Rinne, Weber and Likelihood Ratios

Click here to listen to a recording of the session. Apologies for some minor irregularities in this week's recording. 

Nomogram for using likelihood ratios. 

For HIPPA-related reasons, we are no longer going to be posting Resident Report publically; however, you should soon be able to get a recording of Dr. Schafhalther-Zoppoth's comprehensive introduction to transverse myelitis (and future Resident Reports, noon conferences, etc.) from the Attendings Folder.  We will still be recording the "5 minutes of EBM" sessions, and after a significant outpouring of feedback I (NN) am going to try really hard to remember to talk more slowly.

This week we talked a little about the diagnostic accuracy of physical findings.  Specifically, we talked about likelihood ratios as they apply to diagnostically useful physical signs.

Likelihood ratios (LRs) can be generated from the same information you use to calculate sensitivity and specificity.  What they specifically evaluate is the ratio between the likelihood of a particular diagnostic finding occurring in somebody with the target disorder and the likelihood of the same finding occurring in somebody without the target disorder.  Follow this link for a more comprehensive (and surprisingly readable) discussion of LRs.

Heinrich Adolph Rinne

Likelihood ratios are particularly useful because you can use them to directly translate pre-test probability into post-test probability.  Because the likelihood ratio is an expression of odds, not percent probability, it's easiest to use a nomogram to do this so that you can avoid converting back and forth. To use the nomogram to the upper right (developed by EBM pioneer David Sackett,) connect the pre-test probability to the likelihood ratio of your test using a straightedge.  The number intersected by the straigtedge on the scale furthest to the right is the post-test probability conferred by the likelihood ratio.

We talked specifically about the likelihood ratios associated with Weber's and Rinne's tests for conductive vs. neurosensory hearing loss.  Weber mystified a generation of neurology patients by sticking tuning forks in the middle of their foreheads.  His test is supposed to lateralize to the bad ear in conductive hearing loss, and the good ear in neurosensory hearing loss.  Heinrich Rinne's test for conductive hearing loss involves testing hearing by direct conduction through the mastoid versus air conduction through the tympanum and auditory ossicles. 

Ernst Heinrich Weber

We all learn these tests in medical school, but most people have little sense of their quantitative significance (which is under-emphasized in physical examination generally.) However, if you go to the McGee's magesterial Evidence Based Physical Diagnosis, you will find that Rinne's test has a published positive likelihood ratio of 16.8, and a negative likelihood ratio of 0.2.  For the sake of example, this means that if you take somebody who has a pre-test probability of conductive hearing loss of 20% and Rinne's test reveals that bone conduction is superior to air conduction, their post-test probability rises to around 80%.  Conversely, a normal result would reduce the probability to about 5%.  These are both pretty significant diagnostic yields for a test which is easy to perform and requires nothing more complicated than a vibrating bit of aluminum.

Weber's, on the other hand, does not fair so well.  The finding of lateralization to the good ear as a predictor of neurosensory hearing loss is associated with a modest LR of 2.7, and the negative likelihood ratio for this finding is nonsignificant.  The positive likelihood ratio of lateralization to the bad ear for detecting conductive hearing loss is nonsignificant, and the negative likelihood ratio is only 0.5.  Application of these values to the nomogram is left as an exercise to the reader, but they changes in probability they confer are nothing to write home about.

So the take-home points are that:

A) Many studies of diagnostic strategies report their findings in terms of likelihood ratios, which are not hard to understand and quite useful, and
B) It's worth looking into the published test characteristics associated with your physical exam maneuvers, because some of them (like Rinne's) are very reliable and some (like Weber's) don't change things all that much.