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The Covid pandemic is highlighting
shocking patterns,

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revealing how this disease attacks
men and women differently.

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Men have about a 40% chance of dying
compared to women.

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40% is massive.

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Leading me on a journey to
investigate sex differences

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in health and medicine.

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Wow, is this known by the
general public?

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I don't think it's known.

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What I discover is that even though
women generally outlive men,

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there is a dangerous gender gap in
data and the way women are treated.

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Many of the drugs that we give
we have actually no idea

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how they function in women's bodies.

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I learn how biases in diagnosis can
be life threatening.

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I didn't realise how close I was
to dying.

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PROLONGED PIP

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So, when it comes to our health,
how much does sex matter?

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And ultimately...

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I'm Dr Ronx,
an emergency medicine doctor.

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Over the last year,
hundreds of Covid patients

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have come through my hospital.

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And it's clear more men needed
inpatient treatment

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for Covid-19 than women.

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It made me ask questions about
gender, sex, and race.

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And made me want to investigate why
some people are affected

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much worse than others.

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I'm meeting Anna and Dani, a young,
active couple.

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When we first heard about Covid,
we weren't particularly concerned.

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Early in the first wave,
they both contracted the virus.

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We both lost our taste buds
and sense of smell.

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Whilst my symptoms plateaued
and then sort of disappeared

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within a week, his got very serious
very, very quickly.

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He seemed to just be getting worse
and worse and worse.

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I felt that I was being attacked.

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My body was reacting to it,
but couldn't fight it.

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Hi. Hey, there. How are you?

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I'm really well, thank you.
Right, come on in.

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Thank you.
Keep distance, keep distance.

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Now, Dani, tell me about when you
first realised

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that something wasn't right with
your body.

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So, it was on a Friday in the middle
of March.

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Wasn't really feeling so well.

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Aching bones, loss of taste.

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OK. And then what happened?

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And that's when it
started going downhill.

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Started developing a fever as well.

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And then the other part of it
was the breathing,

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because that in a way was
the game changer.

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And it was as if I was scuba diving,
I'm underwater,

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and someone is little, little by
little turning off that tank.

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And I'm just gasping for air.

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I can't get it in.

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He just had nothing.
Nothing to give. No puff.

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Are either of you thinking, why did
you both have different outcomes?

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Yeah, we've been wondering it
since the beginning.

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Both Anna and I went through the
same initial experience,

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yet Anna plateaued
and started recovering.

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And I pretty much went off
the cliff.

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So, I started thinking about,
"All right, is there a difference?

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"Why did I get it worse
than Anna did?

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"Is there a difference
between the sexes?"

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Anna and Dani aren't
alone in wondering that.

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Anecdotally, men do seem to
be hit harder.

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But is there actually data
backing that up?

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From the very beginning,
I was interested in,

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whether the virus was affecting men
and women differently.

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You'd imagine that it would be
one of the simplest things

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that you could collect on a
medical record.

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But, even so,
we're finding that still,

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a majority of countries are not
telling us anything

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about whether it's men or women that
have got Covid.

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KNOCKS ON DOOR

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Hiya, Sarah.
Hi, Ronx, how are you?

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I'm really well, thank you for
inviting me to your home. Good.

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Come on in... Sarah's organisation
has been collecting available data

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to understand the
global disease patterns.

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We want to know,
is it men getting infected

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or is it women getting infected?

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If we look at the England data,
what we see,

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is that we've got slightly more
cases confirmed amongst women

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in England,
but if we look at deaths,

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we've got more deaths in men.

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And it's very clearly men, as well.
It's very, very clearly men.

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The rate of men being admitted to
intensive care compared

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to women is about double.

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Really? And men have about a 40%
higher chance

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of dying compared to women.

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So, more men are dying?

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And that pattern is repeated again
and again across multiple countries.

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Across the world more
men are dying of Covid than women.

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And, in England, men account
for nearly 60% of all deaths.

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I guess what we now need to find
out, is this related to biology?

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So, XY chromosomes, XX.

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Or is this more about gender and the
behaviours within the social

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constructs that maybe influence
their outcomes?

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We can only ask those questions
because we've got the sex

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disaggregated data
that shows a difference.

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So, you know, data - it's not
the sexiest thing in the world.

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It's not the sexiest thing!
SHE LAUGHS

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But it can be really powerful.

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It feels a little bit ridiculous
that we have all of this data

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that is related to sex, and we
aren't using them to discover

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whether some sexes, or male or
females, do better with diseases.

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So much information and it just
feels like it's all out there,

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but nobody really cares?

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Or maybe there's just not money to,
to interrogate it.

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So, why haven't we been looking at
sex differences more closely?

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Professor Philip Goulder uncovered
sex differences

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in his work investigating HIV,

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and has his own theory to
why it's a little contentious.

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You know, it's sort of a taboo
subject in a way.

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It might be that there's a feeling
to want

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to make out that people are equal.

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That there aren't any differences -
and, therefore,

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to identify differences or suggest
that there might be differences,

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could be an unpopular thing to do.

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On the other hand, I think now that
these differences

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are becoming very clear-cut with
something like Covid,

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people are very interested.

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Philip is conducting
a study investigating

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our immune response to Covid.

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In both sexes our immune system is
divided into two parts,

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the innate and the adaptive.

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The innate response is our first
line of defence.

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It's fast and untargeted.

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A fever is a sign it's working,
raising the temperature

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to kill any potential enemies.

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If that fails, the slower adaptive
response takes over

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with specialised antibodies and
blood cells known as T-cells.

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The question is how and
why do males and females

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respond differently
to the same virus?

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We invited Anna and Dani
on the study

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because they were a special couple,
a special family in the sense that

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they were all exposed at the
same time.

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Philip's colleagues have been taking
samples from both sexes to try

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and understand how their innate and
adaptive responses differ.

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One of the reasons we're really
interested in studying you guys,

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you both, is that your disease
outcome has been very different.

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And that's reflected across
the whole kind of spectrum

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of people who have been infected by
this virus.

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The study will examine differences
in Dani and Anna's T-cell

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and antibody responses.

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If Dani's are higher, it could mean
that his first line of defence

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was weaker, so his adaptive immune
response had to work harder.

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And why haven't we been looking
at the sex differences more before?

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I think, erm...

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..for example, in my field of work
in HIV,

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it took something like 36 years
since the epidemic started

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to realise that women have five
times more chance of completely

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suppressing the virus through their
immune response than men.

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So, if viral infections are hitting
men more severely than women,

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it's worthwhile understanding what's
different between the sexes.

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And the most fundamental thing
are the X and Y chromosomes.

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Most human cells contain 23 pairs
of chromosomes.

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The 23rd pair, the sex chromosomes,
differ between males and females.

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Females have two X chromosomes and
males have one X and one Y.

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Each X chromosome contains around
1,000 genes.

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The Y chromosome is smaller with
less than 100.

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Professor Sabra Klein has been
studying how this

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and other differences between males
and females

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can impact how we fight viruses,
like Covid.

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Sabra, nice to meet you.

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It is lovely to meet you.

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We know that women tend to generate
greater immune responses

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to viruses than do men.

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And high levels of oestrogens have
been associated

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with greater immunity in females.

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Many genes, over 60 genes that are
very important for the

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functioning of our immune system,
are located on the X chromosome.

