The straight leg raise (SLR) is a very common orthopedic and neurological testing procedure that has been around for almost 150 years.  There have been some additions to it but for a neural tension test that has been around for that long, its time to face the facts.

Check out the video below on how to perform the SLR:

Basically, the SLR is a pretty decent screening tool.  Meaning, this test should be implemented in the beginning of your clinical exam to rule-out radiculopathy or other nerve pathology in the dura or meninges.  Just remember, it doesn’t give you any applicable information to rule-in any of these conditions if it is positive, just know that negative means more.

To rephrase this, lets look at the numbers.  From my sources, I have about 20 studies to make a judgment call.  The biggest factor that jumps out at me is the pretty high sensitivity and very low specificity values.  (For review of these values, visit here).  You should also look at likelihood ratios (again, review here).

Instead of going through all of the sources, here is a good one:

The following is from a systematic review by Vroomen et al in 1999 found here.  Concerning the SLR (they looked at other factors too), they found that the “SLR was the only sign consistently reported to be sensitive for sciatica due to disc herniation”.  These are the numbers:

-Sensitivity: 97

This is good for a screening test.  If the test was negative, you were correct 97 out of 100 times to show absence of the condition.

-Specificity: 57

Not very good for screening test or plain any testing.  You were incorrectly positive 57 out of 100.  50/50 here basically.

-LR+: 2.23

Small increase in likelihood of the disease.

-LR-: 0.05

Large and often conclusive decrease in the likelihood of the disease.  This is the number you are looking for as if it is <0.1, then it will really help your decision making.

Bottom Line: 

These numbers by Vroomen et al closely match other sources that show approximate values of ~85% specificity and ~40-50% sensitivity.  You have to be careful of other studies that may show different values due to the quality of the research.  Feel free to shoot me any updated information you may have as it will help all of us in the field.  

And P.S., I do not claim to be a master in statistics so if anyone else can explain the values above in better detail, go for it!


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