Here's an interesting 12 lead ECG that I found on the Lifenet Receiving Station at my receiving hospital. It immediately caught my eye for a couple of different reasons.
In the first place, it's an incomplete 12 lead ECG. Lead V1 is missing. This is probably the reason the GE/Marquette 12SL interpretive algorithm is giving the "Data quality prohobits interpretation" statement.
Let's move on.
There's a slight amount of wandering baseline in leads I, II, and III. However, if we ignore the first two cardiac cycles, it appears as though we have 1 mm of ST segment elevation in the inferior leads. In addition, there is a downsloping ST segment in lead aVL. That's a finding that always catches my eye!
Moving on to the precordial leads, the ST segment depression and T wave inversion in lead V2 and the flat, depressed ST segment in lead V3 are deeply concerning. This is a situation where the ability to view lead V1 would be extremely helpful, but I suspect it wouldn't look much different from lead V2.
When it comes to interpreting an abnormal finding on the 12 lead ECG, Tomas Garcia, MD is fond of saying "consider the company it keeps".
What does he mean by that?
Depending on circumstances, you might be able to dismiss an isolated abnormality or quirk on a 12 lead ECG. However, when those quirks start to multiply, and when they "fit" together (as these abnormalities do) your internal barometer should be rising with each observation.
This is a very subtle acute STEMI, but it's a STEMI none-the-less.
I did some investigating and found out that this patient ended up in the cardiac cath lab. I don't know how long it took, I don't know if the interpretive algorithm gave the ***ACUTE MI SUSPECTED*** statement when the ED performed their own 12 lead ECG, or if it was picked up by the emergency physician on duty.
However it happened, I'm glad the patient received reperfusion therapy! The reciprocal changes associated with posterior STEMI are sometimes misclassified as anterior ischemia. When the cardiac biomarkers come back positive, the patients are sometimes classified as NSTEMI.
How important is good data quality?