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And researchers, including myself,
are very interested in trying

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to better understand how these genes
on the X chromosome may serve

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to protect females from things
like viruses.

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Wow. So, when we think about our
immune system,

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in terms of how effective it is,

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it's as basic as our chromosomes,
XX and XY?

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The simple answer is yes, but we do
know that environmental factors

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as well as our hormones play
distinct roles in contributing

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to male-female differences in the
functioning of the immune system.

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Thank you so much.

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Sabra believes that the second X
chromosome is a key reason

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why females have a better immune
response to viruses.

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I'm thinking if our sex chromosomes
play such an important role

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in immunity and disease progression,

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why has scientific research not
looked more closely at this?

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Women outlive men worldwide
by an average of six to eight years.

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In the SARS and MERS outbreaks,
death rates were 50% higher in men.

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But it's not just viral infections.

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Men are also more
likely to develop diabetes

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and cancer research shows

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that men are around 20% more likely
to get cancer

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and up to 40%
more likely to die from it.

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At the Dana-Farber Cancer Institute,
Dr Andy Lane has been

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investigating why more men
die from cancer.

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Tell me a bit
about your research, then.

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So, I'm a physician and scientist
and I take care of patients with

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leukaemia for most
of my time in the clinic.

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Many of the diseases that I take
care of, those patients have a

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slight bias toward
there being more men than women.

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And it was assumed
that it was because men

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did more risky behaviours
than women,

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like they smoked more cigarettes,
they drank more alcohol,

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and indeed, those
things are cancer risk factors

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and they do change perhaps
the skew of cancer,

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but there are a few things that say
it's not simply that.

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Is the same difference
seen amongst boys and girls?

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In children, the two main
most common cancers in children

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are brain tumours and leukaemias.

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Both of those have a male bias.

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Now, it is not two or three to one,

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but it's still 20% or 30%
higher in males than in females,

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that means boys than in girls,

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and so infants are
not working in the factory,

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being exposed to chemicals,
smoking, etc.

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So that got us thinking that there
might be something intrinsic

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to being a male or a female
at the level of the cell,

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the DNA or the
organism that might be contributing.

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Obviously, females
have two X chromosomes,

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males have one X and one Y,

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so of course there's going to be
differences there.

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Having two X chromosomes means
double the amount

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of genetic information.

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For decades, we've understood
that the body switches off

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one X chromosome in each cell -

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X-inactivation.

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Scientists now know that
up to a quarter of the genes

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on the X chromosome escape
inactivation and remain turned on,

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providing a set of back up genes.

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Some of these genes could
give females added protection

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to diseases like cancer.

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In our study, we called them

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escape from X-inactivation
tumour suppressor genes.

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They have a normal function
and one of those functions

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is to prevent the cell
from behaving like a cancer.

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So, in terms of your research,
there is a relationship

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between genes that have escaped
X-inactivation

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and some cancers
and there is a gender bias.

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And that's where the overall
hypothesis of our work came.

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Female cells, by virtue
of having the escape,

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essentially have extra protection

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and that simply was a kind of a new
idea that hadn't been

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looked at across all cancer types.

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00:14:52,930 --> 00:14:54,010
Wow!

242
00:14:54,010 --> 00:14:56,850
Is this known
by the general public?

243
00:14:56,850 --> 00:14:58,570
I don't think it's known.

244
00:14:58,570 --> 00:15:01,490
I don't think it's known by
many physicians and scientists.

245
00:15:04,010 --> 00:15:06,810
The fact that females may
have a biological advantage

246
00:15:06,810 --> 00:15:09,210
when it comes to
many cancers and diseases

247
00:15:09,210 --> 00:15:12,530
makes me think our bodies
are fundamentally different.

248
00:15:12,530 --> 00:15:14,890
But perhaps
that's not so surprising.

249
00:15:14,890 --> 00:15:18,330
After all,
there are clear everyday examples.

250
00:15:18,330 --> 00:15:19,890
If we think about alcohol,

251
00:15:19,890 --> 00:15:24,370
it's well known that women process
alcohol differently from men.

252
00:15:24,370 --> 00:15:27,250
And a simple drug such as
paracetamol,

253
00:15:27,250 --> 00:15:30,810
the recommended dose for
men and women is exactly the same

254
00:15:30,810 --> 00:15:34,410
but we know that men clear
paracetamol from their bloodstream

255
00:15:34,410 --> 00:15:36,850
20% faster than women.

256
00:15:41,570 --> 00:15:45,090
Females process and
metabolise alcohol and medicines

257
00:15:45,090 --> 00:15:48,370
differently to males and it's not
just because of their size.

258
00:15:48,370 --> 00:15:52,170
It's because they
are biologically different.

259
00:15:52,170 --> 00:15:54,530
Women tend to have
more body fat than men,

260
00:15:54,530 --> 00:15:57,490
where medicines can accumulate
and linger.

261
00:15:57,490 --> 00:15:59,410
Their kidneys are also smaller,

262
00:15:59,410 --> 00:16:02,890
which means it takes longer
for drugs to leave their system.

263
00:16:02,890 --> 00:16:06,370
Changing levels of female hormones
also means that drugs can be

264
00:16:06,370 --> 00:16:09,010
processed differently
over a menstrual cycle.

265
00:16:11,850 --> 00:16:16,170
In the past, women were routinely
excluded from drug trials,

266
00:16:16,170 --> 00:16:18,690
partly to protect women's fertility,

267
00:16:18,690 --> 00:16:21,210
but also
because fluctuating hormones

268
00:16:21,210 --> 00:16:23,610
meant women's results were often
inconsistent

269
00:16:23,610 --> 00:16:25,570
and considered too complicated.

270
00:16:27,570 --> 00:16:31,370
So, drug trials have historically
used male cells, male mice

271
00:16:31,370 --> 00:16:33,330
and male humans.

272
00:16:33,330 --> 00:16:36,370
This means most drugs on the market
have been predominantly

273
00:16:36,370 --> 00:16:37,890
tested on men.

274
00:16:37,890 --> 00:16:40,450
But what's the situation today?

275
00:16:40,450 --> 00:16:44,770
"Guidelines for
phase one clinical trials."

276
00:16:44,770 --> 00:16:49,930
So how to make a good trial?

277
00:16:49,930 --> 00:16:55,170
I'm looking for information about,
or guidance in regards, to sex.

278
00:16:55,170 --> 00:16:57,570
OK, so "special populations" -
women!

279
00:16:59,970 --> 00:17:03,490
"The inclusion of women
as early as possible in a drug

280
00:17:03,490 --> 00:17:07,890
"development might be a valuable
clinical strategy".

281
00:17:07,890 --> 00:17:11,130
I don't think it could be valuable.
I think it's absolutely important.

282
00:17:12,370 --> 00:17:15,890
Incredibly, even now in the UK,

283
00:17:15,890 --> 00:17:19,970
including females in clinical trials
isn't a legal requirement.

284
00:17:19,970 --> 00:17:24,370
And shockingly, women are
twice as likely as men to experience

285
00:17:24,370 --> 00:17:29,410
side effects to drugs and have more
adverse reactions to vaccines.

286
00:17:29,410 --> 00:17:33,130
But the lack of females in clinical
trials is only partly to blame.

287
00:17:34,690 --> 00:17:37,930
In his book on the
genetic superiority of women,

288
00:17:37,930 --> 00:17:40,290
Sharon Moalem outlines why
he believes

289
00:17:40,290 --> 00:17:43,970
women have more side
effects when medicine is involved.

