Monday, February 11, 2013

Winter-meeting in Oslo

The Norwegian Hypertension Society held its bi-annual scientific meeting in Oslo last week. It was a long time in planning. We set the place and date about two years ago. Sent the first announcement in the spring of 2012 and the call for abstracts in September. Then, at the very deadline, the abstracts and registrations start to trickle in. As with all meetings, we pushed the submission-deadline back a week just to allow people without basic planning skills with pressed schedules to join the meeting and present their data. Then, in as little time as possible, all the abstracts have to be formatted into a program, and session-chairs has to be found and matched so that they have an interest but aren't speaking themselves.

Anyway, we got some 17 free communications, varying from experimental physiology to international research politics, but with a heavy focus on epidemiology and clinical research. There were a couple of talks on the recently very hot topic of renal sympathetic denervation for treatment-resistant hypertension (more on that in another post), some interesting sub-group analyses from the LIFE and SCAST studies, and follow-ups on the now 40-year-old Oslo-Ischemia-Study. More of the program at the society home-page.
In addition, we had two invited lectures on statistics in clinical research. The first on how to develop and validate prognostic models by Ingar Holme, and the second on over-adjustment bias in multiple regression models held by Knut Liestøl. It was a useful repetition of the uses and pitfalls of these two very similar kinds of models that require very different study-designs and give very different information in the end. A common problem is that one tries to get etiological information from prognostic research, i.e. treating a risk-factor as a cause for the chosen end-point even though the observational design makes that impossible. The converse is equally common, i.e. trying to infer prognostic information from etiological studies, such as clinical trials, where the highly selected population makes general conclusions very suspect.

All told, it was a very successful meeting, well worth the time both for planning it, and attending.

Sunday, February 10, 2013


The recent popularity of the up-goer five editor (check out the #upgoerfive hash on Twitter) pin-points an important point in writing: It's bloody hard to express a coherent thought in science without any specialised words. And I don't mean jargon or strange abbreviations but words like function, vessel, pressure, kidney and medicine (This point is made much better by the Center for plain language).

However, trying makes for a good bit of fun. The original fun was had by the brilliant Randall Munroe at when he reproduced a technical drawing of the Saturn V rocket with explanations that only included the 1000 most commonly used words. This excluded the use of "saturn" "V" and "rocket", so it was called the Up-goer five. Now, Theo Sanderson has created an editor that tells you when you have used a word that is not among the 1000 most used words. Here is my attempt to explain kidney function and the effect of hypertension induced injury on blood vessel and kidney function.
My job is to understand how the body parts that make piss work, and why they get hurt by the force that the heart makes when it forces the blood around in the body. In the body there are two blood-to-piss-body-parts. They work by making piss out of blood using many small blood-cell-catch-things so that the blood cells stay in the body. Then the blood-to-piss-body-parts take up most of the water again so that the piss becomes strong, and the body can save water. The blood-cell-catch-things use the force-of-the-heart to push water out of the blood. 
However, the smallest of the blood-roads and the blood-cell-catch-things are not strong, and can be hurt by the force-of-the-heart. In the long run this hurts the blood-to-piss-body-parts, and make them stop working. Before they stop working they work less well for a long time. During this time they are easier to hurt in other ways. One important way is when the force-of-the-heart becomes too low, often because of lost blood, and the blood-to-piss-body-parts get too little blood. Too little blood, and too low force-of-the-heart makes it hard to push water out of the blood to make piss. You then get too much piss in your blood which makes you sick. 
At the same time, air is carried by the red blood cells in the blood and used for doing work in the body. Too little blood to the blood-to-piss-body-parts gives them too little air, which they need in order to take back water from the piss. When the force-of-the-heart is low they need to take back even more water than usual to keep more water in the blood and keep the force-of-the-heart normal. This makes the blood-to-piss-body-parts use more air even though less comes to them. Since the cells that make up the blood-to-piss-body-parts need air to live, too little air hurts them and some of them die.

In a blood-to-piss-body-part that has been hurt by too high force-of-the-heart a sick with too low force-of-the-heart hurts more than in a well blood-to-piss-body-part. This means that for each earlier hurt the next hurt will hurt more and lead to blood-to-piss-body-parts that do not work at all faster and faster.

Too high force-of-the-heart hurts the blood-to-piss-body-parts by hurting the blood-roads first. This hurt changes how much blood passes the blood-cell-catch-things, and how much water is taken back to the body from the piss. Doctors can keep the blood-to-piss-body-parts from getting hurt by giving doctor-stuff that makes them work less hard and by keeping the force-of-the-heart normal. When the blood-roads have been hurt a lot it is hard to save the blood-to-piss-body-parts. Is important to keep the force-of-the-blood normal as much as possible.
If you want to read some other examples go to Ten Hundred Words of Science. Lots of fun for everyone.

Saturday, February 02, 2013

Speech impediment - Locale in R under OSX

My R-installation developed a language problem ("L" is a statistical ploglamming language). The startup message, all errors and system messages started appearing in German. I do speak German but it was still quite annoying. This ended with a work-around that I published previously in a post about R-startup scripts. I have finally figured out what causes the error. My Language & Text settings for language were as follows:
  1. British English 
  2. Swedish
  3. Norwegian
  4. Danish
  5. German 
  6. French 
The problem lies in using the British English locale. I use it because I hate when all programs always correct my excellent spelling from Proper English™ to American. R does not have a locale for British English, nor for Swedish, Norwegian or Danish. So, to R, the locale priority list actually looks like this:


    2. German 
    3. French
So, understandably it goes for what it knows. The solution is to extend the list and put a standard English locale high up:
    1. British English
    2. English 
    3. Swedish
    4. Norwegian
    5. Danish
    6. German 
    7. French