With this blog I would like to try something new by presenting an interesting case for you to ponder. Please study that data and the diagnosis and contemplate the situation before reading my comments.
A 32 year old homeless male presents to the Emergency Department complaining of chest pain. He admits to the clinician of drinking excessive amounts of alcohol on a regular basis. At this time there is alcohol on his breath. His sinus rhythm is 100 and his ECG/EKG is non-diagnostic.
The laboratory runs a series of cardiac markers at To and again at T2 hrs:
Marker To T2
Total CK 1469 1431
CK-MB 31 30
Myoglobin 206 165
cTnI 0 0
The admitting clinician’s diagnosis was “Heavy alcohol abuse; acute subendocardial MI.”
What do you think?
My thoughts:
1) In sharing this case with medical technologists across the country I have not heard the diagnosis of MI from any of them. Where is the discrepancy? It seems to me that the clinician made the diagnosis based on the TCK, MB and myoglobin, all of which were elevated at the time of presentation. The troponin was undetectable at that time and 2 hours later. These two values argue against an MI.
2) Both the total CK values are exceptionally high for an AMI.
3) The TCK and MB really didn’t change during the 2 hour period between samples, arguing against an MI.
4) The ratio (for those of you who remember) of MB to TCK (MB*100/TCK) is only slightly above 2.0, which is generally considered normal.
In essence, there are not compelling data to suggest an MI. Contrarily, this data can be used to rule out an MI.
What, then, are the take home messages? First, this case is an excellent argument for discontinuing TCK, MB and myoglobin in the ED patient where the results could be misleading. In this case, the admission of heavy alcohol use reminds us that in a sense alcoholism is a muscle-wasting disease and explains the high constant levels of markers known to be affected by muscle damage. Second, three markers might point in one direction, the cTnI points in another. This is the time to ask why there might be confounding data? Lab error? Did I miss something?
I thank Dr. P. Patterson for this case and suggest you read How Doctors Think for an intriguing look at that topic.
I would like to solicit cases from you to include in future blogs—left as comments below, or you can e-mail davidplaut@yahoo.com. Thank you.