290
00:17:43,970 --> 00:17:46,250
Sharon, nice to meet you.
Hello!

291
00:17:46,250 --> 00:17:48,130
Likewise!

292
00:17:48,130 --> 00:17:51,810
Even though women have
this biological advantage,

293
00:17:51,810 --> 00:17:54,170
they're still being
let down by medicine.

294
00:17:54,170 --> 00:17:57,130
Many of the drugs that we
give we have actually no idea

295
00:17:57,130 --> 00:17:59,490
how they function in women's bodies.

296
00:17:59,490 --> 00:18:02,530
This is really scary.
It's really scary to hear.

297
00:18:02,530 --> 00:18:07,050
As someone who has XX chromosomes,
there's a little bit of me that

298
00:18:07,050 --> 00:18:11,450
feels like, oh, the whole population
of men just don't care about women.

299
00:18:11,450 --> 00:18:14,610
I don't think that there was some
type of patriarchal conspiracy.

300
00:18:14,610 --> 00:18:17,210
In fact, I think it's the opposite.

301
00:18:17,210 --> 00:18:18,970
It was seen that
men are a bit stronger

302
00:18:18,970 --> 00:18:21,490
and they didn't want
to harm women's reproduction.

303
00:18:21,490 --> 00:18:24,250
Do you feel that women
are being included more

304
00:18:24,250 --> 00:18:26,610
in clinical trials now?

305
00:18:26,610 --> 00:18:28,530
Yes.
So, what does that mean?

306
00:18:28,530 --> 00:18:32,010
So, if we start out
using male cells and male mice

307
00:18:32,010 --> 00:18:35,450
and then at the end of the trial,
we include both men and women,

308
00:18:35,450 --> 00:18:38,690
but not enough of them
to get a meaningful result.

309
00:18:38,690 --> 00:18:42,610
It's like mixing red
and white wine into a bowl together.

310
00:18:42,610 --> 00:18:43,930
You'll get rose.

311
00:18:43,930 --> 00:18:46,850
And that's the way in
which we have drugs approved.

312
00:18:46,850 --> 00:18:47,970
Wow.

313
00:18:47,970 --> 00:18:50,970
So in fact, by including women
in clinical trials today

314
00:18:50,970 --> 00:18:53,850
we have less information about the
sex differential effects

315
00:18:53,850 --> 00:18:55,170
of the drug.

316
00:18:55,170 --> 00:18:59,210
That's why I'm arguing that why are
we developing drugs for both sexes?

317
00:18:59,210 --> 00:19:01,570
Why don't we have
two parallel systems?

318
00:19:01,570 --> 00:19:05,450
One we use female cells, female
animals, female test subjects,

319
00:19:05,450 --> 00:19:07,410
and then get
drug approval for women.

320
00:19:07,410 --> 00:19:09,530
And do the same thing for men.

321
00:19:09,530 --> 00:19:12,290
We might actually learn that some
drugs may only work for one

322
00:19:12,290 --> 00:19:13,490
sex or another.

323
00:19:13,490 --> 00:19:16,290
This is literally so fascinating.

324
00:19:16,290 --> 00:19:18,930
If we're not going
to take sex into account,

325
00:19:18,930 --> 00:19:21,410
then really we're not going
to really be helping both sexes.

326
00:19:21,410 --> 00:19:23,170
Does sex matter?

327
00:19:23,170 --> 00:19:26,930
Nothing matters from the perspective
of biology and medicine

328
00:19:26,930 --> 00:19:29,210
greater than sex.

329
00:19:29,210 --> 00:19:31,130
DR RONX LAUGHS

330
00:19:31,130 --> 00:19:33,970
What Sharon say makes perfect sense.

331
00:19:33,970 --> 00:19:36,610
If we metabolise drugs differently,

332
00:19:36,610 --> 00:19:42,170
for example females respond up here
and males respond down there,

333
00:19:42,170 --> 00:19:44,250
we mix that data together,

334
00:19:44,250 --> 00:19:48,690
but then it is not clear
how each sex has responded.

335
00:19:48,690 --> 00:19:53,130
And so, if we are going to include
females in clinical trials,

336
00:19:53,130 --> 00:19:59,570
we need to be examining the data
and dividing it by sex,

337
00:19:59,570 --> 00:20:02,770
otherwise we could
be doing more harm than good.

338
00:20:06,290 --> 00:20:11,130
And sometimes, even when we
do know a drug will have adverse

339
00:20:11,130 --> 00:20:14,210
effects, the information doesn't
get through to women.

340
00:20:14,210 --> 00:20:17,330
An example is a drug
called sodium valproate,

341
00:20:17,330 --> 00:20:20,290
that has been on the market
since 1973.

342
00:20:20,290 --> 00:20:23,490
It's used mainly to treat epilepsy.

343
00:20:23,490 --> 00:20:26,370
Even though regulators have known
about the dangers

344
00:20:26,370 --> 00:20:27,970
of this drug for decades

345
00:20:27,970 --> 00:20:31,530
very few patients were told
that it could damage unborn babies.

346
00:20:38,010 --> 00:20:41,450
Emma has epilepsy
and has been taking sodium valproate

347
00:20:41,450 --> 00:20:43,530
since the age of 12.

348
00:20:43,530 --> 00:20:47,930
Her friend Janet has also
taken the drug since her teens.

349
00:20:47,930 --> 00:20:52,610
When they decided to have children,
each consulted with their doctor.

350
00:20:52,610 --> 00:20:56,290
The consultant always advised
that it would be OK to take during

351
00:20:56,290 --> 00:20:59,650
pregnancy, there would be no risks
to the baby,

352
00:20:59,650 --> 00:21:01,570
and that's what I did.

353
00:21:06,730 --> 00:21:09,930
I've got five children and
they've all been diagnosed with

354
00:21:09,930 --> 00:21:12,290
Foetal Valproate Spectrum Disorder.

355
00:21:12,290 --> 00:21:17,850
There are many symptoms - autism,
epilepsy, cerebral palsy, deafness,

356
00:21:17,850 --> 00:21:22,890
incontinence, neurodevelopmental
delays, speech and language delay.

357
00:21:24,370 --> 00:21:25,570
A huge array.

358
00:21:25,570 --> 00:21:29,970
Emma and Janet now know that
these issues are all related to the

359
00:21:29,970 --> 00:21:33,850
sodium valproate that
they each took in pregnancy.

360
00:21:33,850 --> 00:21:36,210
They were poorly,
they weren't developing.

361
00:21:36,210 --> 00:21:40,210
It couldn't just be my bad
luck that this was happening.

362
00:21:40,210 --> 00:21:42,730
My sister phoned me one day

363
00:21:42,730 --> 00:21:46,330
and she was she was crying on the
phone saying that she'd seen a lady

364
00:21:46,330 --> 00:21:51,850
appealing for women to come forward
who had been on sodium valproate.

365
00:21:51,850 --> 00:21:54,210
That was a light bulb moment.

366
00:21:54,210 --> 00:21:58,770
It was that moment where everything
I had been saying to everyone,

367
00:21:58,770 --> 00:22:03,970
to health care professionals,
doctors, nurses, family...

368
00:22:05,650 --> 00:22:09,570
..that there was something wrong and
no-one believed what I was saying.

