Tag Archives: Kidney

A vision of kiwi kidneys

Sick of writing boring text reports.  Take a leaf out of Christchurch nephrologist Dr Suetonia Palmer’s (@SuetoniaPalmer) book and make a visual abstract report.  Here are two she has created recently based on data collected about organ donation and end stage renal failure by ANZDATA (@ANZDATARegistry). Enjoy.

Suetonia C-18RfJXUAApRcU

Suetonia C-16lBZXsAERoeM

ps. The featured image is of the Kidney Brothers.  Check out the great educational resources at The OrganWiseGuys.

Cheesecake files: A little something for World Kidney Day

Today is World Kidney Day, so I shall let you in on a little secret. There is a new tool for predicting if a transplant is going to be problematic to get working properly.

Nephrologist call a transplant a “graft” and when the new kidney is not really filtering as well as hoped after a week they call it “Delayed Graft Function.”  Rather than waiting a week, the nephrologist would like to know in the first few hours after the transplant if the new kidney is going to be one of these “problematic” transplants or not.  A lot of money has been spent on developing some fancy new biomarkers (urinary) and they may well have their place.  At this stage none are terribly good at predicting delayed graft function.

A while ago I helped develop a new tool – simply the ratio of  a measurement of the rate at which a particular substance is being peed out of the body  to an estimate how much the body is is producing in the first place.  If the ratio is 1 then the kidney is in a steady state. If not, then either the kidneys are not performing well (ie not keeping up with the production), or they have improved enough after a problem and are getting rid of the “excess” of the substance from the body.  This ratio is simple and easy to calculate and doesn’t require extra expense or specialist equipment.

A few months ago, I persuaded a colleague in Australia to check if this ratio could be used soon after transplant to predict delayed graft function. As it turns out in the small study we ran that it can, and that it adds value to a risk prediction model based on the normal stuff nephrologists measure! I’m quite chuffed about this.  Sometimes, the simple works.  Maybe something will become of it and ultimately some transplants will work better and others will not fail.  Anyway, it’s nice to bring a measure of hope on World Kidney Day.

This was published a couple of weeks ago in the journal Nephron.

 

Cheesecake files: Just how deadly is it?

Everyone said it did, but how did they know and by how much?  Statements like

“The development of AKI [Acute Kidney Injury] after CPB [Cardiopulmonary Bypass Surgery] is associated with a significant increase in infectious complications, an increase in length of hospital stay, and greater mortality.” (Kumar & Suneja, Anaesthesiology 2011 14(4):964)

are common place in the acute kidney injury literature.  When I started to look at the references for such statements I realised that they were all to individual, normally single centre, studies and that the estimates of the increased risk associated with AKI after CPB varied considerably.  Furthermore, the way AKI is defined in these studies is quite varied. This lead to two questions?

  1. Just how deadly is getting AKI after CPB?
  2. Does it matter how we define AKI in this case?

These questions are important as the answer to them helps a surgeon and patient to better assess the risk associated with choosing to have cardiopulmonary bypass surgery and what the importance is in monitoring kidney function after such a surgery.  To answer these questions required a meta-analysis the results of which I have just published (a.k.a earned a cheesecake).  A meta-analysis involves systematically searching through the literature, a sentence which takes seconds to write but months to serve, for all articles reporting an association between AKI and mortality after CPB.  Then there is learning how to put all the, sometimes disparate, data together (I had to learn a lot of R for this one) and to report on it.  As this was my first meta-analysis, I was fortunate to have the assistance of two highly competent scientists & nephrologists with meta-analysis experience, namely Dr’s Matt James of Calgary, and Suetonia Palmer of my own department in the University of Otago Christchurch.

So – what did we find?

