June 19, 2020 | Several groups have published research highlighting the neurological impacts of COVID-19, and other groups are looking into how well patients may self-assess or even self-sample for rapid diagnosis. Plus more from this week’s COVID-19 news and research in the diagnostics industry.
Cleveland Clinic researchers have developed a prediction model for healthcare providers to forecast an individual patient's likelihood of testing positive for COVID-19 as well as their outcomes from the disease. According a new study published in CHEST, the risk prediction model (called a nomogram) shows the relevance of age, race, gender, socioeconomic status, vaccination history and current medications in COVID-19 risk. The risk calculator is a new tool for healthcare providers to aid them in predicting patient risk and tailoring decision-making about care. DOI: 10.1016/j.chest.2020.05.580
Several groups of researchers are highlighting the neurological impacts and COVID-19 and alerting clinicians that neurological symptoms could be among the earliest. One group from Johns Hopkins and University of Washington (published in the Journal of Alzheimer’s Disease) outlines a three-stage "NeuroCovid" classification scheme. Stage 1 includes short term loss of taste or smell; Stage 2 results from a cytokine storm that could cause blood clots and strokes; Stage 3 is damage to the blood brain barrier resulting in seizures, coma, and more. DOI: 10.3233/JAD-200581. Separately, in Annals of Neurology, a review of the literature by Northwestern University researchers asserts that COVID-19 poses a global threat to the entire nervous system. DOI: 10.1002/ana.25807 And French researchers published retrospective MRI findings in Radiology outlining eight distinctive neuroradiologic patterns (excluding ischemic infarcts) in patients with severe COVID-19 infection with abnormal brain MRIs. DOI: 10.1148/radiol.2020202222
Several recent studies are looking at tools to help patients self-assess or even self-sample for more efficient COVID-19 diagnosis. A small study conducted by researchers at the Stanford University School of Medicine shows test samples collected by people who swabbed their own nasal passages yielded results for the COVID-19 virus that were as accurate as samples collected by a health care worker. The study was published as a research letter in JAMA Network. The 30 study participants, who previously had tested positive for COVID-19, collected their own samples at a drive-through testing site after watching a short video animation and reading a one-page document instructing them how to perform the swab. The nasal swab for the study is more comfortable to use than the long nasopharyngeal swab currently used to collect samples from the back of the nasal cavity. The only discordant result was a participant whose self-collected nasal specimen tested positive, whereas both of their physician-collected specimens tested negative. DOI: 10.1001/jamanetworkopen.2020.12005.
A University of California web-based COVID-19 patient self-assessment tool was used by more than 275,000 people. Users reported symptoms potentially attributable to COVID-19 69.6% of the time, though only 20% of those reporting COVID-19 symptoms were impacted severely enough to require immediate medical attention. The research was published in the Journal of General Internal Medicine. The tool, which is freely available in English and Spanish, was developed in partnership with AltaMed Health Services, the nation's largest independent federally qualified community health center. DOI: 10.1007/s11606-020-05893-0
The University of Rochester has made its self-screening chatbot tool available free as open source software. University of Rochester Medical Center (URMC) employees have been using the tool since April 9, to self-check for COVID-19 symptoms before they report to work. The University's chatbot technology also is the foundation of a "ROC COVID" community screening tool recently launched in thirteen counties in the Finger Lakes, N.Y. region to track potential new outbreaks of COVID-19 cases. University of Rochester's open source code includes a simple user interface accessible from an employee's smartphone, tablet, PC or other device, seven avatars representing a range of friendly onscreen health professionals who conduct the daily symptom checks on a rotating basis, a survey with questions determined by individual employers, and daily email or text messages to remind employees to complete the brief survey questions. Press release.
Nicoya will receive advisory services and up to $299,190 in research and development funding from the National Research Council of Canada Industrial Research Assistance Program (NRC IRAP) to develop a portable COVID-19 saliva diagnostic test called Atlas. This funding comes as part of a joint challenge issued by the Public Health Agency of Canada (PHAC) and the National Research Council of Canada (NRC) through the Innovative Solutions Canada (ISC) program. The saliva-based test will be able to detect COVID-19 infection in less than 20 minutes, with an easy-to-use device that can be employed in a variety of settings. Atlas will be a single-use, disposable device that will detect active infection by testing for SARS-CoV-2 viral proteins. To make the test as accessible as possible, Nicoya is powering it with smartphone technology so that it can deliver lab-quality results to an app in under 20 minutes. The test will be performed with a saliva sample, rather than the more common nasopharyngeal swab samples. With Atlas, Nicoya hopes to make testing more available everywhere, from remote communities to front-line screening procedures. Press release.