Tuesday, June 23, 2015

Point of Care Evidence-Based Nephrology Diagnosis

The use of evidence-based diagnosis is what we are taught that we should all do but in practice, this is quite difficult. EBM diagnoses rely on likelihood ratios but it is impossible to remember the diagnostic accuracy of the thousands of tests out there.

This is why I developed a simple tool to help with the scientific diagnosis of common nephrological problems, as well as diseases spanning most specialties. It is a database of more than 700 likelihood ratios of tests (history, physical exam, radiology, etc.). The likelihood ratios are completely free for all to access and are available on my website and on an app I developed for the iphone/ipad called DxLogic. Android users are not left out as the website is mobile-friendly.

The following examples will demonstrate how you to can use this resource to approach some common clinical nephrology situations in a probabilistic and rational manner. The screenshots found below are from the iOS application.

Example #1

You are consulted for a 50yr old man admitted with pneumonia who has developed AKI in hospital. He was started on ceftriaxone 10 days ago and, after examining the patient and a chart review, you wonder about acute interstitial nephritis secondary to antibiotics. You remember being told that urinary EOS are a great test for this disease. But does this test actually increase or decrease the possibility of this diagnosis? From the screenshot below, we see that the presence of EOS in the urine actually has no diagnostic value for AIN. You save the lab time and money by not ordering the test.




Example #2

A 30 year old woman presents to your clinic with symptoms and signs consistent with nephrotic syndrome. She also has a questionable malar rash and a family history of lupus.  You wonder if she could have lupus nephropathy. Using the resource we find that her probability of having lupus nephropathy before any tests are ordered is 14%,



You order an ANA titer and this comes back negative. Plugging this into that app we find that her probability of having lupus nephropathy on renal biopsy is now 3% - a low, but not an insignificant percentage. 



I hope this article has made you aware of the important role that likelihood ratios can play in nephrological practice. Please give my app/website a try and feel free to contact me with any comments or suggestions.

Contact information:
Michael Garfinkle
University of Calgary
Twitter –  @joyofmed 

1 comment:

Ala Ali said...

Excellent work, We will try and feed back. Renal Transplantation ???