  1. If you get AKI after CPB you about 4 time more likely to die compared to if you do not get AKI after CPB even after accounting for things like age, diabetes, and other risk factors.
  2. Somewhere between 37 and 118 lives per 10,000 CPB operations could be saved if we could find a way to eliminate AKI.
  3. How AKI was measured did not make any difference to the results.
  4. AKI after CPB was also associated with increased risk of stroke.
Figure 1 from Pickering et al, AJKD 2014

A teaser of a figure from Pickering et al, AJKD 2014

Pickering, J. W., James, M. T., & Palmer, S. C. (2014). Acute Kidney Injury and Prognosis after Cardiopulmonary Bypass: A Meta-analysis of Cohort Studies. American Journal of Kidney Diseases : the Official Journal of the National Kidney Foundation. doi:10.1053/j.ajkd.2014.09.008

ps. Sorry about the paywall folks, but as I’ve said before, if we want to put this data in front of the people it is most relevant to we haven’t the budget to always make them Open Access.

 

Cheesecake files: A stadium full

As we’ve been enjoying the World Cup and the Commonwealth Games my latest cheesecake appeared in print online. The topic once more is Kidney Attack biomarkers – those pesky little proteins in the urine that appear when your kidney is injured.  This time I have been getting stuck into some math (sorry) to try and understand what it is that affects when these biomarkers appear in the urine after injury.  I call this a biomarker time-course.  A “Pee Profile” may be a better term but it would never get past the editor.  What I care about is whether the type of biomarker and/or extent of injury, affects the pee profiles.

There are three basic types of biomarkers.  First are those that are filtered from the blood by the two million odd filters in the kidney.  Often they are then reabsorbed back into the blood in the little tubules where the pee is produced – that is, they don’t appear in the urine.  Think of it like a stadium with many entrances.  People (biomarkers) come in and sit down (are reabsorbed).  If, though, a section of the stadium has been fenced off because of broken seating from the previous game (the injury), then some of those entering the stadium may end up exiting it again (the pee biomarkers).  The numbers being reabsorbed and exiting will also depend on whether all the entrances are open – if some are closed then this will have a flow on affect on the rate of people leaving the stadium.

The second are preformed biomarkers.  If we change the analogy slightly, imagine these as people already in the stadium (if the analogy was accurate they would have been born there!).  If some terrible injury happens (like the 4th, 5th, 6th and 7th goals of a now famous football match) some of those people would get up and exit quickly.  The overall rate of exit would reflect on the extent of the injury.

The third, are induced biomarkers.  These are ones that don’t already exist, but are produced in response to an “injury.”  Instead of being biomarkers, let us think of the spectators as produces of these biomarkers and let noise be the biomarker.  There is some background noise of course, but when an “injury” (goal, gold medal performance etc) occurs there is a sudden increase in noise which slowly dies down.  Depending on the team and the number of supporters this will be softer or loader and will carry on for shorter or longer periods (Goooooooooooaaaaaaaaaaaa……lllllllllllll).

The upshot of it all were many coloured graphs and a step towards understanding how we may better make use of the various types of novel biomarkers of kidney injury that have been recently discovered.

PlosOneFigs

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Pickering, J. W., & Endre, Z. H. (2014). Acute kidney injury urinary biomarker time-courses. PloS One. doi:10.1371/journal.pone.0101288

 

 

Cheesecake files: Of bathtubs and kidneys

Sitting in the bathtub you notice that there is a slow leak around the plug.  You adjust the taps to maintain a flow of water that exactly counteracts the loss due to the leak; the water level stays constant.  This is called a steady state and the same thing happens with out kidneys and the molecule used to assess their function.  Our bodies generate creatinine at a constant rate which finds its way into the blood.  Under normal circumstances our kidneys excrete that creatinine into the urine at the same constant

rate.  The creatinine concentration in the blood, therefore, stays constant.  When our kidneys get injured (as they very often do in hospitalised patients) this is like plugging the leak.  Just as the water level in the bathtub would rise slowly – undetectable at first – so too does the creatinine concentration rise slowly.  It normally takes a couple of days to be noticed.  Most of my work has been about trying to detect this injury to the kidney early.  However, if the kidneys start to recover then excess creatinine is only slowly cleared from the blood by the kidney – a process that similarly can take a day or two before it is detected.  Just as not knowing if the kidneys have been harmed makes treatment and drug dosing difficult for the nephrologists and intensivists, so too is not knowing if they have recovered.  My latest publication (aka a cheesecake file) that has appeared in press presents a simple tool for the physicians to try and determine if kidney function has recovered after having been compromised.