369
00:22:10,890 --> 00:22:15,290
Very hard, and just to speak
to Janet, just to hear somebody

370
00:22:15,290 --> 00:22:17,690
that knew what I was going through,
it was...

371
00:22:19,970 --> 00:22:21,330
I'll never forget that moment.

372
00:22:23,410 --> 00:22:26,010
It saved my life,
it saved my children's life

373
00:22:26,010 --> 00:22:28,210
because we've now got answers.

374
00:22:30,570 --> 00:22:34,010
Since we met, we decided
to start this campaign and try

375
00:22:34,010 --> 00:22:38,410
and help and support other families
and try and make a difference

376
00:22:38,410 --> 00:22:41,370
to ensure that these
families are looked after the way

377
00:22:41,370 --> 00:22:45,090
that they should be, knowing full
well that they weren't at the time.

378
00:22:54,250 --> 00:22:57,930
One family that has joined
their campaign are Lisa, Robbie

379
00:22:57,930 --> 00:23:00,010
and their nine-year old son, Kieron.

380
00:23:00,010 --> 00:23:03,010
He's one of around
20,000 children that have been

381
00:23:03,010 --> 00:23:07,250
affected by sodium valproate
since it came to market in 1973.

382
00:23:08,370 --> 00:23:11,410
He knows he's
different from other people,

383
00:23:11,410 --> 00:23:13,930
other children
notice he's different.

384
00:23:13,930 --> 00:23:16,210
He struggles with writing,

385
00:23:16,210 --> 00:23:18,850
anything, fine motor,

386
00:23:18,850 --> 00:23:20,450
speech.

387
00:23:20,450 --> 00:23:24,130
He's still struggling with sight -
he's improving.

388
00:23:25,490 --> 00:23:27,330
Yeah, he's got quite a lot.

389
00:23:30,370 --> 00:23:33,330
It went a bit off.
It went a bit off!

390
00:23:33,330 --> 00:23:35,650
But he is still special.

391
00:23:35,650 --> 00:23:37,930
We wouldn't have him any other way.

392
00:23:40,490 --> 00:23:43,850
At no point at all did they say
you shouldn't be taking this drug

393
00:23:43,850 --> 00:23:48,250
if you're thinking about having
a child in the future

394
00:23:48,250 --> 00:23:51,050
or we could wean you off this drug,
anything like that.

395
00:23:54,490 --> 00:23:56,610
I thought it was me.

396
00:23:56,610 --> 00:24:01,130
Have I been a bad mum
or am I fated to be like this?

397
00:24:01,130 --> 00:24:03,690
I think there'll always
be an essence of guilt there.

398
00:24:03,690 --> 00:24:06,490
But today, thanks to the
campaigning of Janet and Emma,

399
00:24:06,490 --> 00:24:10,890
women taking sodium valproate
are much more aware of the dangers.

400
00:24:10,890 --> 00:24:14,610
So that's a big warning for women
and girls

401
00:24:14,610 --> 00:24:18,330
that this medicine can
seriously harm your unborn baby.

402
00:24:18,330 --> 00:24:24,770
I started to get these on my
medication probably around 2019.

403
00:24:24,770 --> 00:24:27,210
It is something clear
and it is something there,

404
00:24:27,210 --> 00:24:29,850
and it's something you take note of,

405
00:24:29,850 --> 00:24:32,250
but there was nothing there,
not a thing.

406
00:24:33,810 --> 00:24:38,210
How many families' lives wouldn't
have been, not ruined,

407
00:24:38,210 --> 00:24:41,130
but turned upside down,
just with a little symbol?

408
00:24:43,490 --> 00:24:48,890
This symbol has finally given women
the power to make informed choices.

409
00:24:50,210 --> 00:24:53,490
Emma and Janet tell me
it took years of campaigning

410
00:24:53,490 --> 00:24:56,010
for their concerns to be heard.

411
00:24:56,010 --> 00:25:00,050
It feels to me,
and I'm pretty cross about this,

412
00:25:00,050 --> 00:25:04,810
that historically, women have not
been listened to. Yeah.

413
00:25:04,810 --> 00:25:10,690
Historically, women
are seemly being "protected"

414
00:25:10,690 --> 00:25:15,170
from making informed
decisions about their bodies.

415
00:25:15,170 --> 00:25:16,650
Absolutely.

416
00:25:16,650 --> 00:25:19,490
And we definitely feel it is...

417
00:25:20,650 --> 00:25:22,930
It's an institutional problem.

418
00:25:22,930 --> 00:25:24,210
Absolutely.

419
00:25:24,210 --> 00:25:29,450
It is agreed that pregnant
people on sodium valproate

420
00:25:29,450 --> 00:25:32,330
should be warned about this. Yeah.

421
00:25:32,330 --> 00:25:35,530
But not every pregnant person is.

422
00:25:35,530 --> 00:25:37,170
Is that what we're saying? No.

423
00:25:37,170 --> 00:25:38,970
Yes, exactly.

424
00:25:38,970 --> 00:25:41,330
We know that there
are families out there

425
00:25:41,330 --> 00:25:43,690
that still
aren't being told about it.

426
00:25:43,690 --> 00:25:45,650
And I think
that's what keeps us going.

427
00:25:45,650 --> 00:25:50,170
We know that there were 400 babies
harmed by valproate last year.

428
00:25:51,730 --> 00:25:56,130
Janet, Emma, you've done
so much already.

429
00:25:56,130 --> 00:26:00,170
You have used
kind of personal trauma

430
00:26:00,170 --> 00:26:03,250
to actually make
changes to a medication.

431
00:26:03,250 --> 00:26:07,250
You're thinking about
future children and you really,

432
00:26:07,250 --> 00:26:13,130
really want women to have
the autonomy to make decisions

433
00:26:13,130 --> 00:26:18,650
with correct information about their
bodies and their future pregnancies

434
00:26:18,650 --> 00:26:22,370
and I am humbled by you,

435
00:26:22,370 --> 00:26:26,010
but absolutely disgusted
that it's taken this long.

436
00:26:34,090 --> 00:26:36,130
The story of these families

437
00:26:36,130 --> 00:26:38,810
highlights many flaws within
the system

438
00:26:38,810 --> 00:26:41,210
and the biggest concern of them all

439
00:26:41,210 --> 00:26:44,610
is that women were not
listened to and dismissed.

440
00:26:44,610 --> 00:26:48,250
Deliberate or unconscious,
in the medical world

441
00:26:48,250 --> 00:26:51,170
bias against women exists,

442
00:26:51,170 --> 00:27:00,480
and this can lead
to serious consequences.

443
00:27:00,480 --> 00:27:04,880
It's obvious, but females
are biologically different to males.

444
00:27:04,880 --> 00:27:09,480
But it goes way beyond drugs
acting on the sexes differently.

445
00:27:09,480 --> 00:27:14,480
Women can also present differently
to men for the same conditions.

446
00:27:14,480 --> 00:27:18,160
But because so much of medicine
and health care is biased to men,

447
00:27:18,160 --> 00:27:20,520
these differences
are often overlooked.

448
00:27:20,520 --> 00:27:25,160
You can see this bias in
the diagnosis of autism.

449
00:27:25,160 --> 00:27:27,440
Scientists believe that
thousands of women

450
00:27:27,440 --> 00:27:30,200
and girls are going undiagnosed.

