Narrative
This rational clinical examination confirms the findings of previous studies indicating that traditional coronary artery risk factors (e.g. diabetes, hypertension, etc.) are not useful predictors of acute coronary syndrome. This systematic review also shows that isolated signs and symptoms are not helpful in identifying the underlying ischemic etiology for chest pain. The review states that the most rational approach would be to use TIMI or HEART tools in combination with the institution's background prevalence of ACS to calculate the initial pre- stress test probability of ACS. Unfortunately, the risk scores alone may not be adequate to lower the probability sufficiently to achieve a desired miss rate lower than 1%.
The authors of this systematic review employed the following definition of ACS as their reference standard: either final hospital discharge diagnosis of ACS [either as determined by the treating physician or by systematic central adjudication by reviewers using a pre specified definition of ACS] or clinical cardiac events [encompassing at least cardiovascular death, myocardial infarction, and revascularization] through 14 days to 6 weeks after presentation). A review of the included trials revealed that some of the studies considered events such as “revascularization” and even “conservative management of coronary artery disease” as indicator of ACS diagnosis at discharge. We acknowledge that this method of determining ACS outcome is far from ideal. Therefore we expect that the results of future high quality trials with a proper gold standard for ACS (death or MI) change the likelihood ratios dramatically.
Caveats
Author
Shahriar Zehtabchi, MD
Published/Updated
February 1, 2017
What are Likelihood Ratios?
LR, pretest probability and posttest (or posterior) probability are daunting terms that describe simple concepts that we all intuitively understand.
Let's start with pretest probability: that's just a fancy term for my initial impression, before we perform whatever test it is that we're going to use.
For example, a patient with prior stents comes in sweating and clutching his chest in agony, I have a pretty high suspicion that he's having an MI – let's say, 60%. That is my pretest probability.
He immediately gets an ECG (known here as the "test") showing an obvious STEMI.
Now, I know there are some STEMI mimics, so I'm not quite 100%, but based on my experience I'm 99.5% sure that he's having an MI right now. This is my posttest probability - the new impression I have that the patient has the disease after we did our test.
And likelihood ration? That's just the name for the statistical tool that converted the pretest probability to the posttest probability - it's just a mathematical description of the strength of that test.
Using an online calculator, that means the LR+ that got me from 60% to 99.5% is 145, which is about as high an LR you can get (and the actual LR for an emergency physician who thinks an ECG shows an obvious STEMI).
(Thank you to Seth Trueger, MD for this explanation!)