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.

 

Can Doctors and Nurses help Dialysis patients recover?

In the case of dialysis dependent acute kidney injury patients this is a question which Dr Dinna Cruz  and colleagues (University of California San Diego) are asking and seeking opinions from both nephrologists and non-nephrologist doctors and nurses involved in care of dialysis patients.  It was a question which arose out of discussions at this year’s Continuous Renal Replacement Therapies conference (CRRT 2014). Personally, I think it is a brilliant starting point for research to go out and seek the opinion of those “at the coal face” actually treating patients. If that includes you, please take a moment to complete the survey. If it includes someone you know, please pass this request to participate on.  Here is Dr Cruz’s request:

Currently there is much interest regarding the recovery aspect of AKI. A specific area of interest is how to enhance recovery in patients who remain dialysis-dependent at the time of discharge. It is hypothesized that patients with potential for renal recovery may require a different care plan than the “usual” ESRD patient.

Therefore we are asking your opinion regarding the post-discharge care of such patients, using this short survey. It will take only a few minutes of your time, and represents a starting point for developing potential strategies for these patients. We think it is very important to have the input of specialists from different healthcare settings and countries to give a more balanced view.

Kindly complete the survey appropriate for your specialty, then please share both these links with other colleagues so we get more responses from around the world

For nephrologists:

https://www.surveymonkey.com/s/postdischAKIcare_neph

For non-nephrologists, including acute and chronic dialysis nurses:

https://www.surveymonkey.com/s/postdischAKIcare

Thank you very much for your help!

Source: Anna Frodesiak-Wikimedia Commons

Source: Anna Frodesiak-Wikimedia Commons

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

_____________

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

 

Does being unconscious mean you should miss out?

The front page of the Herald this morning questions the participation of unconscious patients in clinical trials.

While I understand Auckland Women’s Health Council co-ordinator Lynda Williams unease, I also detected a failure to understand the process of how progress in medicine is made.

First, all research in such cases is approved by ethics committees which include lay people and patient advocates. That is clear in the article. In my experience they are very very thorough at ensuring the best interests of patients are highest priority. Family or whanau consent is almost always required (especially if the research involves an intervention*). These are the same family or whanau who are talking with medical staff and, at times, providing consent for medical interventions.  When a person is vulnerable it is up to all around them to treat them with respect and care.  Offering them, through their family, the opportunity to participate in research is showing respect for them as a valued member of society who is prepared to give in the interests of others.  Indeed, it is a right of the patient, through their family, to be offered such research.

Second, without such research there can be no progress in medical treatment of unconscious critically ill patients. In order to save lives interventions must be made at critical junctures during the progress of a disease, normally at the earliest possible time. It is in the best interests of us all that such research take place. The alternative is to give up hope and allow current mortality rates to remain as they are. I research a disease (Acute Kidney Injury) which affects 1 in 3 people in the Intensive Care Unit and increases their chances of dying about 4 times. There is no treatment and it is devilishly difficult to detect in the early stages. An estimated 2 million a year die because of Acute Kidney Disease. Without the generosity of family and friends allowing trialling of an intervention (always based on years of prior research and judged to be possibly efficacious) there will be no progress and the death toll will remain high. I salute family and patients around the world who have participated in such studies in the past, and will do so in the future.

Disclaimers: 1. I have no knowledge or understanding of the antiobiotic trial under discussion.  2. I have been involved in an intervention study where participants were unconscious at the time consent was obtained.

*Note, there are some circumstances where when minutes count an intervention is required.  Research in these areas is ethically more difficult, but no less necessary.  I welcome public debate in this area.  While ethics committees can deal with ensuring minimisation of harm in such circumstances, we do need to decide as a society what sacrifices of individual rights we should make for the greater good.