451
00:27:30,200 --> 00:27:32,960
And part of the reason
is that this condition

452
00:27:32,960 --> 00:27:36,600
is typically linked
to boys and men.

453
00:27:36,600 --> 00:27:38,960
Francesca, Hi. I'm Dr Ronx.
Hi, nice to see you, come on in.

454
00:27:38,960 --> 00:27:42,080
Thank you.

455
00:27:42,080 --> 00:27:47,200
When I have watched TV programmes
or met autistic people,

456
00:27:47,200 --> 00:27:51,680
they tend to always be men, male.

457
00:27:51,680 --> 00:27:53,760
So, we have the stereotype

458
00:27:53,760 --> 00:27:56,800
and it's perpetuated
in research, actually.

459
00:27:56,800 --> 00:27:59,160
A lot of studies didn't
even recruit females,

460
00:27:59,160 --> 00:28:00,960
cos they didn't
expect to get enough.

461
00:28:00,960 --> 00:28:03,880
And that's a real problem, because
then that trickles down into

462
00:28:03,880 --> 00:28:06,600
what we know about autism, how we
design the diagnostic systems

463
00:28:06,600 --> 00:28:10,520
and so on. So, this
male stereotype is a real problem.

464
00:28:10,520 --> 00:28:12,920
We know that some autistic women

465
00:28:12,920 --> 00:28:15,640
develop quite
complex masking behaviour.

466
00:28:15,640 --> 00:28:17,720
So they've learnt how to behave

467
00:28:17,720 --> 00:28:21,040
and they maybe watch a lot of films
to try and learn, "How do I dress?

468
00:28:21,040 --> 00:28:22,880
"How do I walk? What do I talk
about?

469
00:28:22,880 --> 00:28:24,520
"How do I start a conversation?"

470
00:28:24,520 --> 00:28:27,920
Learning quite consciously
and deliberately how to fit in.

471
00:28:27,920 --> 00:28:33,320
How does the diagnostic tool
that you use cater for this?

472
00:28:33,320 --> 00:28:35,760
I can imagine many young girls,

473
00:28:35,760 --> 00:28:39,560
many women will be able to fake it,
for want of a better word.

474
00:28:39,560 --> 00:28:41,480
It's a really important question -

475
00:28:41,480 --> 00:28:45,040
how do we adapt diagnosis to
be fair to women and girls?

476
00:28:45,040 --> 00:28:47,840
And at the moment,
that hasn't really been done.

477
00:28:47,840 --> 00:28:50,240
We need to focus our research
on them so that what

478
00:28:50,240 --> 00:28:53,360
we know about autism isn't just
what we know about male autism.

479
00:28:56,120 --> 00:28:59,520
Autistic women and girls
often go undiagnosed

480
00:28:59,520 --> 00:29:04,160
partly because they are able to
mask or camouflage their autism.

481
00:29:04,160 --> 00:29:08,840
At Limpsfield Grange, a state school
comprising mostly of autistic girls,

482
00:29:08,840 --> 00:29:11,440
their headteacher believes
that early intervention

483
00:29:11,440 --> 00:29:15,040
is the key to
accessing tailored support.

484
00:29:15,040 --> 00:29:19,080
Miss Wild, hello.
Hi, Ronx, lovely to meet you.

485
00:29:19,080 --> 00:29:22,160
How are you? I'm very good
thank you. How are you?

486
00:29:22,160 --> 00:29:26,120
Parents who suspect that
their children are autistic,

487
00:29:26,120 --> 00:29:29,240
or their female child is autistic,

488
00:29:29,240 --> 00:29:31,040
what are the things
that they've told you

489
00:29:31,040 --> 00:29:33,800
in terms of difficulties
getting diagnosis?

490
00:29:33,800 --> 00:29:36,160
They come up against lots
and lots of barriers,

491
00:29:36,160 --> 00:29:38,440
and it's almost like autism isn't
even on the list

492
00:29:38,440 --> 00:29:39,600
because you're female.

493
00:29:39,600 --> 00:29:42,600
Actually, it is about medical
professionals and GPs, in
particular,

494
00:29:42,600 --> 00:29:46,600
having an open mind and really
hearing what people say.

495
00:29:46,600 --> 00:29:49,760
It feels quite poignant to hear you
say, "Health care professionals

496
00:29:49,760 --> 00:29:54,160
"need to be open-minded and learn
to do better and be better."

497
00:29:54,160 --> 00:29:56,520
I am ten years out of
medical school now and still

498
00:29:56,520 --> 00:30:00,920
when anybody says the word
autistic, autism to me,

499
00:30:00,920 --> 00:30:04,240
I have somebody lining
up pencils or cars

500
00:30:04,240 --> 00:30:06,240
or being really intelligent.

501
00:30:06,240 --> 00:30:09,800
Or I've got the really unruly,

502
00:30:09,800 --> 00:30:13,520
difficult to manage
non-verbal autistic boy.

503
00:30:13,520 --> 00:30:17,920
In my head, I definitely
don't have an autistic woman or
an autistic female child.

504
00:30:17,920 --> 00:30:20,840
It's really about
just people listening.

505
00:30:20,840 --> 00:30:22,840
And, actually, if you
don't make the right call,

506
00:30:22,840 --> 00:30:24,760
you don't listen to
all of the information,

507
00:30:24,760 --> 00:30:27,640
you're going to close down doors
that you're not even thinking about.

508
00:30:27,640 --> 00:30:31,000
And I guess we all come
with our own biases, don't we?

509
00:30:31,000 --> 00:30:33,000
In our workplace,
in our social life, etc.

510
00:30:33,000 --> 00:30:37,680
I feel even more worried
that the biases that

511
00:30:37,680 --> 00:30:42,960
I hold would prevent a young
person being able to access

512
00:30:42,960 --> 00:30:46,080
the care that they need,
which could be life-changing.

513
00:30:51,640 --> 00:30:55,640
Hi, everybody,
thanks for having me here.

514
00:30:55,640 --> 00:30:57,920
I'm Amina and I'm 13.

515
00:30:57,920 --> 00:30:59,760
I'm Scarlett and I'm 15.

516
00:30:59,760 --> 00:31:01,720
My name is Leila and I'm 15.

517
00:31:01,720 --> 00:31:04,800
I'm Sophie and I'm 12.

518
00:31:04,800 --> 00:31:08,120
Are you able to tell
me about when

519
00:31:08,120 --> 00:31:11,400
you were first told that
you were autistic?

520
00:31:11,400 --> 00:31:14,000
I was diagnosed formally
when I was three.

521
00:31:14,000 --> 00:31:18,400
I think I was about seven or eight.

522
00:31:18,400 --> 00:31:21,360
I was in year five at my old
mainstream primary school.

523
00:31:21,360 --> 00:31:23,720
And it was more of a
relief to my parents,

524
00:31:23,720 --> 00:31:26,520
cos they were fighting
so much to get my diagnosis.

525
00:31:26,520 --> 00:31:29,480
I was nine when I was diagnosed.

526
00:31:29,480 --> 00:31:32,800
And I remember, like, cos my
parents, literally, like Scarlett,

527
00:31:32,800 --> 00:31:37,200
they'd been fighting for, like,
two years, like, so hard.

528
00:31:37,200 --> 00:31:40,040
You seem very, very
confident and socialised.

