Cambridge University Hospitals researchers win award for showing how plasma viscosity can predict progression of Covid-19
Research that showed how a type of blood test could be used to identify Covid-19 patients at greater risk from complications has earned a Cambridge team an award.
Led by Daniel Gleghorn, a senior biomedical scientist at Cambridge University Hospitals NHS Foundation Trust, the researchers showed how testing plasma viscosity can be used to stratify patients. A cheap and reliable test, which is already available in many haematology laboratories, it could aid early intervention for those at more risk of needing intensive care treatment.
The team won the 2021 Bernie Benson Award from Wales-based Benson Viscometers, a leading provider of clinical viscometers in the UK, Europe and the USA, which also has a development factory in Ipswich.
The presentation of the award last week follows the publication of the research in the International Journal of Laboratory Hematology.
In it, Daniel and colleagues Orisadare Olayiwola, Anisa Omer, Roderick Lynn, David Norcliffe and Mark Robinson described how 395 blood samples from Addenbrooke’s Hospital patients were analysed between April and May 2020 using a Benson Viscometer.
Of these, 171 had tested positive for Covid-19 using a PCR test, and they were found to have “significantly” higher plasma viscosity – an average of 2.00mPas, compared to 1.62mPas, and there was a strong correlation between a result above 1.83mPas and disease progression.
Plasma viscosity is essentially the thickness of the liquid part of the blood. It is affected by proteins produced by the body in response to infection or inflammation, and also by proteins produced abnormally in some diseases.
It increases the resistance to blood flow, meaning the heart has to do extra work and the passage of blood to the organs – known as perfusion – can be impaired.
In their research paper, the team reported: “Our results suggest that the level at which inpatient admission is required can be directly correlated with the degree of increase in plasma viscosity.
“We showed that plasma viscosity is highly sensitive at discriminating between inpatients with symptomatic Covid-19 and without.”
While earlier studies had shown elevated plasma viscosity in Covid patients, this work offered “a broader evaluation of plasma viscosity levels in a range of symptomatic hospital inpatients”.
The team said: “This cheap and simple test may provide more useful information in risk-stratifying patients who present with symptoms of Covid-19 as to date there have been no other reported laboratory tests which have been able to quantify the degree of individual disease burden.
“Based on these data, we conclude that plasma viscometry analysis can be implemented into assessment algorithms to help quickly categorize patients with suspected symptoms of Covid-19 into high or low disease complication risk groups.”
They added: “The simplicity of the plasma viscosity test is that this is rapidly available, requires only limited operator training and may help facilitate quick decision-making when combined with additional clinical data such as degree of hypoxia or measurement of other inflammatory proteins.”
The SARS-CoV-2 virus that causes Covid-19 is known to increase serum immunoglobulins as well as fibrinogen and clotting factors in patients’ blood.
The team said: “Our findings demonstrate additional evidence of the increase in serum proteins that contribute to the combined hyperinflammatory and prothrombotic states that have been well reported.”
Daniel would like to broaden the research to a multi-centre study, and explore whether variants of the virus have any impact on plasma viscosity.
He has suggested that routinely measuring this in critically ill Covid patients could offer additional evidence to clinical teams on how the disease is progressing.
Following the award to Daniel and the team, Benson Viscometers said: “The research demonstrated a sensitive and original use of plasma viscosity in the risk stratification of patients with Covid-19 infection.
“This research could change the way we manage the pandemic and help to quickly categorize patients with suspected symptoms of Covid-19 into high or low disease complication risk groups.”
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