This particular piece of work began when a St Louis Nephrologists (a kidney doc), Dr John Mellas, contacted me to say that although a manuscript of his had been rejected by reviewers, he thought there was merit and could I help him (he found me through a search of the literature).  I confessed to being one of the reviewers who had rejected the manuscript!  Fortunately, John was forgiving.  His problem was that he was called in to the intensive care unit to look at a patient with high blood creatinine concentration.  Should he put the patient on dialysis or should he wait?  If he knew if the kidney was already recovering, then he would be less likely to put on dialysis. We talked about the issue for a while and eventually settled on a possible tool which we could test by looking at the behaviour of creatinine over time in abut 500 patients in the ICU.  The tool is quite simple.  It is the ratio of the creatinine that is excreted to the creatinine that is generated.  If more creatinine is being generated than excreted then probably the kidney function is still below normal, however, if more is excreted than generated then probably the kidney is recovering.  The difficulty is that there is no way to measure in an individual what the creatinine generation is.  We ended up using equations based on age, sex, and weight to estimate creatinine generation.  This is a bit like using an equation which takes into account pipe diameter, mains water pressure, and how many turns of the screw the tap has had to determine the rate of water flow.  Creatinine excretion, though, can be easily measured by recording total urine production over several hours (we suggest 4h) and multiplying this by the concentration of creatinine in the urine.

We discovered that by using the ratio between estimated creatinine generation and creatinine excretion we were able to tell in most patients if the kidney was recovering or not.  My hope is that physicians will test this out for themselves.  The good thing is that it requires only minimal additional measurements (and costs) beyond what are already made in ICUs, yet may save many from expensive and invasive dialysis.

Pickering, J. W., & Mellas, J. (2014). A Simple Method to Detect Recovery of Glomerular Filtration Rate following Acute Kidney Injury. BioMed Research International, 2014. doi:10.1155/2014/542069

 

A day to celebrate

If it weren’t for your kidneys where would you be?

You’d be in the hospital or infirmary,

If you didn’t have two functioning kidneys.

(with apologies to John Clarke aka Fred Dagg)

Happy World Kidney Day everyone.

This blog started off life as $100 Dialysis because I believe that if we can make a computer for $100 then surely we can do the same for dialysis!  Dialysis is a life saver, yet its cost kills as so many can not afford the treatment.

There’s some good news in the dialysis world.

Schematics of the zeolite nanonfibres and how they may look in practice

Schematics of the zeolite nanonfibres and how they may look in practice

Just last week the MANA – International Centre for Materials NanoArchitectionics announced  they have developed a method to remove waste from the blood using an easy-to-produce nanofibre mesh.  Importantly, they claim it is cheap to produce.  Details were published in Biomaterials Science (free access).  Despite the photograph, there have been no human studies yet, but I expect that won’t be too long in the future.

Dr Victor Gura and the Wearable Artificial Kidney (WAK)

Dr Victor Gura and the Wearable Artificial Kidney (WAK)

In the meantime, the FDA gave approval last month for human trials of a wearable dialysis device produced by Blood Purification Technologies Inc (the WAK).

New Zealand, and Dunedin and Christchurch in particular, lead the way in Home Dialysis.  One Dunedin tradesman has even taken Home Dialysis a step further and turned it into portable dialysis by dialysing in his work van during his lunch hour. Of course, those needing a holiday may go on the road in specially equipped camper vans (http://www.kidneys.co.nz/Kidney-Disease/Holiday-Dialysis/).

Cause for celebration in the New Zealand kidney community was the gong (Office of the New Zealand Order of Merit) given to Adrian Buttimore who for 40 years managed Christchurch’s dialysis service.

