HIGH BLOOD PRESSURE: IT’S A SYMPTOM, NOT A DISEASE, STUPID!

[Guest guest]

Reactions to chemicals can also make your blood pressure go up.

CARDIOVASCULAR EFFECTS: by Dr Ziem

http://chemicalinjury.net/MedicalCare.htm

blessings

Shan

HIGH BLOOD PRESSURE: IT’S A SYMPTOM,

NOT A DISEASE, STUPID!

http://www.thincs.org/Malcolm.htm#hypertens1

by Malcolm Kendrick MD

 

Let’s suppose that one day you went to the doctor and she decided to take

your temperature, just to see what it was. To your surprise it was two degrees

higher than normal. As we all know, a high temperature is associated with a

higher than normal level of mortality, so the doctor decided to use a drug to

get

your temperature down, along with advice to wear less clothes and take cold

baths.

 

Time passes and you have been on this drug for five years. The baths and

chilly walks are getting to be a bit of a pain. On the bright side, at least the

temperature is back to normal.

 

I think you would agree that such a scenario is, quite frankly, nuts.

 

Yet, every day, thousands of people are found to have high blood pressure,

and put on blood pressure lowering drugs on pretty much the same basis. The

logic, after all, is the same.

 

1. People with high blood pressure are more likely to die from CHD

 

2. Therefore a high blood pressure causes CHD

 

3. Therefore if you lower the blood pressure you will reduce the rate of

CHD

 

4. So, take a blood pressure lowering drug for the rest of your life

 

I suppose that most people believe that it must have been proven by now that

blood pressure lowering does reduce the rate of CHD, rendering the example of

a high temperature somewhat pointless. Well, I am going to quote you quite a

long passage from the European Heart Journal, issue 20, October 2000. Please

read it carefully, for it is actually quite stunning.

 

‘It is widely believed that randomised trials have proved that

lowering blood pressure is beneficial. Actually, that is not true. All

antihypertensive drugs have profound effects on the cardiovascular system, aside

from their

haemodynamic (blood pressure lowering) effect. How much, if any, of the

observed risk reduction can be ascribed to the reduction in pressure and how

much

to the direct action of the drug on the cardiovascular system? Motivated by the

belief in the linear relationship of risk to pressure, many automatically

attribute the risk reduction to the pressure reduction, ignoring the direct

action of the drugs on the target outcomes. But results of a multitude of

clinical

trials make it clear that such a simplistic view cannot be true. In fact,

evidence is mounting (especially from the newer trials) that it is the direct

effects that are producing most, if not all, or the benefit and that the

accompanying blood pressure reduction may be just an inconsequential side

effect.’ Port

S et al.

 

In short, there is no evidence whatsoever that lowering blood pressure has

any effect on CHD. As they authors of the paper further state:

 

‘ALLHAT (A major blood pressure lowering trial) showed a dramatic difference

between alpha blockers and diuretics, with essentially no difference in blood

pressure between the treatment and control groups.’

 

Quelle surprise? Not really, after all, the underlying hypothesis that blood

pressure causes CHD was always nonsense. After all, how could a high blood

pressure make atherosclerotic plaques form? Well, you can create a convoluted

argument involving endothelial damage, but you would struggle to create a clear

cut case.

 

On the other hand, it is very much more simple to see how an atherosclerotic

plaque, by narrowing an artery supplying blood to a vital organ, can trigger

the heart to pump harder, thus overcoming the narrowing in the artery by

increasing the blood pressure.

 

Perhaps it is time for a rewind. What is a high blood pressure, and what

could cause it? In about ten per cent of cases there is a clearly established

cause for high blood pressure. Conditions such as renal artery stenosis, or

hyperthyroidism, or kidney problems. If these are treated, the blood pressure

drops

back to normal.

 

However, in about ninety per cent of cases when the blood pressure is raised,

no cause can be found. At which point the medical profession, rather than

using the somewhat pathetic sounding term ‘Raised blood pressure of no known

cause,’ decided to rename the condition Essential Hypertension. You’ve got

to

admit, this sounds a great deal more scientific and ‘disease like.’ In fact

it

sounds so impressive that Essential Hypertension has managed the transformation

from ‘symptomless medical sign’ to a real disease, one that needs to be

treated.

 

Let’s examine the logic in use here. One day, for no known reason, your body

decides that the blood pressure needs to be raised. So your heart pumps

harder, or your arteries decide to contract, or both. This has the desired

effect of

raising the blood pressure to a point where it can cause damage. It can lead

to strokes, heart failure, kidney failure, etc.

