Tag Archives: AKI

Hot oil baths and other things to do on World Kidney Day 2015

“In ancient times the Persian philosopher Avicenna [Ibn Sina] noted that urine may be retained in crisis of fever (s393) and prescribed hot oil baths (s413)(1). Unfortunately, apart from the supportive therapy of dialysis, there has been little progress since in the treatment of acute kidney injury (AKI).”(2)

Given that getting AKI at least doubles your chance of dying in hospital “no progress” is a major health issue.

Today is World Kidney Day and I get to post quite possibly the first blog post in the world on this day. I believe Avicenna would be thrilled with the attention paid to the organ which delivers urine. He may not be so thrilled that hot oil baths have been abandoned. Of course there is the obvious safety issues of scalding and drowning. Also, as Herod the Great found out, syncope (sudden loss of consciousness) is also a possible side effect (probably just because the heat constricted his blood flow [vasoconstriction] causing too little oxygen to reach his brain [cerebral anoxaemia].(3) Nevertheless, I think Avicenna is the type of person who would have welcomed a randomised controlled trial of hot oil baths verse today’s standard treatment.


The statue of Avicenna (Ibd Sina) to be found in Hamaden, Iran. http://www.panoramio.com/photo/91467137

If you don’t fancy a hot oil bath this World Kidney Day, then there are other things to do to minimise the possibility of Acute Kidney Injury. Have you got high blood pressure, diabetes or Chronic Kidney Disease? Be warned, ~10% of the adult population have Chronic Kidney Disease, many of whom are not aware, and many more are at risk of developing it. All add to your risk of multiple illnesses any one of which can trigger acute kidney injury. If you happen to have a heart attack or sepsis (very serious infection) you are more likely to get AKI and more likely to die because of these underlying conditions.

So, on the assumption that readers of this blog are smarter than the average bear, I shall give you some sound advice – for the sake of yourselves and your family LOOK AFTER YOURSELF (yes, I’m shouting and therefore sinning against the internet protocol police – but this is important). Cut the sugar intake, quit smoking, take a walk around the block. It ain’t rocket science (one of the simpler sciences that involves cylinders with fins and lots of explosives) – it’s easier than that.

Former World Kidney Day posts

2014 A day to celebrate https://100dialysis.wordpress.com/2014/03/13/a-day-to-celebrate/

2013 Happy WKD https://100dialysis.wordpress.com/2013/03/14/happy-wkd/

2012 I am a pee scientist https://100dialysis.wordpress.com/2012/03/07/i-am-a-pee-scientist/


  1. Avicenna: The Canon of Medicine [Internet]. 2nd ed. New Yourk: AMS Press; 1973. Available from: http://archive.org/stream/AvicennasCanonOfMedicine/9670940-Canon-of-Medicine_djvu.txt
  2. Pickering JW, Endre ZH: The definition and detection of acute kidney injury. Journal of Renal Injury Prevention 2014; 3:19–23 http://www.journalrip.com/Archive/3/1
  3. Retief FP, Cilliers JFG: Illnesses of Herod the Great. S Afr Med J 2003; 93:300–303

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: 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


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.


*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.

H7N9 kills and attacks kidneys

27% of patients with H7N9 Influenza A died.  This is the finding of a report just released  in the New England Journal of Medicine is a study of 111 of the 132 confirmed cases of H7N9 Influenza A*.

Acute Kidney Injury or “Kidney Attack” was amongst the most common complications.

Of the 111 patients we evaluated, 85 (76.6%) were admitted to an intensive care unit (ICU); of these patients, 54 were directly admitted to the ICU, and 31 were admitted during hospitalization. Moderate-to-severe ARDS [Acute Respiratory Disease Syndrome] was the most common complication (in 79 patients), followed by shock (in 29 patients), acute kidney injury (in 18 patients), and rhabdomyolysis (in 11 patients).

In an analysis in the Appendix to the paper a comparison was made between the 30 patients who had died and 49 who had recovered (others were still in hospital).  100% of those who died had had ARDS compared with 40% of those who recovered.  One third of those who died had Acute Kidney Injury compared with 4% of those who recovered.  From a statistical perspective these numbers illustrate a real difference with a low probability (~ 1-2 out of 1000) of observing such a difference by chance.**

Note, all patients had been in close contact withe live chickens or pigeons within 2 weeks of hospitalisaton.

