As the COVID-19 pandemic continues, researchers around the world are rapidly publishing new findings related to the virus. The growing body of research creates challenges for health professionals trying to assimilate new evidence efficiently and accurately into their current understanding of the virus, including its behavior, treatment, and risk factors.
To address this challenge, the White House and a group of leading research organizations released the COVID-19 Open Research Dataset Challenge (CORD-19) on the Kaggle machine learning competition platform, providing several discrete tasks for AI practitioners in the general public to tackle. With RTI’s mission being to improve the human condition by turning knowledge into practice, we funded a team of two data scientists and a microbiologist/immunologist to prepare a submission for the task of automatically extracting key information from papers related to the increased risk of blood clotting, seen in 20-30% of COVID-19 patients.
COVID-19 and Blood Clotting
COVID-19 is best known for its direct impacts on the respiratory system, but it can also cause complications across a range of organ systems including the gastrointestinal tract, nervous system, liver and kidneys. Non-respiratory symptoms range from vomiting to a loss of smell.
A tendency for blood to become sticky, or hypercoagulable, precedes blood clot formation and can be especially dangerous to COVID-19 patients, since it can exacerbate the effects of compromised lung function. An emerging hypothesis is that clots in tiny lung air sacs restrict movement of oxygenated blood, thereby compounding the severity of reduced lung capacity associated with pneumonia. Such a scenario would help explain why some people benefit from receiving oxygen rather than the use of mechanical ventilators.
It is currently unclear why the hypercoagulable state occurs in some COVID-19 patients and not others. One possibility is that the virus attacks blood vessel cells via the same ACE2 receptor known to mediate lung infection. Damaged blood vessels could be releasing factors that increase clotting tendency.
To address the hypercoagulable state, physicians have been treating COVID-19 patients with blood thinners known as anti-coagulants and have seen mixed benefit to patients. The best dosing regimens are unknown, and clinicians must monitor for consequences associated with excessive bleeding in the event the prescribed blood thinner dosage is too high.
Despite the known danger, little is known about the best way to combat the blood clotting response seen in COVID-19 and while many reports are being published, information synthesis is a challenge.
The RTI Center for Data Science team developed an iterative, semi-automated workflow for key components of a rapid systematic review to collect evidence on treatments for the hypercoagulable state seen in COVID-19.