A new entity is born: CDaR

Have you ever been told the blood test is positive and the disease in question is shocking – Cancer, an STD (but you don’t sleep around!), MS?  Have you every wondered why it is that some drugs get withdrawn years after, and millions of prescriptions after, they were first approved?  Surely, you’ve read a headline that coffee is good for you and chocolate bad, or was that chocolate good and coffee bad or were they both good, or both bad? Probably you’ve read all those headlines.  What does it all mean?  Am I sick or not (I heard some tests falsely give positive results)? Does it matter if I’ve been taking that drug or drinking three cups a day?  The answer to all those questions depends on one thing – clinical data research.  That is, it depends on how we collect the numbers, and what story those numbers are telling us.  Today, I am thrilled to announce that I have had my department’s (Department of Medicine, University of Otago Christchurch) endorsement to establish a new group, Clinical Data Research (CDaR), which will focus on the stories numbers in medicine tell us.

Source: Pickering et al http://ccforum.com/content/17/1/R7

Source: Pickering et al http://ccforum.com/content/17/1/R7

My recent expertise, as readers of this blog may have picked up, is in Kidney Attack (or Acute Kidney Injury). My contribution, as someone with a physics background, has been in data analysis and mathematical modeling.  It has been a privilege to have been involved with many discoveries and helping bring to light the stories of the biomarkers of that disease and the results of a unique randomised controlled trial.  Kidney Attack is a notoriously difficult to detect, and, partly because of that, one that has no effective treatment.  I’m currently working on the story of the association of Kidney Attack with death following surgery with cardiopulmonary bypass.  I am now looking to take those skills and work with other researchers in other medical specialties who generate data and are looking to tell its story (although I will still work on the kidney data!).  I’m particularly keen to engage with more students and pass on some of the data analysis skills I have acquired.  Moves towards open data as well as collection of data in large databases is providing more opportunities to assess the efficacy of health interventions and detect disease risk factors. The prospect of personalised medicine is one of both hope and hype. To sort fact from fantasy in all these areas will require development of new analytical techniques and careful assessment of evidence. This is what I wish to devote the rest of my career to, and to inspire others along the way. John Ioannidis, a highly respected biostatistician, once wrote an essay entitled “Why most research findings are false”  It is a scary thought that many interventions and diagnostic techniques in medicine may be based on biased studies (usually inadvertently biased!). More data will help reduce the bias, if it is treated nicely.  I promise to do my best to treat my data nicely, after all it is your and my health that is at stake.

I posted a few weeks ago my ten commandments of a data culture.  This is the ethos of CDaR.  Below is the lay summary of the new entity.

Group Name:            Clinical Data Research (CDaR)

Department:             Department of Medicine

Institution:                University of Otago Christchurch

Aim: To provide transparent evidence, with the lowest possible risk of bias, of the utility of biomarkers and efficacy of treatments in health or disease.

Lay summary of our aim: We aim to save lives and reduce the burden of disease by applying new ways to collect and analyse clinical data to better diagnose diseases, to predict the course and outcomes of diseases, and to assess how well treatments work.  We do this because we all want the best possible health outcomes for our communities, our families, and ourselves, with the least possible harm done along the way.  We are excited by the new ways scientists, including those at the University of Otago Christchurch, have come up with to measure disease, disease risk, and treatment outcomes. We are also living in an age of unprecedented data generation. To discover both benefits and harm in all this data and to make those discoveries available to all those making clinical decisions requires people dedicated to analysing this data in a transparent and open fashion that exposes both the good and the bad. That is who we want to be and who we want our students to become.

Definition:  A biomarker is any measureable quantity related to disease risk or diagnosis, or disease or health outcomes.

Nelson Mandela is on dialysis

CNN is reporting Nelson Mandela is on dialysis. http://t.co/HZTIlmGrtO.  This means he is suffering from Acute Kidney Injury, the disease I study.  Having to have dialysis is very serious. Unfortunately, survival rates are only about 50% by this stage, less in the very elderly.  Dialysis is not a treatment, merely a support for the kidney to try and give them time to recover  function on their own and  a means to remove toxins from the body.