 

Undeterred by the damage that this raised blood pressure is causing, the body

continues for day after day, month after month, year after year, to keep the

pressure up. Eventually your heart can’t carry on any more, so it starts to

pack in, you develop heart failure, and within about five years you are dead.

 

There is just one teensy little thing missing from this model. A cause. Why

does the pressure suddenly rise? One thing is for sure, the body does nothing

without a cause, especially if the effect is to damage health. So we need to

ask a deeper level question. What could cause the blood pressure to rise?

 

In order to understand this, you need only to the grasp the exceedingly

simple concept that the pressure of liquid flowing through a pipe is a function

of

two variables. The first variable is the rate of flow of the liquid; the

second is the diameter of the pipe. If you want to increase the pressure you

must

pump more fluid, or narrow the pipe.

 

Therefore, if your blood pressure goes up, for no known reason, one of two

basic things is happening.

 

1. The heart is pumping harder

 

2. The diameter of the arteries has narrowed (causing the heart to pump

harder to keep the blood flow the same)

 

Things that make your heart pump harder would include: anxiety, exercise,

stimulants e.g. coffee. Things that narrow your arteries would be……? Dum de

dum,

let me think. Oh yes. An atherosclerotic plaque (the underlying cause of CHD)

would narrow an artery. Therefore, a probable cause of high blood pressure is

the presence of CHD.

 

Thus, ergo etc. a high blood pressure is not a cause of CHD. Instead CHD is a

cause of high blood pressure. So yet again gentle reader, as with raised

cholesterol levels and CHD, we see another rather grisly example of the medical

profession grasping the wrong end of the stick and desperately trying to cure a

disease (CHD) by sweeping a symptom of that disease (high blood pressure)

under the carpet. No big surprise, it doesn’t actually work.

 

Does this all seem incredibly basic? It should, because it is. So, whilst

blood pressure lowering may have some effect on preventing strokes, heart

failure

and other pressure related problems, it has no effect on reducing death from

heart attacks. After all, how could it?

 

 

Some of you may have seen research reported in the New Scientist magazine

which established quite clearly that most scientific researchers don’t bother

to

read the full papers that they use for references. In fact, most of them just

copy and paste the list of references used in other papers.

 

This may seem a somewhat arcane issue, removed at two steps from real life. I

can sense a collective ‘so what?’ resonating round the world on this issue.

But please pay attention, because this fact is VITALLY IMPORTANT! And it

explains much about the treatment paradigm for high blood pressure.

 

In medical science, many measurements are imprecise. A blood pressure taken

at ten in the morning may have changed five minutes later. The doctor may have

put the blood pressure cuff on in a slightly different way, whatever. So, when

you start drawing a graph of blood pressure measurements taken over time vs.

the rate of death, in different groups of people, it does not have precise

cut-off points. It may look more like someone has fired blunderbuss at a piece

of

graph paper.

 

[ Graph here of Blood Pressure ]

 

However, if you are really clever and understand mathematics and calculus,

and suchlike, you can draw a perfect line through that mass of dots. This can be

called a ‘linear logistic model.’ (My line is just a random guess by the

way)

 

[ Graph here ]

 

However, to quote the European Heart Journal: ‘Before one can have confidence

that the linearity correctly reflects the behaviour of the data, and is not

just an artefact of the model, it is necessary to carefully examine the data in

relation to the proposed model.’ In plain English, stop guessing. Although

guessing does look a lot more impressive when you use terms such as Cox model

and double-tailed chi-squared, etc. which no one understands.

 

So, what does this all have to do with the price of beans?

 

I have two strands to my discussion so far.

Strand one: most researchers never bother to read the papers they quote; at

most they manage to read the abstract.

Stand two: statistical models used to look at blood pressure vs. mortality

are all based on the supposition that ‘the relation of blood pressure to risk

of

death is continuous graded and strong, and there is no evidence of a

threshold.’

 

Now, where did this supposition first come from? Our old friend Framingham,

the world’s longest and most detailed study of the relationship between

various

‘risk factors’ and death from heart disease. Researchers looking at the

Framingham data started the ‘linear and continuous’ ball rolling, and, ever

since, everyone has decided to use the same methodology. A statistical

methodology

which implies that the lower the blood pressure the better, and there is no

lower limit.

 

No one questions this methodology; in fact it has been quoted in so many

papers over the years that it would appear to have been proven beyond the shadow

of a doubt. But of course, the reason why it is now quoted so often is that

paper after paper has quoted from other papers that have all shown this linear

regressive model to be true. A process of error reinforcing error.

