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Axis Determination: Why Learn It?!

Updated: Jun 21, 2021



Jeff Beeson, DO, LP once said, “The eyes cannot see that which the mind does not know.” Without a proper understanding of axis, you cannot really see a 12-lead ECG. Once you fully understand axis it gives you a vocabulary that allows you to take ECG interpretation to the next level.


It doesn’t help that this topic is poorly taught at all levels.


Here are some examples where understanding the heart’s axis helped me make wise decisions on actual emergency calls.


The most common causes of left axis deviation are left anterior fascicular block and Q-waves from inferior MI. So when I see a left axis deviation it prompts me to consider these conditions. Many times I have caught subtle inferior STEMIs because the axis was slightly to the left and it prompted me to look at lead aVL for subtle reciprocal changes.



A paced rhythm with a pacing lead in the apex of the right ventricle typically shows LBBB morphology in lead V1 and left axis deviation. So this prompts me to double-check for a pacemaker pocket on the patient’s chest and consider that the rhythm may be paced before I decide the patient is showing frequent PVCs or a run of slow VT. Remember Rhythm Challenge #5?



Conversely, it would be very unusual for LBBB or paced rhythm to show LBBB morphology in lead V1 with a right axis deviation. That in turn further supports the dx of VT in a patient who happens to have a pacemaker. That helped me identify a run of VT at a rate of 140 when others called it a “runaway pacemaker.”


Here’s a similar example:


A pulmonary disease pattern may pull the axis to the right. It may also cause right atrial enlargement. In addition, many congenital heart defects cause right ventricular hypertrophy with an associated right ventricular strain pattern. So when you see right axis deviation, tall R-waves in lead V1, and T-wave inversion in the right precordial leads, you know it’s consistent with the patient’s history and “anterior ischemia” requiring NTG. There is a young woman with a congenital heart defect in my jurisdiction who has received MONA for her anxiety attacks more than once because of her abnormal ECG.


Here’s the ECG if you’re curious:


Q-waves from high lateral MI pulls the axis to the right. Left posterior fascicular block is rare as an isolated finding, but that also pulls the axis to the right. Combine left anterior fascicular block (left axis deviation) or left posterior fascicular block (right axis deviation) with RBBB morphology in lead V1 and it’s referred to as a “bifascicular-pattern” which is one of the keys to understanding wide complex tachycardia.


An extreme right axis deviation (or right superior axis) might suggest incorrect lead placement, electrolyte derangement, or help you rule in a ventricular rhythm. I can’t discuss this topic without mentioning that failure to rule in VT based on QRS morphology does not rule out VT. Brugada’s algorithm and Wellens’ criteria are not well understood and have led far too many health care providers of all stripes to call a wide complex rhythm “SVT with aberrancy” which can lead to clinical misadventure.


Never assume that a wide complex tachycardia is SVT with aberrancy based solely on QRS morphology! Just because it looks like LBBB doesn’t mean it isn’t VT.



I could give other examples, but the point is that you cannot develop a trained eye if you don’t have the tools to describe what you see. I was explaining the concept of appropriately discordant T-waves with bundle branch block to someone the other day and it would have been extremely difficult if he didn’t understand the concept of a terminal deflection.


If you want a dramatic illustration of this point, teach a 12-lead ECG class and at the beginning of the class ask the students to take out a blank piece of paper and draw a picture of a normal 12-lead ECG. If you don’t understand normal how can you possibly hope to identify abnormal?




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About Me

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I am the Battalion Chief of EMS for Hilton Head Island Fire Rescue and obsessed with all things process improvement, system performance, human factors, crew resource management, and evidence-based performance measures for time-sensitive diagnoses.

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