529
00:31:40,040 --> 00:31:41,640
So do you think that was part

530
00:31:41,640 --> 00:31:44,960
of the reason why your
diagnosis came later?

531
00:31:44,960 --> 00:31:47,440
I guess I was just
really good at masking,

532
00:31:47,440 --> 00:31:50,960
which I don't know if that's
a good thing or a bad thing,

533
00:31:50,960 --> 00:31:54,000
but nowhere would believe
that I was autistic.

534
00:31:54,000 --> 00:31:59,080
And that is really something that
us doctors need to realise is

535
00:31:59,080 --> 00:32:05,000
that in girls, the way that autism
traits and autism can present

536
00:32:05,000 --> 00:32:10,200
sometimes is just so subtle that we
mistake it for something else.

537
00:32:10,200 --> 00:32:14,600
Now, tell me how your life has
changed being here.

538
00:32:14,600 --> 00:32:19,000
I guess I know who myself is
and I know I'm not like the angry

539
00:32:19,000 --> 00:32:23,840
person I was when I was,
like, before I was diagnosed.

540
00:32:23,840 --> 00:32:26,200
Now that I'm here,

541
00:32:26,200 --> 00:32:29,320
I've found girls
who are just like me.

542
00:32:29,320 --> 00:32:32,080
This school has honestly
changed my life.

543
00:32:32,080 --> 00:32:36,760
I think it's created
a person out of what

544
00:32:36,760 --> 00:32:41,000
I was at a mainstream school that
I could never have done by myself.

545
00:32:50,960 --> 00:32:53,640
The alpacas are quite jittery
and they're quite anxious

546
00:32:53,640 --> 00:32:56,240
and so it's quite a good way
of talking to the girls about,

547
00:32:56,240 --> 00:32:59,760
"Well you have to be a bit calmer if
"you want to spend time with the
alpacas."

548
00:32:59,760 --> 00:33:03,000
Just seeing how this school supports
autistic girls

549
00:33:03,000 --> 00:33:07,320
really emphasises how
important early diagnosis is

550
00:33:07,320 --> 00:33:09,320
for their quality of life.

551
00:33:09,320 --> 00:33:13,720
The gender bias in autism,
I don't think it's deliberate,

552
00:33:13,720 --> 00:33:16,080
but definitely needs
to be challenged.

553
00:33:16,080 --> 00:33:20,400
We need to be asking specific
questions which pick up

554
00:33:20,400 --> 00:33:22,360
female autistic traits.

555
00:33:22,360 --> 00:33:24,720
And I guess as a society,

556
00:33:24,720 --> 00:33:29,000
we need to redefine
our understanding of autistic women.

557
00:33:33,400 --> 00:33:36,440
Gender bias exists everywhere.

558
00:33:36,440 --> 00:33:39,280
It prevents women and girls
from getting help sooner

559
00:33:39,280 --> 00:33:41,640
and in some conditions,
like heart disease,

560
00:33:41,640 --> 00:33:45,040
this delay can be
a matter of life or death.

561
00:33:45,040 --> 00:33:48,400
We tend to think of heart
attacks as a male problem,

562
00:33:48,400 --> 00:33:52,120
but it is the single biggest
killer in women worldwide.

563
00:33:52,120 --> 00:33:56,480
For both sexes, crushing chest
pain can be the main symptom.

564
00:33:56,480 --> 00:33:59,120
But as Dr Kunadian explains to me,

565
00:33:59,120 --> 00:34:02,840
women are more likely to present
with a wider range of symptoms.

566
00:34:02,840 --> 00:34:06,040
In medical school, I just remember
being taught that it's the

567
00:34:06,040 --> 00:34:07,480
"Oh, my God! Oh, my God!"

568
00:34:07,480 --> 00:34:10,280
You know, pale, sweaty,
clutching chests.

569
00:34:10,280 --> 00:34:14,000
But in reality,
that isn't always what we see.

570
00:34:14,000 --> 00:34:17,080
The gender bias in heart disease
is something that we have

571
00:34:17,080 --> 00:34:19,440
known about for a
number of years now.

572
00:34:19,440 --> 00:34:24,120
So, when a woman presents or
even if she's experiencing,

573
00:34:24,120 --> 00:34:29,040
she doesn't think that she could be
having a heart problem herself.

574
00:34:29,040 --> 00:34:31,040
One of Dr Kunadian's patients,

575
00:34:31,040 --> 00:34:32,960
35-year old Jenna,

576
00:34:32,960 --> 00:34:35,640
experienced this bias first-hand.

577
00:34:38,280 --> 00:34:41,680
On TV it seems to be
portrayed as a man's problem.

578
00:34:41,680 --> 00:34:45,040
It's always the men that you see
hit the floor, holding their arm.

579
00:34:45,040 --> 00:34:47,400
It's not very often you see a woman.

580
00:34:47,400 --> 00:34:51,280
I had no chest pains, no
pain in the arm, nothing like that.

581
00:34:51,280 --> 00:34:54,400
No shortness of breath,
nothing at all.

582
00:34:57,760 --> 00:35:00,840
I felt like I had a little
bit of heartburn.

583
00:35:00,840 --> 00:35:06,160
It felt like there was acid
rising from here, like about here,

584
00:35:06,160 --> 00:35:07,520
up my throat,

585
00:35:07,520 --> 00:35:10,680
just to around my lower jaw,
but it went as quick as it came.

586
00:35:10,680 --> 00:35:14,360
It started happening at least
three, four times a day.

587
00:35:14,360 --> 00:35:18,760
So I thought, "I think it's probably
time I went and seen a doctor."

588
00:35:18,760 --> 00:35:22,480
The nurse examined us, she said she
could hear a slight crackle

589
00:35:22,480 --> 00:35:25,520
on one of my lungs
and gave us antibiotics.

590
00:35:25,520 --> 00:35:27,920
I thought I just had an infection.

591
00:35:30,400 --> 00:35:32,000
I got an episode while I was in Asda

592
00:35:32,000 --> 00:35:35,200
and it lasted about four or
five minutes.

593
00:35:35,200 --> 00:35:37,560
So, I just stood still
leaning on the trolley,

594
00:35:37,560 --> 00:35:40,640
waited for it to pass,
continued doing my shopping.

595
00:35:40,640 --> 00:35:43,320
My sister ended up
phoning an ambulance.

596
00:35:43,320 --> 00:35:44,800
When they came into my house,

597
00:35:44,800 --> 00:35:47,160
they just came in,
introduced themselves,

598
00:35:47,160 --> 00:35:49,200
put the stuff down on
the floor and said,

599
00:35:49,200 --> 00:35:51,880
"Right. Come on, then. We'll stick
this ECG machine on you."

600
00:35:51,880 --> 00:35:54,600
And you could tell by his face
when he looked at the results,

601
00:35:54,600 --> 00:35:56,680
it was like, "Yeah."

602
00:35:56,680 --> 00:35:59,880
He took my husband into the passage
and I could hear him saying,

603
00:35:59,880 --> 00:36:01,840
"Your wife's having a heart attack,

604
00:36:01,840 --> 00:36:04,120
"and if she's not in Freeman's
within the next 30 minutes,

605
00:36:04,120 --> 00:36:05,360
"she's not going to make it."

606
00:36:07,800 --> 00:36:11,120
I didn't realise how
close I was to dying.

607
00:36:11,120 --> 00:36:13,760
Skinny, 35.

