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Recognition-Primed Bradycardia

The AHA has an algorithm to approach a patient with symptomatic bradycardia. While the data in this algorithm may vary from one revision to the next, the overall flow has remained relatively the same. The algorithm starts when a patient has a heart rate < 50 and associated symptoms.

While all good things to consider, this approach's flow does not match how experienced clinicians think through and approach bradycardia. My idea for this blog (and class in Studio) is to utilize Gary Klein's "recognition-primed decision" model to decrease the time it takes for timely, meaningful intervention.

Early in my career, I met a relatively new paramedic voicing frustrations with his rather short Rolodex of experiences for decision-making. I remember he said, " it seems like everything I do or see is like the first time." In fact, it was the first time. One particular call he mentioned was from a patient who was hypotensive and bradycardic at a nursing home. He correctly interpreted the rhythm as a complete heart block and worked his way down the algorithm to pacing. After nearly 30 minutes of trying to get capture, he decided to just transport to the hospital.

The patient had a rather large fistula in her arm and a history of chronic renal failure. The potassium returned with a value of 8 meq/l, and he was beating himself up for not recognizing this and administering calcium.

This example is one of many across healthcare individuals who either:

  • Have limited exposure to sick patients

  • Have limited experience in the field

  • Do not pay close enough attention even to recognize what happened

I used to utilize the acronym DIE when thinking of the most common causes of bradycardia.

  • Drugs - Beta blockers, calcium channel blockers, dexmedetomidine, octreotide, digoxin.. and whatever new drugs I learn about that cause bradycardia.

  • Ischemia - With roughly 80% of the population being right dominant (meaning the posterior descending artery is fed by the right coronary artery), one of the first ECG findings in an MI (especially in the inferior wall) is bradycardia. However, bradycardia can also arise from overstretched or underfilled ventricles; such is the case in the famous Bezold-Jarisch Reflex.

  • Electrolytes - Hyperkalemia, Hypomagnesemia, etc

The DIE algorithm was what I would use to think through the first few minutes of why someone could possibly be bradycardic. Until one day when it failed me. A previously healthy young man presented to the ED with a syncopal episode. His initial ECG revealed a complete heart block. The heart rate was 34, and the blood pressure was stable. No chest pain, electrolytes were within normal range, and there was no report or reason to believe this was drug-induced.

"I mean, maybe he just has a sick SA or AV node?" I thought to myself.

I spent the entire transport trying to figure out why this 28 yr guy would suddenly have a complete AV block, and his only real symptom was flu-like symptoms over the last month.

The physician asked the patient if he had had any recent unexplained rashes or tick bites. The patient said he indeed did and that it was a little over a month ago. You could see the physician working through a very specific mental model, which was very intriguing to watch. The patient pointed to a rash on the back of his right leg.

After the physician left the patient's beside, I approached his desk and asked:

"How in the world did you diagnose that within seconds of him being here?!"

He explained that this was very common in Wisconsin during hunting season and that he had seen it before. The patient was started on doxycycline and the AV block resolved within a few days.

I became obsessed with cases where clinicians almost seemed to have super clinical ESP. Sometimes it appeared as if they were tipped off or read a cheat sheet before arriving at the patient's bedside. I wanted this.. like, more than anything. I thought reading everything I could get my hands on regarding medicine would help. It did, but not in isolation. I found the recipe for me building mental models that were effective in real-life scenarios was dependent on the following:

  • The volume of sick patients seen over time

  • An objective and current resource to read up on the disease process or injury within 24 hours of encountering it in the field.

  • Accurate performance evaluation

Unfortunately, building a wide array of strong and accurate mental models in an area where call volume is low will be nearly impossible. The only way I believe this can be done is through quality simulation. Simulation can, however, be completely useless if the objectives do not accurately reflect real-life scenarios and illness patterns.

The AHA bradycardia algorithm (or any of their algorithms) are built as a framework for providers without a strong mental model for differentials and treatment course. This may be a dentist or family practice physician with different types of mental shortcuts.

It is important to note that mental simulation can make us fall in love with a particular diagnosis and reject anything else because it does not match our previous experience. This is why it is important to be quick to make a decision but even quicker to change your mind in light of new information. Check out this podcast on FOAMfrat discussing when mental models fail.

Every time you encounter a patient or walk into the simulation lab, you have the opportunity to upgrade your mental model and Rolodex of experiences to pull from in stressful situations.

Oh, and I also updated my bradycardia model.

FOAMfrat Studio provides an evidence-based resource to utilize within 24 hours of encountering a specific type of patient. During this time frame, my brain identifies the clinical questions regarding the type of patient I encountered as extremely relevant. With over 300 classes that range from self-paced to instructor-led scenarios, there is not much you will encounter in the field that we haven't dissected and provided the current evidence on.

Click the picture below for more information on FOAMfrat's Library.

References are linked throughout the blog.


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