New research suggests COVID-19 severity can be predicted in hospitalised patients

Research conducted at Addenbrooke’s hospital and supported by the NIHR Cambridge Biomedical Research Centre has found it may be possible to predict which patients will go on to develop severe or long-term COVID symptoms (sometimes known as ‘long COVID’). The results have been released as a pre-print, due to their implications for public health.

Most people with COVID-19 will experience mild to moderate symptoms without needing medical treatment, but some – most commonly older people or those with underlying health conditions –become seriously ill and may have long-term complications.

In this study, Cambridge researchers looked at blood samples taken at regular intervals over three months from more than 200 people, ranging from COVID patients who were severely ill and needed ventilation to asymptomatic NHS staff who had tested positive for the virus but showed no symptoms.

They compared the samples with those taken from 45 healthy controls.

The samples showed that people’s immune response to COVID-19 determined how sick they were from the virus.

The immune systems in patients who were the sickest showed early evidence of an abnormal inflammatory response, leading to a flood of immune cells which damaged healthy cells as well as the virus. This can cause serious problems such as lung damage and organ failure, and even death.

Worryingly these cells remained in this fighting state even after the virus has been cleared, causing chronic (long-lasting) inflammation.

Crucially evidence of this inflammation was present in the earliest blood samples taken, suggesting that this could help doctors to identify and predict patients who will develop severe COVID.

Doctors could then treat them quickly to prevent long-term damage, using some of the treatments identified in studies such as RECOVERY.

In contrast, the immune responses in patients with mild or asymptomatic symptoms quickly recognised and fought off the infection. This response decreased once the virus was gone, with no chronic inflammation which damages the organs.

Dr Paul Lyons, senior co-author, from the Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), said: “Our evidence suggests that the journey to severe COVID-19 may be established immediately after infection, or at the latest, around the time that they begin to show symptoms.

“This finding could have major implications as to how the disease needs to be managed, as we would need to begin treatment to stop the immune system causing damage very early on.”


The study also indicated a way to help identify which patients may develop ‘long COVID’ – where they no longer have the virus but are still experiencing symptoms of the disease, including fatigue, for several weeks or even months after infection.

In these patients, researchers found that their immune cells still showed signs of abnormalities long after they no longer have the virus and had been discharged from hospital.

Researcher Dr Laura Bergamaschi said: “[These cells] are likely to be of huge importance in long COVID…The more we understand about this, the more likely we will be able to better treat patients whose lives continue to be blighted by the after-effects of COVID-19.”

This research was made possible through the participants in the NIHR COVID-19 BioResource. Professor John Bradley, Chief Investigator of the NIHR BioResource, said: “The NIHR BioResource is a unique resource made possible by the strong links that exist in the UK between doctors and scientists in the NHS and at our universities. It’s because of collaborations such as this that we have learnt so much in such a short time about SARS-CoV-2.”

The research was supported by CVC Capital Partners, the Evelyn Trust, UK Research & Innovation COVID Immunology Consortium, Addenbrooke’s Charitable Trust, the NIHR Cambridge Biomedical Research Centre and Wellcome.

Bergamaschi, L et al. Early immune pathology and persistent dysregulation characterise severe COVID-19. MedRXiV; 15 Jan 2021; DOI: 10.1101/2021.01.11.20248765

• You can read more on this research on the University of Cambridge website.

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