 

To give a more concrete example of how this happens. I write a paper which

states that ‘the relation of blood pressure to risk of death is continuous

graded and strong.’ Someone else comes along and quotes that paper, without

bothering to look at the methodology or results. So now I have two papers making

the

same statement.

 

Then, along comes researcher B, who is looking for papers on blood pressure

and mortality. He sees two papers with the same self-reinforcing statement on

it, and quotes them. Now I have three papers making the same statement. How

long before there are one hundred, two hundred, a thousand papers?

 

You think this number may be an exaggeration, but Simkin and Roychowdury (who

looked at the issue of misreporting) found that mis-citations can occur many

thousands of times. To quote the New Scientist article again:

 

‘To find out how common this (misreporting) is, Simkin and Roychowdhury

looked at citation data for a famous 1973 paper on the structure of

two-dimensional

crystals. They found it had been cited in other papers 4300 times.’

 

And the errors this leads to are not specific to two-dimensional crystals:

 

‘The problem is not specific to this paper, the researchers say. Similar

patterns of errors cropped up in a dozen other high-profile papers they studied.

The trouble is that researchers trust other scientists to repeat the key

message of a paper correctly. This means that when misconceptions take root,

they

spread like weeds.’

 

It should be clear by now, where I am heading.

 

Someone, somewhere, decided that there is a continuous linear relationship

between death and blood pressure. They used a statistical method to establish

this, and ever since everyone has used the same model. So there are now

thousands and thousands of papers out there ‘proving’ this paradigm to be

true. In

fact, if you wrote a paper on the treatment of high blood pressure using another

model it would almost certainly be rejected on the basis that the linear

relationship model was the established, and correct, model, so yours must be

wrong.

 

There is just one teensy, weensy, little problem here. When you actually

decide to look at the data - it disproves the model.

 

‘Shockingly we have found that the Framingham data in no way supported the

current paradigm to which they gave birth. In fact, these data actually

statistically reject the linear model. This fact has major consequences.

Statistical

theory now tells us that the paradigm MUST be false..’ EHJ 2000 21, 1635 -

1638

 

 

I didn’t add the italics or capital letters. The Authors put them in - the

paradigm MUST be false. Normally, in clinical papers, people state things very

calmly, e.g. ‘the data suggests an association between.’ So to see a

statement

such as the paradigm MUST be false is very strong stuff.

 

So what is really being stated here that is so important?

 

I will use an analogy to try to make the point. If you chose to live in the

Himalayas you may find yourself twelve thousand feet above sea level. Most

people can cope with this height, and it has very little impact on your health

or

life expectancy. Go up a few thousand feet and everyone dies. The exact ‘death

zone’ height varies from person to person.

 

The fact that you die at sixteen thousand feet, however, does not mean that

any altitude above sea level is harmful. What it means is that, at a certain

level, your body cannot cope any more and the systems start to break down.

 

Yet, with blood pressure, any rise represents a risk - according to the

linear model. There is no ‘death zone’ no cut-off point. According to this

logic,

even if you have a ‘normal’ blood pressure, it would be better if you could

get it lower. And believe me, papers have been written stating this.

 

But, anyone with half a brain can see that a model with a ‘cut point’ is

much more likely to be correct. Is it really likely that a 5-15mmHg rise in

blood

pressure will cause problems? According to the linear model, the answer is

yes. But, as we have seen, the data doesn’t actually support a linear model,

and

logic would also dictate that at a certain point - which has, in reality,

never been defined - a raised blood pressure creates problems. Below that point

it may be a bit high, but frankly it’s nothing to worry about.

 

What is that point…. I don’t know. But I would guess it is something like a

systolic of 160 - 180. However, the medical profession, with its ever present

desire to squeeze all patients into a little box called ‘normal’ is

inexorably bringing down the level at which treatment is needed. I have seen

calls to

get everyone to a level of 120/70 (the level considered ‘normal’). The WHO

has

set the limit at 130/85. Already in diabetes the recommended level is 120/85.

 

 

Why are they trying to achieve this? On the basis of a model made up years

ago which, due to sloppy research, has become accepted fact. On the basis of a

model which, if you examine it properly, MUST be wrong. Try explaining this to

your local, friendly doctor, you will get the same reaction that I always do.

‘

Don’t talk rubbish, it has been proved that you should lower the blood

pressure as much as possible.’