608
00:36:13,760 --> 00:36:16,200
Walking, talking.

609
00:36:16,200 --> 00:36:19,240
But it nearly killed us.

610
00:36:19,240 --> 00:36:21,440
If it can happen to me,
it can happen to anybody.

611
00:36:24,040 --> 00:36:26,320
Jenna wasn't having
a chest infection,

612
00:36:26,320 --> 00:36:27,960
she wasn't having indigestion,

613
00:36:27,960 --> 00:36:31,840
but she was actually having
a full-blown heart attack.

614
00:36:31,840 --> 00:36:34,480
The important thing
is that these atypical

615
00:36:34,480 --> 00:36:39,040
characteristics of the heart
pain has been described more

616
00:36:39,040 --> 00:36:43,480
prevalent in women
when compared to men

617
00:36:43,480 --> 00:36:48,960
and that could be one of the reasons
why women's symptoms are ignored.

618
00:36:48,960 --> 00:36:51,320
That has shocked me

619
00:36:51,320 --> 00:36:53,880
and then I think lots of doctors
would then be thinking,

620
00:36:53,880 --> 00:36:57,320
"Hmm. I've seen loads of female
patients with heart pain or

621
00:36:57,320 --> 00:37:01,040
"chest pain or symptoms that
I couldn't quite place.

622
00:37:01,040 --> 00:37:03,600
"They were well,
so I've sent them home.

623
00:37:03,600 --> 00:37:06,320
"Maybe I should have sent them to
the Rapid Access Chest Clinic

624
00:37:06,320 --> 00:37:10,200
"or to have an angiogram sooner."

625
00:37:10,200 --> 00:37:13,080
Women are 50% more likely
than men to receive the wrong

626
00:37:13,080 --> 00:37:15,720
initial diagnosis for
a heart attack

627
00:37:15,720 --> 00:37:18,960
and this can often be fatal.

628
00:37:18,960 --> 00:37:22,880
One diagnostic tool used is
the coronary angiogram.

629
00:37:22,880 --> 00:37:26,880
It uses X-ray imaging and contrast
dye to see if your heart's

630
00:37:26,880 --> 00:37:30,560
blood vessels are allowing
blood through as they should.

631
00:37:30,560 --> 00:37:34,600
Most male heart attack patients show
very clear blockages like this one.

632
00:37:34,600 --> 00:37:37,920
But this angiogram,
of a woman's heart,

633
00:37:37,920 --> 00:37:40,880
reveals they often have
a different cause.

634
00:37:40,880 --> 00:37:46,680
What we see is that her arteries
further down, they are very narrowed

635
00:37:46,680 --> 00:37:52,160
and some unusual appearances,
particularly in that area

636
00:37:52,160 --> 00:37:56,080
and that is a
condition which happens

637
00:37:56,080 --> 00:38:00,120
more frequently in
women than in men.

638
00:38:00,120 --> 00:38:02,560
Women are more than
twice as likely as men

639
00:38:02,560 --> 00:38:05,560
to have only partially
blocked arteries.

640
00:38:05,560 --> 00:38:09,960
This means problems are harder
to spot on an angiogram.

641
00:38:09,960 --> 00:38:13,760
From the patients to the families
to health care professionals,

642
00:38:13,760 --> 00:38:18,160
the bias runs deep and it's actually
quite upsetting that only

643
00:38:18,160 --> 00:38:22,920
recently we've become
aware of these sex differences.

644
00:38:22,920 --> 00:38:24,680
When women show different symptoms

645
00:38:24,680 --> 00:38:26,960
and health care professionals
don't listen,

646
00:38:26,960 --> 00:38:29,520
women are harmed.

647
00:38:29,520 --> 00:38:31,160
This can be avoided.

648
00:38:31,160 --> 00:38:33,500
Things have got to change.

649
00:38:39,170 --> 00:38:42,970
It's now clear to me there's a
data gap between the sexes.

650
00:38:42,970 --> 00:38:45,930
Information is missing
about women's health

651
00:38:45,930 --> 00:38:48,210
and it's costing women their lives.

652
00:38:48,210 --> 00:38:50,050
But it doesn't stop there.

653
00:38:50,050 --> 00:38:54,450
I feel kind of embarrassed
and ashamed that

654
00:38:54,450 --> 00:38:59,570
I haven't thought more openly about
sex differences in lots of things.

655
00:38:59,570 --> 00:39:03,970
So, being a feminist, I'm always
thinking this world is unequal,

656
00:39:03,970 --> 00:39:05,850
this world is designed for men,

657
00:39:05,850 --> 00:39:08,250
everything is for men,
blah, blah, blah, blah,

658
00:39:08,250 --> 00:39:11,610
but I've never actually sat down
and thought, actually,

659
00:39:11,610 --> 00:39:17,410
in terms of health outcomes and also
just even broader in terms of...

660
00:39:17,410 --> 00:39:22,210
..each...how the world is designed,
I've never really sat down

661
00:39:22,210 --> 00:39:24,930
and thought, is there data in
regards to this?

662
00:39:24,930 --> 00:39:29,330
This gender data gap is something
Caroline Criado Perez

663
00:39:29,330 --> 00:39:32,970
investigated in her best-selling
book, Invisible Women.

664
00:39:32,970 --> 00:39:35,250
Caroline! Hello.

665
00:39:35,250 --> 00:39:36,450
Hi! Hi!

666
00:39:36,450 --> 00:39:38,970
How are you? Oh, I'm good,
thank you! Hello!

667
00:39:41,570 --> 00:39:43,850
I just couldn't help myself.

668
00:39:43,850 --> 00:39:50,290
I was so horrified to discover

669
00:39:50,290 --> 00:39:55,890
that we were basing medical
treatment

670
00:39:55,890 --> 00:40:01,650
and the development of drugs just
using male bodies,

671
00:40:01,650 --> 00:40:05,410
and that women were basically dying
as a result.

672
00:40:05,410 --> 00:40:06,850
Obviously not in every instance.

673
00:40:06,850 --> 00:40:09,930
And so we just don't notice
when we're excluding women

674
00:40:09,930 --> 00:40:12,290
because we're always talking
gender neutrally,

675
00:40:12,290 --> 00:40:14,650
when most of the time we're
actually talking about men.

676
00:40:14,650 --> 00:40:18,570
And then when women don't conform to
that, they're screwed.

677
00:40:18,570 --> 00:40:21,530
And that's the most frustrating
thing for me,

678
00:40:21,530 --> 00:40:24,410
is that it does seem really,
really, really obvious.

679
00:40:24,410 --> 00:40:27,210
How can this be
going on in the 21st century

680
00:40:27,210 --> 00:40:29,690
and it not be, you know, a
front-page news story every day?

681
00:40:29,690 --> 00:40:31,730
And that is because of the data gap.

682
00:40:31,730 --> 00:40:34,730
So in the allocation of Government
resources,

683
00:40:34,730 --> 00:40:38,730
in how we plan our economy,
in public transport,

684
00:40:38,730 --> 00:40:40,570
in private transport,

685
00:40:40,570 --> 00:40:42,770
and you just see it crop up in all
sorts of areas.

686
00:40:44,530 --> 00:40:47,850
The solution to the gender data gap
is very, very simple.

687
00:40:47,850 --> 00:40:52,250
All you have to do is collect
data on men and data on women,

688
00:40:52,250 --> 00:40:55,890
and then label it and
then analyse it separately.

