Dionne and colleagues (CMAJ, 2005) recently published a clinical prediction rule (CPR) which was designed to determine what baseline variables in individuals with low back pain will predict a “return to work in good health” at 2 years. This type of information if robust enough to substantially change our post test probabilities would be very helpful to us. The best predictive model included 7 baseline variables (patient’s recovery expectations, radiating pain, previous back surgery, pain intensity, frequent change of position because of back pain, irritability and bad temper, and difficulty sleeping). The model was somewhat helpful for identifying individuals that will go on to problems (i.e. specificity or +LR) it was more helpful in identifying those folks that will not have problems. In other words what group of subjects is at a low risk for an adverse outcome?
In my opinion the greatest value of the paper is Figure 3 which is a clinical algorithm to predict the likely outcome of an individual patient at 2 years of return to work in good health. Practically speaking if a patient doesn’t believe he will be back to work in 3 months and has leg pain then you only have a 25% chance for total success in this patient and nearly 50% (46%) chance that they will not be working at 2 years. We better be very aggressive in our rehabilitation including a comprehensive program to address the probably fear avoidance beliefs in this patient.
Tim
Download CPR_LBP_RTW_CMAJ_2005.pdf