Researchers from all across the world are in a quest to find the underlying risk factors that predispose to Covid-19 mortalities. Pre-existing risk factors in clinical settings, such as chronic diseases, can be partially attributed to elevated mortality rates in ethnic minorities, states the world’s largest study to data, analysing over 17.4 million patient’s electronic health records (EHRs) on behalf of NHS England to analyse the risk factors for Covid-19 deaths of more than 5,600 in-hospital deaths.
Risk factors for death from COVID-19 https://t.co/NvFO0fe2cL
— Nature Rev Immunol (@NatRevImmunol) May 27, 2020
This article published in medRxiv, the preprint server for health sciences. Therefore, this study is a preprint and has not been peer-reviewed which means it’s a newly reported medical research that has yet to be evaluated and cannot be used to guide clinical practice.
— medRxiv (@medrxivpreprint) May 7, 2020
Researchers from the University of Oxford and the London School of Hygiene & Tropical Medicine (LSHTM), affiliated with NHSX, worked on behalf of NHS England and used OpenSAFELY analytics platform to investigate over 17.4 million pseudonymised health data of UK adults to determine the basic key risk factors linked with Covid-19 deaths. OpenSAFELY is a new safe platform for analysing NHS electronic health records in order to cater urgent results during the crisis of Covid-19 pandemic. Currently, it successfully analysed more than 24 million anonymous patients called pseudonymised primary care NHS patient records. The use of this platform reduces risk of security breach of patients’ data from transferring and storing elsewhere. To preserve patients’ privacy, NHS keeps control of all the data and data is kept anonymous for researchers.
In the UK, the @OpenSafely project undertook research on NHS patient records that included looking at deprivation and ethnic background and their linkage to Covid-19 deaths. I'm wondering how any such research would work in India with our track record. https://t.co/vlbtMBDU15 pic.twitter.com/UFaybGLpof
— Pranesh Prakash (@pranesh) May 10, 2020
The large-scale study conducted so far analysed more than 17.4 million UK adults during February 1st, 2020 to April 25, 2020. The study delivers the sturdiest evidence to date on Covid-19 risk factors. The study revealed that an estimated 5,707 in hospital deaths >17.4 million were due to Covid-19. In the study, only data of patients hospitalised due to Covid-19 has been used.
In the study, the authors used “multivariable Cox proportional hazards model” identify the risk factors linked with Covid-19 deaths. The potential risk factors include old age, underlying clinical conditions such as respiratory diseases, diabetes, obesity, cancer, kidney and heart failure, brain and autoimmune diseases, male gender, lower social and financial status, and background of non-white ethnicity.
It was found that asthma is one of the major risk factors attributes to Covid-19 deaths. Moreover, relative to white people, Asian and Black ethnic people were discovered to be at higher risk of Covid-19 death. The plausible explanation for such link is higher proportion of clinical conditions in these peoples such as diabetes, heart diseases, and hypertension. These speculations accounts for only small part associated with excessive risk of death. Therefore, it needs further elucidation to fully understate and determine whether death rate is actually high in this group due to presumed clinical conditions.
In this study, research findings also reveal that people with disadvantaged social backgrounds are reported to be at higher risk of death due to Covid-19 which could not justified by other risk factors. Further, the study confirms males are at higher risk of getting Covid-19 infection and die out of it. Individuals with older ages, poorly controlled diabetes, and severe asthma are at highest risk of Covid-19 death.
The speculations obtained from OpenSAFELY analysis are critical for all the countries around the world as right now there is an urgent need of highly accurate data to efficiently manage the pandemic and improve the patient outcomes. Moreover, the OpenSAFELY is a highly secure model to keep the data secure as we owe it each patient whose data is used so far. The OpenSAFELY platform analysis is undergoing further analysis and can be used to determine the spread of novel corona virus with new interventions to model, predict, and assess health services and needs which may help in finding ways to ease lockdown.