OUWB Question about pseudohyponatremia

First catch of the year.

I have a question regarding your OUWB lectures. I’m trying to grasp why hyperglycemia causes an increase in serum tonicity and decrease in serum sodium, but hyperlipidemia causes no change in serum tonicity and a decrease in serum sodium. For hyperglycemia, I understand that the glucose contributes to the serum osmolarity and can’t passively cross the membrane so causes water to move. However, I’m confused with the situation with lipids and was wondering if you could clarify. Thank you so much!

I may have over indexed on false hyponatremia stuff. This is something you need to be familiar with but a detailed understanding of the mechanism of pseudohyponatremia.

The student had perfect knowledge of the mechanism behind hyperglycemia induced hyponatremia associated with hyperglycemia.

The lipid situation is just a lab error. The lipids fool the lab machine into thinking the sodium is low. It is not low. That is why the osmolality is normal. The osmolality detector is not fooled by the high fats (or proteins) in the blood.

You will not need to know the mechanism for the lab error. I tried to explain it but that may be a situation where I causes more confusion than provided clarity.

The unexpectedly high protein or lipid fraction results in the sample being over diluted resulting in a false report of hyponatremia. The serum sodium is normal. Only about a third of clinical labs are susceptible to this error.

 

All my Posts for Medical Students at OUWB

I have had the honor to teach the M2s since the medical school opened it’s doors. Here are the blog posts I have written to answer medical students questions or to post the latest materials (Handouts, Keynotes).

OUWB M2 questions and Answers

OUWB M2 questions and Answers

The Prince William Question Lets do this number

More questions from the minds of the M2s at OUWB

More questions from the minds of the M2s at OUWB

The minds of OUWB continue to provide thoughtful

Metabolic Alkalosis, the emergency lecture

Metabolic Alkalosis, the emergency lecture

“I thought you were going to do metabolic

The Hypernatremia Lecture for OUWB

Las\\t Wednesday I was unable to get through the

Introduction to Acid-Base and Metabolic Acidosis

Introduction to Acid-Base and Metabolic Acidosis

Today’s lecture, in PowerPoint, no less.

OUWB Question about pseudohyponatremia

OUWB Question about pseudohyponatremia

First catch of the year. I have a question

All my Posts for Medical Students at OUWB

I have had the honor to teach the M2s since the

The TTKG is dead, now what?

Halperin has declared the TTKG dead.

And therefore never send to know for whom the bell tolls; It tolls for the TTKG

However we still need to assess patients for hypokalemia and differentiate between renal and extra-renal losses.

Measuring a fractional excretion of potassium (FEK) doesn’t physiologically make sense. The idea behind the fractional excretion calculation is calculating what percentage of the filtered potassium (in this case, but can be anything) ends up in the urine. But potassium doesn’t work that way. Essentially all of the filtered potassium is reabsorbed in the proximal tubule and thick ascending limb of the loop of Henle so that the fractional excretion of potassium is zero at that point. Then in the late distal convoluted tubule and the medullary collecting duct all of the potassium that is destined for the toilet is secreted. So all of the potassium that is cleared by the kidney is secreted but the distal nephron/tubules not filtered by the glomerulus. That said the FEK is just a calculation and you can do it. I reviewed the the best data on it here:

FERE: Fractional excretion of random electrolytes

So what calculation do I use? I use the TTKG, but that’s because I’m a dinosaur. What I should be doing is the urine potassium to creatinine ratio.

The answer is 13 mEq/g creatinine.

In this study of hypokalemic periodic paralysis versus patients with increased renal potassium excretion, the K:Cr ratio neatly divided the two groups.

the dividend line here was 2.5 mmol K/mmol Cr or 22 mEq/g Cr

If you know of a better reference for the potassium to creatinine ratio, tweet me up.

