- In the biggest study of its kind, OpenSAFELY analysed the data of more than 17 million patients to gain insight into Covid-19 deaths.
- The platform was commissioned by England's National Health Service.
- Ethnicity and socioeconomic factors also seemed to contribute to coronavirus mortality rates.
In probably the biggest study of its kind, more than 17 million patients' data across England were analysed for risk factors contributing to Covid-19-related deaths.
Commissioned by England's National Health Service (NHS), OpenSAFELY is a health analytics platform that uses anonymised data of about 40% of all patients in the country to better understand the impact of the coronavirus.
In the study published in Nature, they linked this data to 10 962 coronavirus deaths to understand what makes people more likely to die from the disease. The last data was from 6 May 2020, which means the numbers might look different today.
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Risk of age
The overall risk of death 90 days after the study's start was less than 0.01% in those aged between 18 and 39 years, rising to 0.67% and 0.44% in men and women respectively aged 80 years and older.
In fact, those above 80 had a twentyfold increased risk of dying from Covid-19 compared to people in their 50s.
Ethnicity plays a role
Besides the risk factors of age, being male, obesity and having comorbidities like diabetes, they also found that patients of black and South Asian ethnicity were much more likely to succumb to the diseases, despite making up only 11% of patients.
"Our findings show that only a small part of the excess risk is explained by higher prevalence of medical problems such as cardiovascular disease or diabetes among Black and minority ethnic people, or higher deprivation.
"We have demonstrated – for the first time – that only a small part of the substantially increased risks of Covid-19 related death among non-white groups and among people living in more deprived areas can be attributed to existing disease," the researchers added.
The researchers recommend that more research be considered on reasons why non-white groups are adversely affected – reasons like occupational exposure and living conditions. It's important to note that this scenario might only be relevant to the UK or in a Western context.
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They also found severe asthma to be a high-risk factor, even though previous studies did not see high death numbers in asthmatics, and might be an under-reported demographic.
One interesting statistic relates to smoking. The researchers found that smoking did not put someone at higher risk of death, unless they had a comorbidity as a result of their nicotine habit. The researchers did posit, though, that more research be conducted, and do not regard nicotine as "protective" against the coronavirus.
OpenSAFELY is still collecting data and will continue to use its massive platform to generate further insights into Covid-19.
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Some concerns were raised by some epidemiologists and data scientists when the study was published as a preprint in an open letter, cautioning that the wording in the study could be interpreted in "causal terms".
The 'Table 2 Fallacy' is where the effect estimates of secondary exposures are presented in the same manner as the primary exposure estimated from the same model.
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