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Home›Feature›Scientists identify six different types of covid-19 in ‘major’ breakthrough for treatment

Scientists identify six different types of covid-19 in ‘major’ breakthrough for treatment

By alternativeafrica
July 18, 2020
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London, July 18, 2020 (AltAfrica)-Six distinct types of coronavirus have been identified by scientists in a breakthrough that promises to save lives by flagging the highest-risk patients.

Scientists say the findings will have ‘a profound impact on our understanding of the extent and impact of COVID-19’

Scientists say each with a specific collection of symptoms is a major breakthrough that could help doctors predict which patients are most at risk.

Analysis of thousands of cases by artificial intelligence software has revealed different “clusters” of symptoms and ranked them in order of severity.

READ ALSO: UK BACKED COVID-19 ANTIBODY TEST PASSES FIRST TRIAL WITH 98.6% ACCURACY

Although a continuous cough, fever and loss of smell are usually highlighted as the three key symptoms of the illness, data gathered from around 1,600 users of the COVID Symptom Study app in the UK and US shows that people can experience a wide range of different effects.

African Union launches consortium to search for Africa’s Covid-19 vaccine

These can include headaches, muscle pains, fatigue, diarrhoea, confusion, loss of appetite, shortness of breath and more.

And researchers concluded that which of the six main cluster of symptoms each infected person suffered tended to indicate how quickly the disease would progress and how ill they were likely to get

Scientists at King’s College London (KCL) found that patients with the sixth type of Covid-19 are nearly 10 times more likely to end up needing breathing support than patients in the first group.

This is significant because often patients only deteriorate to a critical stage several days after ashowing symptoms. The new ranking system should flag up the highest-risk cases and give doctors the opportunity to intervene earlier.

The six clusters of symptoms – which emerged at similar points in the disease’s progression – were identified by the researchers along with the likely severity that each tended to correspond with.

And the team behind the study said that while some of the listed symptoms – such as confusion, abdominal pain and shortness of breath – had not been widely linked to COVID-19, they were hallmarks of its most severe forms.

  1. Flu-like’ with no fever – Headache, loss of smell, muscle pains, cough, sore throat, chest pain, no fever.
  2. ‘Flu-like’ with fever – Headache, loss of smell, cough, sore throat, hoarseness, fever, loss of appetite.
  3. Gastrointestinal – Headache, loss of smell, loss of appetite, diarrhoea, sore throat, chest pain, no cough.
  4. Severe level one, fatigue – Headache, loss of smell, cough, fever, hoarseness, chest pain, fatigue.
  5. Severe level two, confusion – Headache, loss of smell, loss of appetite, cough, fever, hoarseness, sore throat, chest pain, fatigue, confusion, muscle pain.
  6. Severe level three, abdominal and respiratory – Headache, loss of smell, loss of appetite, cough, fever, hoarseness, sore throat, chest pain, fatigue, confusion, muscle pain, shortness of breath, diarrhoea, abdominal pain It was discovered that only 1.5% of people with cluster 1, 4.4% of people with cluster 2 and 3.3% of people with cluster 3 required breathing support.

But these figures were 8.6%, 9.9% and 19.8% for clusters 4, 5 and 6 respectively – while nearly half of the patients in cluster 6 ended up in hospital, compared with just 16% of those in cluster 1.

The researchers said that, in general, people with clusters 4, 5 or 6 tended to be older and frailer, and were more likely to be overweight and have pre-existing conditions such as diabetes or lung disease than those with type 1, 2 or 3.

Having identified the different clusters, they then combined information about patients’ age, sex, BMI and pre-existing conditions with symptoms each gathered over just five days from the onset of the illness.

This allowed them to devise a model which they say predicts more accurately – and, crucially, earlier – which cluster each patient falls into and how likely they are to require hospital treatment and breathing support

Dr Claire Steves, from King’s College London, said: “These findings have important implications for care and monitoring of people who are most vulnerable to severe COVID-19.

“If you can predict who these people are at day five, you have time to give them support and early interventions such as monitoring blood oxygen and sugar levels, and ensuring they are properly hydrated – simple care that could be given at home, preventing hospitalisations and saving lives.”

And Sebastien Ourselin, professor of healthcare engineering at King’s College London and senior author of the study, said the research was having “a profound impact on our understanding of the extent and impact of COVID-19”.

Professor Tim Spector added that the findings showed the importance of people getting into the habit of using the app daily, “helping us to stay ahead of any local hotspots or a second wave of infections”.

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