689
00:41:00,770 --> 00:41:05,170
I believe it's so important
this data gap is filled.

690
00:41:05,170 --> 00:41:09,090
Understanding differences is going
to help both sexes.

691
00:41:09,090 --> 00:41:11,730
It's what the
Oxford team are trying to do

692
00:41:11,730 --> 00:41:14,090
with their Covid immunity study -

693
00:41:14,090 --> 00:41:16,370
the one Anna and Danny
took part in -

694
00:41:16,370 --> 00:41:18,930
and now they've got the results.

695
00:41:18,930 --> 00:41:20,450
Hiya, Anna.

696
00:41:20,450 --> 00:41:22,330
Hello.

697
00:41:22,330 --> 00:41:24,290
Hey. Hi, good evening.

698
00:41:24,290 --> 00:41:30,730
So, should we cut to the chase
and tell you what the results are?

699
00:41:30,730 --> 00:41:35,050
Basically,
you both have antibody responses.

700
00:41:35,050 --> 00:41:36,130
Excellent.

701
00:41:36,130 --> 00:41:39,330
However, the size of the responses
was very different,

702
00:41:39,330 --> 00:41:44,210
and Danny's antibody
levels are about 15 -

703
00:41:44,210 --> 00:41:48,610
a bit more than 15 - times higher
than yours, Anna.

704
00:41:48,610 --> 00:41:51,410
And then the T-cell response is
really, again,

705
00:41:51,410 --> 00:41:54,130
the same sort of pattern, so...

706
00:41:54,130 --> 00:41:58,130
And we know that females
make stronger responses,

707
00:41:58,130 --> 00:42:01,650
innate immune responses to viruses
and vaccines.

708
00:42:01,650 --> 00:42:06,410
If that innate immune response can
block or deal with

709
00:42:06,410 --> 00:42:10,930
most of the virus, then the adaptive
immune response has much less

710
00:42:10,930 --> 00:42:14,770
work to do to
to clear out the rest of it.

711
00:42:14,770 --> 00:42:18,610
Her first line of defence is much
stronger than, let's say,

712
00:42:18,610 --> 00:42:20,450
my first line of defence.

713
00:42:20,450 --> 00:42:24,450
So it broke down my first line
defence, got into me, which is

714
00:42:24,450 --> 00:42:26,850
then why I had a lot
more of the effect

715
00:42:26,850 --> 00:42:29,490
and a lot more, I guess,
now, of antibodies,

716
00:42:29,490 --> 00:42:34,370
where Anna was able to deflect it
and still get some of it through,

717
00:42:34,370 --> 00:42:37,130
and I guess built up
her immunity as well.

718
00:42:37,130 --> 00:42:40,210
I think that's a good summary of it.

719
00:42:40,210 --> 00:42:44,050
If we could understand why Anna's
first line of defence is

720
00:42:44,050 --> 00:42:48,010
so strong, that information could be
used to help someone like Danny

721
00:42:48,010 --> 00:42:51,570
and perhaps prevent him
ending up in hospital or worse.

722
00:42:51,570 --> 00:42:55,970
This could have massive implications
for prevention through vaccines

723
00:42:55,970 --> 00:42:59,490
and for treatment that, together,
could save many lives.

724
00:42:59,490 --> 00:43:03,890
The more information we have,
the more sex-disaggregated data

725
00:43:03,890 --> 00:43:07,490
we have, the better
it will be for both sexes

726
00:43:07,490 --> 00:43:10,010
when it comes to
thinking about health,

727
00:43:10,010 --> 00:43:13,930
when it comes to thinking
about vaccinations, medicines.

728
00:43:13,930 --> 00:43:18,970
Basically, we can't treat each
other as though we are one sex.

729
00:43:21,090 --> 00:43:24,810
It's taken something as awful
as a global pandemic for us

730
00:43:24,810 --> 00:43:27,170
to finally start seeing this.

731
00:43:27,170 --> 00:43:30,330
Many individuals in the scientific
community

732
00:43:30,330 --> 00:43:32,170
have been pushing for this

733
00:43:32,170 --> 00:43:36,410
and it feels as though that they
are slowly starting to be heard.

734
00:43:41,330 --> 00:43:44,490
As are Emma and Janet
and the thousands of families

735
00:43:44,490 --> 00:43:47,290
affected by the drug
sodium valproate.

736
00:43:47,290 --> 00:43:50,810
A long-awaited review,
led by Baroness Cumberlege,

737
00:43:50,810 --> 00:43:53,730
is aired on national TV.

738
00:43:53,730 --> 00:43:59,170
If this Government and the
health care system ignores our

739
00:43:59,170 --> 00:44:05,770
review and another medication and
medical device damages people to the

740
00:44:05,770 --> 00:44:13,010
extent that we have witnessed, they
will and should not be forgiven.

741
00:44:13,010 --> 00:44:18,770
Sodium valproate is an effective
medication to control epilepsy,

742
00:44:18,770 --> 00:44:25,050
but, even today, this medication
causes harm to unborn children.

743
00:44:31,570 --> 00:44:34,370
Women told us that
when they were pregnant

744
00:44:34,370 --> 00:44:38,130
and controlling their epilepsy
with sodium valproate,

745
00:44:38,130 --> 00:44:44,770
they were never told that the unborn
baby could be seriously damaged.

746
00:44:44,770 --> 00:44:49,770
They didn't know that
the chances are one in two.

747
00:44:49,770 --> 00:44:53,290
One in two damaged babies.

748
00:44:53,290 --> 00:44:55,010
What a tragedy.

749
00:45:01,170 --> 00:45:03,530
It's a vindication that we
were right.

750
00:45:03,530 --> 00:45:09,330
You know, it's been worth every
fight, every tear, every late night,

751
00:45:09,330 --> 00:45:12,930
and to hear that, to see that,
it's been worth every moment.

752
00:45:15,210 --> 00:45:17,050
We've got to continue the campaign

753
00:45:17,050 --> 00:45:19,770
because children's lives depend on
this now.

754
00:45:21,170 --> 00:45:26,890
The aim for us now, as a family,
is to make sure that no families

755
00:45:26,890 --> 00:45:31,290
have to go through all this again -
that women get an informed choice,

756
00:45:31,290 --> 00:45:33,890
that they know the risks, the full
risks,

757
00:45:33,890 --> 00:45:37,370
and then, obviously we want
care plans for our children.

758
00:45:38,810 --> 00:45:40,370
We can't be around forever.

759
00:45:55,130 --> 00:45:57,490
What's become really clear to me

760
00:45:57,490 --> 00:46:00,970
is that there is value in studying
sex differences.

761
00:46:00,970 --> 00:46:03,770
The key to protecting us equally

762
00:46:03,770 --> 00:46:08,090
could, in fact, be found in treating
us differently.

763
00:46:08,090 --> 00:46:09,930
As doctors, we're gatekeepers.

764
00:46:09,930 --> 00:46:12,690
We must be aware of our biases.

765
00:46:12,690 --> 00:46:16,330
We must also be aware that every
decision we make

766
00:46:16,330 --> 00:46:18,610
affects people's lives.

767
00:46:18,610 --> 00:46:21,170
So, does sex really matter?

768
00:46:22,250 --> 00:46:23,730
Definitely.

769
00:46:37,010 --> 00:46:39,970
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