID-19 negative Time: 3 months
Data processed on September 26, 2020.
An HTML report was created for each of the unique drugs, MeSH, and HPO terms associated with COVID-19 clinical trials. Each report contains a list of either the drug, the MeSH terms, or the HPO terms. All of the terms in a category are displayed on the left-hand side of the report to enable easy navigation, and the reports contain a list of correlated drugs, MeSH, and HPO terms. Further, all reports contain the details of the clinical trials in which the term is referenced. Every clinical trial report shows the mapped HPO and MeSH terms, which are also hyperlinked. Related HPO terms, with their associated genes, protein mutations, and SNPs are also referenced in the report.Drug Reports MeSH Reports HPO Reports