Some addenda to my Curbsiders podcast on NAGMA

In my discussion on The Curbsiders I talked about the urine anion gap as a way to estimate urine ammonium. Here are the figures I would have shown for the urine anion gap, if the Curbsiders was a television show rather than a podcast:

The urine anion gap is wildly inaccurate at estimating urine ammonium. In this study of 1,044 people with chronic kidney disease, the urine anion gap was 42, while the urine ammonium was only 21:

Would you trust a technique to measure serum sodium if it was twice the actual serum sodium?

There is a second way to estimate the urine ammonium, the urine osmolar gap. The urine osmolar gap was devised to escape a different weakness in the urine anion gap, the problem with large amounts of urine anions, like ketones or hippurate.

The osmolar gap assumes that the difference between the measured and calculated osmolality will largely be made up by ammonium salts.

Here is a tweetorial about this, if that is your thing:

Part One: Don’t trust equations:

Part Two: But you need to understand the equations so you can use them properly, the urine anion and osmolar gap:

The other mistake I made was an over simplification on how NH4+ is made. I said NH3 was made in the proximal tubule but it is more complicated than that. A lot more complicated. From David Goldfarb:

The proximal tubule makes 2 molecules of NH4+ via Glutaminase which also produces a  1 alpha-ketaglutamate (AKG). The AKG generates 2 molecules of HCO3 which is added to the blood. The NH4 gets tossed into the tubular fluid. So for every NH4+ created in the proximal tubule, one bicarb gets added to the blood.

Twitter and the New England Journal of Medicine

In the last month, the NEJM published two articles with Twitter as a central focus.

First there was “Social Media and Advancement of Women Physicians” featuring Heather Logghe’s #ILookLikeASurgeon and @McSassyMD, @SingleScalpel and @DoctorMeowskis‘s #GirlMedTwitter

https://twitter.com/mcsassymd/status/1019283981106405376

And then in tomorrow’s print edition is former NEJM editor, Lisa Rosenbaum‘s editorial about Esther Choo‘s recent viral hashtag #ShareAStoryInOneTweetTwitter Tailwinds — Little Capsules of Gratitude.

It is amazing to see thought leaders in medicine emerge from #MedTwitter. And it is equally amazing to see the oldest of the old guard, The NEJM, embracing this brave new world.

Curbsiders #104: Renal Tubular Acidosis

This is the back half of my Acid-Base talk, a detailed dive into non-anion gap metabolic acidosis with an examination of renal tubular acidosis. This one turned out pretty good.

Here is a link to the Curbsiders page for this episode.

This is the sequel to #88 Acid base, boy bands, and grandfather clocks with Joel Topf MD

Before that I did episode #67 and #69 on chronic kidney disease

Before that was #48 Hyponatremia Deconstructed

And I started my Curbsiders career with #31 Diuretics, leg cramps and resistant hypertension.

So non-anion gap metabolic acidosis is my fifth or sixth appearance on the Curbsiders. Thanks guys.

Tweetorial attention attenuation–updated

My first Tweetorial has turned into my second most popular tweet, only behind:

A tale of two tweets:

Twitter analytics provide a unique opportunity to look deeper than just who saw the original tweet. By checking the analytics of each subsequent tweet in the stream we can see how many people trudged all the way to the end.So how did the hyponatremia tweet stream do? Here are the analytics from the first to the last tweet.The Y-axis is “Impressions.”This is not impressions like Symplur does (used to do?). This is not the tweets multiplied by the number of followers. Twitter is in the unique position to know how many times any particular tweet is delivered to a device. So your cousin who lost her twitter password in 2014 and the sock puppet account that Eugene Gu abandoned in medical school don’t get counted as impressions. The first Tweet had 47,000 impressions. The second had 5,700. That first step is a doozy.From there things were surprisingly stable. Hey Dr V, let’s see a blog post track who reads to the end of the post.More than 3,000 people read pretty much the entire stream. I am quite satisfied. 3000 people is a lot of grand rounds.

 

Update

Some people have wondered about the second drop in participation that occurs at tweet 31.

I think the answer is here:

When you click on the initial tweet, you can see tweets 1-30, but to get the last 5 you need to click on the “5 more replies” link.

The final bump is due to a surge of people tweeting in celebration of completing the tweet stream: