I am sitting in a meeting of the Australian and New Zealand society of nephrologists. I want to do them out of a job. Will you help?
Diabetes is the number one risk factor for Chronic Kidney Disease (CKD). High blood pressure is number two.
About 10% of the population has CKD. They are much more likely to die than the rest of us. Some of them will go on to need dialysis or a transplant.
Scared? You should be.
What can you do? Eat well, shut your computer and go for a 30 minute walk. Do the same tomorrow. Take a friend with you, especially if they are overweight and at risk of diabetes themselves. If you are wise, you are already out the door and not reading this, if not…please act soon.
Know someone about to start dialysis? I am sitting in a conference hall and have just heard a fascinating talk by Prof Chris MacIntyre about the danger to other organs for those undertaking dialysis. The stress dialysis puts on the vasculature is the culprit. Myocardial stunning can occur in nearly 2 out of 3 paients each dialysis session . The effect in creases many fold with every extra litre of fluid removed. The death rates are much higher amongst those who exhibit the stunning than those who don’t.
It is not all bad news. Cold dialysis and more frequent dialysis seem to help. Randomised Control Trials are underway to test these interventions. A portable continuous $100 Dialysis machine may not just be cheaper, but may have less side effects!
In the meantime, support from friends and family are all the more important in those few months.
Colleague Dr Suetonia Palmer just won a prestigious L’Oreal for Women in Science award. She’s one of my “go to people” for nephrological type questions (ie all the stuff I don’t know). This award is very well deserved! The press release on scoop gives all the salient details. Just let me add my bit.
What impresses me about Suetonia and her work is her attention to detail and her dedication to dig for the truth. Her work is focussed on systemic reviews with the Cochrane Collaboration. Quite simply, this is about as good as it gets for evidence based medicne. Her mission is to gather evidence from multiple trials for a particular treatment or clinical practice and to analyse that evidence in detail to answer the age old question “Does it really work?” Her focus, of course, is kidney disease. An example is a meta-analysis of Vitamin D supplementation in Chronic Kidney Disease (1). Suetonia and colleagues trawled through data from 76 trials, assessed them for quality, and combined the data. Apparently Vitamin D had been widely used to prevent and treat secondary hyperparathyroidism – a consequence of the failure of the kidney to handle Vitamin D properly. The result was that despite its wide use, the beneficial effects of Vitamin D compounds on patient-level outcomes were unproven. We all want our doctors to use the best available treatment with the least side-effects, and we don’t want unnecessary (or expensive) treatments. Suetonia’s work enables that to happen.
Well done Suetonia.
1. Palmer SC, McGregor DO, Macaskill P, Craig JC, Elder GJ, Strippoli GFM. Meta-analysis: vitamin D compounds in chronic kidney disease. Ann Intern Med 2007;147(12):840–53.
See more of Suetonia’s publications at http://www.otago.ac.nz/christchurch/research/ckrg/ourpeople/index.html.
The Games are over, let the analysis begin.
We’ve had some fun with ranking countries’ performance at the London Olympics according to medals per million (medals per capita) or medals per 100 billion of Gross Domestic Product (see my tables below). As I predicted a few posts back, the medals per capita will be one by a country with very low population and few medals – Grenada is the winner here. It seems obvious when we think about it that a country with a population of just 100,000 (0.1 Million) may end up with a very high medals per million score if they win just 1 or 2 medals (even though that is still a difficult feat). What is not so easy to see is that countries with very high populations have a “limit” for their performance that is very much lower. With just ~900 medals on offer and a population of over 1340 million China’s possible maximum medals per million score is just 0.67 (compared with Grenada’s 9000). It is this breadth of this range of possible values that causes the bias in the ranking system.
I like to visualise data. The two graphs below show the bias for the “Official Rankings” (you know, the ones that rank according to number of golds first, silvers second and bronzes third) and for the medals per capita. The bias is obvious because the points on the graph are not scattered without any discernible pattern all over the graphs. The “Official Rankings” obviously are biased towards countries with greater populations, the Medals per capita is biased towards countries with lesser populations. Obviously, dividing by population does not remove the bias, merely shifts the bias. Note, that the scales on the “y” axis are what we call “log scales”. This enables us to see all the data more easily (ie countries with 100,000 and 1.3 billion can be displayed on one graph). What is not shown on the graph is the 122 countries ranked 80th equal who won no medals at all.
Later this week, once I am happy with my grant writing and get my head around some data I am trying to analyse I shall attempt to put together an equation which will better help us answer the important question of the day – “Which is the greatest olympic nation?”
Top graph: The Official Rankings verse Population (note the log scale).
Bottom graph: The Ranking of number of medals won per million population v population
Have a read of this blog from a medical student – He/She (not sure which) writes well and writes passionately.
Seeing the big picture.
As expected, a country with a small population has grabbed the top medal position when Grenada (population, 104,000) grabbed a gold. WIth a medals per million score of 9.6 they are only likely to be beaten by a country with even smaller population. Meanwhile, Jamaica has moved into 5th position with 5 medals, all in athletics. If this was health stats, then these two situations would be examples of “outliers.” Worthy of study in and of themselves, but having a distorting influence on the overall population statistics. Also of interest is that perhaps Great Britain is reaching a plateau, meanwhile China continues to fall as sports they are not traditionally strong in dominate the second week of competition.
The weekend success of a New Zealand rowing pair put them in gold medal position on the medals per capita table. They have now sneaked ahead of Slovenia. Denmark are in bronze medal position with Australia solid in fourth. The big mover over the weekend was Great britain moving from 17th at the end of day 6 to 11th at the end of day 9.