Today's report examining the UK’s pandemic response completely ignores the most obvious explanation for the excess mortality among BAME people. Crucial technology simply did not work properly for them. Thousands of people died literally because of the colour of their skin. 1/
Let me explain.

Early on in the pandemic, it was clear that people of African and South Asian ancestry were disproportionately affected. Here is a picture of the first NHS doctors to die. 2/
The magnitude of the effect of race on risk of dying of COVID was remarkable – a two-fold increase or more. Although many illnesses vary in prevalence and severity across different ancestries these variations can almost always be expressed as small percentage differences. 3/
Exceptions are some genetic conditions such as sickle, thalassaemia and Tay Sachs.

But to see such differences between ethnicities in response to infection was unprecedented. 4/
I was so struck that I wondered if there might be some genetic effect at work, perhaps a variant present in some ancestries but not others which conferred heightened susceptibility. I looked at the two most obvious genes but found nothing.… 5/
Further studies have identified genetic variation which does influence response to COVID. However it can in no way explain the heightened BAME mortality which we observe. Crucially, the main variant increasing risk is actually absent from people with African ancestry. 6/
So what does explain the excess BAME mortality? The report does seek to address this question. You can read it here:

Coronavirus: lessons learned to date… 7/
The report concludes that genetic factors are not the explanation: “genetic differences between ethnic groups cannot explain the higher number of severe cases and deaths since ethnic minorities are very genetically diverse””. 8/
Instead the report concludes that socioeconomic factors and issues around communication may have contributed to increased BAME mortality. But the most important driver may be literally staring us in the face – skin colour. 9/
To understand this, one needs to realise that a crucial part of managing patients with COVID is to assess how much oxygen their lungs are able to absorb. This is a key measure to judge the severity of their condition. 10/
It informs every critical decision – whether to admit to hospital, whether to ventilate, whether to transfer to ITU, etc.

The routine way to measure blood oxygenation is with a pulse oximeter. 11/
This simple device goes over a patient’s finger and shines a light through it to determine the colour of the blood. Blood carrying more oxygen is redder, less oxygen bluer.

Pulse oximeters do not work properly on people with brown skin. 12/
In December 2020 a report was published in a top medical journal, the New England Journal of Medicine. It showed that pulse oximetry was nearly three times as likely to be dangerously inaccurate in Black patients than White patients. 13/
The report is here:

Racial Bias in Pulse Oximetry Measurement…

This is a simply shocking finding. 14/
Medical technology at the heart of managing a variety of conditions simply does not work on BAME patients because it is more difficult to assess the colour of blood through brown skin.

What would this mean in practice? 15/
Somebody unwell with COVID at home might call an ambulance and as part of their assessment the ambulance driver would carry out pulse oximetry. A falsely high reading would result in the patient being left at home when they should have been admitted. 16/
Or a patient might be sent home from A&E because of a high reading. If they did get admitted, they would have regular pulse oximetry every day to assess their progress. 17/
(This is called “measuring sats”, for oxygen saturation.) Again, a high reading could disguise the fact that they had deteriorated and required transfer to ITU. 18/
People were even encouraged to have a pulse oximeter at home so they could check their own readings and know whether to call a doctor or ambulance. The NHS advice is still online:

Using a pulse oximeter to check you are OK… 19/
At every stage of the clinical journey, from calling for assistance to being admitted to being provided with oxygen to being transferred to ITU, a BAME patient would be at much higher risk of a false oximetry reading which would mean that they did not get the correct care. 20/
This horrifying glitch could perfectly well explain a very substantial proportion of the excess mortality among BAME people, quite possibly accounting for thousands of deaths which could have been avoided.

I am baffled that this has not received more attention. 21/
One final, shocking thought. The fact that pulse oximeters do not work properly on BAME patients has been known since 2005.

“The three tested pulse oximeters overestimated arterial oxygen saturation during hypoxia in dark-skinned individuals.” 22/

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More from @davecurtis314

1 Sep
@sw1chg @BallouxFrancois He's referring to the fact that the primary analysis includes the null effect within the confidence intervals:

@sw1chg @BallouxFrancois There are other issues with the study.

Even if there is a real non-random difference between the groups, how do we know this is due to mask-wearing? The intervention group got a lot of information about COVID, encouragement to wear masks, etc. Maybe they were more careful? 2/
@sw1chg @BallouxFrancois In fact, we know that the intervention group did more social distancing than the controls. Maybe this reduced their infection rate? Or maybe something else, like not going out when they were unwell? 3/
Read 5 tweets
11 Jun 20
I have a few thoughts I would like to share about racism and British science. If you’re interested, bear with me. There might be quite a lot to say.

I want to talk about one way research magnifies the disadvantage experienced by ethnic minorities. 1/
Let's begin with UK Biobank and see what happens if we search PubMed for the terms:
biobank white european…

We see things like this.

What's going on? 2/
The UK Biobank has data from half a million British citizens who volunteered to provide personal and health information, blood samples and do other tests to help medical research.

These studies only use data from the volunteers who are white. 3/
Read 19 tweets
14 Apr 20
I see some prominent people are trying to push the agenda that we should routinely wear masks because the overall effect will be to reduce COVID-19 transmission, so let's look at the maths. 1/x
A standard way to define the effectiveness of an intervention is the number needed to treat, NNT. This is the number of people who need to have the intervention in order to achieve the desired outcome. 2/x
For example, if we treat 1000 people with an antihypertensive and 1000 with placebo then at the end of five years we may see 22 heart attacks in the treated group and 24 in the placebo group. 3/x
Read 21 tweets
20 Mar 20
The advice of the Scientific Advisory Group for Emergencies (SAGE): on the Coronavirus (COVID-19) response has been published.…

I think there are major problems with it. 1/n
Major issues are not considered at all, or scarcely. This means that the advice itself is fatally flawed. More later, but I'm particularly thinking of testing, contact tracing, effective therapies, nuanced approach to large events and capacity building. 2/n
Testing is hardly mentioned at all. It's not 100% accurate but it gives a pretty good idea of who is and who is not currently infected (and infectious). It is a keystone of containment in other countries. It's not happening here and that's a disaster. 3/n
Read 31 tweets
18 Feb 20
I work on human genetics and am honorary professor at the UCL Genetics Institute. I’m the editor-in chief of a journal which used to be called Annals of Eugenics. I just wanted to say that we now know from the latest research that eugenics simply would not work.
I have published hundreds of scientific papers on human genetics including on intellectual disability, mental illness and the predictive ability of genetic. You can view the list here:…
Let’s say that the aim of eugenics is to intervene at a societal level to improve the genetic stock of the population, for example to eliminate undesirable characteristics or to produce average increases in the values of desirable traits.
Read 19 tweets

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