NEJM 23 May 2013

NEJM 23 May 2013

* Clinical Findings in 111 Cases of Influenza A (H7N9) Virus Infection

Hai-Nv Gao, M.D., Hong-Zhou Lu, M.D., Ph.D., Bin Cao, M.D., Bin Du, M.D., Hong Shang, M.D., Jian-He Gan, M.D., Shui-Hua Lu, M.D., Yi-Da Yang, M.D., Qiang Fang, M.D., Yin-Zhong Shen, M.D., Xiu-Ming Xi, M.D., Qin Gu, M.D., Xian-Mei Zhou, M.D., Hong-Ping Qu, M.D., Zheng Yan, M.D., Fang-Ming Li, M.D., Wei Zhao, M.D., Zhan-Cheng Gao, M.D., Guang-Fa Wang, M.D., Ling-Xiang Ruan, M.D., Wei-Hong Wang, M.D., Jun Ye, M.D., Hui-Fang Cao, M.D., Xing-Wang Li, M.D., Wen-Hong Zhang, M.D., Xu-Chen Fang, M.D., Jian He, M.D., Wei-Feng Liang, M.D., Juan Xie, M.D., Mei Zeng, M.D., Xian-Zheng Wu, M.D., Jun Li, M.D., Qi Xia, M.D., Zhao-Chen Jin, M.D., Qi Chen, M.D., Chao Tang, M.D., Zhi-Yong Zhang, M.D., Bao-Min Hou, M.D., Zhi-Xian Feng, M.D., Ji-Fang Sheng, M.D., Nan-Shan Zhong, M.D., and Lan-Juan Li, M.D.New England Journal of Medicine Online May 22, 2013 DOI: 10.1056/NEJMoa1305584

** something called a multivariate analysis was attempted which trys to take into account correlations between diseases to see which diseases are the major factors.  However, with “only” 30 deaths such an analysis is very limited and I do not think of value in this situation.

The Face of Kidney Attack

The Face of Acute Kidney Injury.  (Published with permission).

The Face of Acute Kidney Injury. (Published with permission).

It ain’t pretty, it’s Acute Kidney Injury.  This case was probably brought on by leptospirosis.  This is the face of a well known New Zealander.  Do you recognise him?  He’s kindly lent his name to my research on AKI.  I will reveal that name in future posts as I tell his remarkable story.

Diabetes in NZ – new scary data

If this doesn’t scare you, you are an Ostrich.  Otago University researcher Dr Kirsten Coppell has released new data on the prevalence of diabetes in New Zealand.  See here for the press release.

Basic data:

  • 7% of New Zealanders over the age of 15 have diabetes
  • 18.6% have pre-diabetes which typically leads to Type II diabetes (therefore the prevalence is likely to go higher than 7%).
  • The pre-diabetes prevalence increases with age – it was 45% in 55-64 year age group.

For those interested in reading the research, it can be found in the NZ Medical Journal.  NZMJ 1 March 2013, Vol 126 No 1370; ISSN 1175 8716  URL: http://journal.nzma.org.nz/journal/126-1370/5555/  Dr Coppell kindly sent me a copy (*I’ve made a few more observations about the details of the study for those who are interested below).

In the meantime, this is rightly hitting the headlines.  We should be afraid, very afraid.  Our politicians must stop arguing over that which is petty (like selling less than half of a small fraction of our assets) and get focussed on what matters.  Next year is election year – we should demand a comprehensive diabetes policy from each political party.  Below is a letter I wrote to the Christchurch Press prior to the last election – not much has changed.  As for you – you can stop attacking the sugar – you don’t need it and it may kill you.  Beware of “fat free” food which substitutes sugar instead.  Get some advice – see your doctor.  Don’t become a statistic in the next survey.

As for the link with my work (Kidney Attack a.k.a. Acute Kidney Injury), the little diagram explains.Diabetes AKI



*  The study was a representative sample of New Zealanders.  The study size was large (for an NZ study) – 4,721.

From the results

Overall the prevalence of diabetes was 7.0% (95% CI: 6.0, 8.0). Diabetes was more common among men (8.3%; 95% CI: 6.4, 10.1) compared with women (5.8%; 95% CI: 4.7, 7.0). The prevalence of diagnosed diabetes was 6.0% (95% CI: 4.5, 7.5) among men and 4.0% (95% CI: 3.1, 4.8) among women, and the prevalence of undiagnosed diabetes was 2.1% (95% CI: 1.2, 3.0) among men and 1.5% (95% CI: 1.0, 2.0) among women.

Scary for me is the percentage of undiagnosed diabetes.  This represents tens of thousands of New Zealanders!

Tables in the paper show how the prevalence increases with age and body mass index and that there are marked differences according to ethnicity.  One third of Pacific people over the age of 45 had diabetes, yet about 40% of this was undiagnosed diabetes!

By the way – 95% CI with two numbers following means a that the 95% confidence interval for the prevalence is between the two numbers.  What this means is that there is a 95% chance that confidence interval contains the true prevalence (which can only be known if everyone is measured).  Eg There is a 95% chance that the 6% to 8% confidence interval contains the true prevalence of diabetes (note – 7% should be thought of as an estimate).