These are just a few pieces of good news as doctors and scientists work around the world to improve the lives of dialysis patients.

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Hot off the Press… I couldn’t resist adding this…. Pee, the answer to the world’s energy problems. http://www.bbc.com/future/story/20140312-is-pee-power-really-possible

 

Cheesecake files: Too little pee

This week’s post is really about the coloured stuff & why too little of it is dangerous.  Note, I say coloured stuff because it aint just yellow – check out this herald article if you don’t believe me (or just admire this beautiful photo).

 A rainbow of urine from a hospital lab. Credit:  laboratory scientist Heather West.

A rainbow of urine from a hospital lab.
Credit: laboratory scientist Heather West.

Story time

A long time ago, when Greeks wore togas, and not because they couldn’t afford shirts, a chap named Galen* noted that if you didn’t pee you’re in big trouble.  It took 1800 more years before the nephrologists and critical care physicians got together to try and decide just how much pee was too little.  This was at some exotic location in 2003 where these medics sat around for a few days talking and drinking (I’m guessing at the latter, but I have good reason to believe…) until they came up with the first consensus definition for Kidney Attack (then called Acute Renal Failure, now called Acute Kidney Injury)1.  It was a brilliant start and has revolutionised our understanding of just how prevalent Kidney Attack is.  It was, though, a consensus rather than strictly evidence based (that is not to say people didn’t have some evidence for their opinions, but the evidence was not based on systematic scientific discovery).  Since then various research has built up the evidence for or against the definitions they came up with (including some of mine which pointed out a mathematical error2 and the failings of a recommendation of what to do when you don’t have information about the patient before they enter hospital3).  One way they came up with to define Kidney Attack was to define it as too little pee.  Too little pee was defined as a urine flow rate of less than half a millilitre per kiliogram of body weight per hour over six hours (< 0.5ml/kg/h over 6h).  Our groups latest contribution to the literature shows that this is too liberal a definition.

The story of our research is that as part of a PhD program Dr Azrina Md Ralib (an anaesthesist from Malaysia) conduct an audit of pee of all patients entering Christchurch’s ICU for a year.  She did an absolutely fantastic job because this meant collecting information on how much every patient peed for every hour during the first 48 hours as well as lots of demographic data etc etc etc. Probably 60-80,000 data points in all!  She then began to analyse the data.  We decided to compare the urine output data against  meaningful clinical outcomes – namely death or need for emergency dialysis.  We discovered that if patients had a flow rate of between 0.3 to 0.5 ml/kg/h for six hours it made no difference to the rates of death or dialysis compared to those with a flow rate greater than 0.5.  Less than 0.3, though, was associated with greater mortality (see figure).  For the clinician this means they can relax a little if the urine output is at 0.4 ml/kg/h.  Importantly, they may not give as much fluid to patients. Given that in recent times a phenomenon called “fluid overload” has been associated with poor outcomes, this is good news.

The full paper can be read for free here.

Proportion of mortality or dialysis in each group. Error bars represent 95% confidence intervals.From Ralib et al Crit Care 2012.

Proportion of mortality or dialysis in each group. Error bars represent 95% confidence intervals.From Ralib et al Crit Care 2013.

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*Galen 131-201 CE.  He came up with one of the best quotes ever: “All who drink of this remedy recover in a short time, except those whom it does not help, who all die.”

1.     Bellomo R, Ronco C, Kellum JA, Mehta RL, Palevsky PM, Acute Dialysis Quality Initiative workgroup. Acute renal failure – definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit Care 2004;8(4):R204–12.

2.     Pickering JW, Endre ZH. GFR shot by RIFLE: errors in staging acute kidney injury. Lancet 2009;373(9672):1318–9.

3.     Pickering JW, Endre ZH. Back-calculating baseline creatinine with MDRD misclassifies acute kidney injury in the intensive care unit. Clin J Am Soc Nephro 2010;5(7):1165–73.