A treatment-based classification algorithm for low back pain (LBP) was created to help clinicians select treatments that a patient is most likely to respond to. To allow the algorithm to classify all people with LBP, additional criteria are provided to assist therapists' decisions for patients who do not clearly fit a subgroup (ie, unclear classifications). Recent studies have found that ~34% of LBP patients have unclear classifications.
To guide improvements to the algorithm, it is imperative to determine if these patients are different from those with clear classifications.
Secondary analysis of data from three previous studies investigating the algorithm.
Baseline data from 529 consecutively-recruited LBP patients were used (3 discrete cohorts). The primary outcome was the type of classification: ‘clear’ or ‘unclear’. Univariate logistic regression was used to determine which participant variables were related to having an unclear classification.
People who received an unclear classification had greater odds of being older (OR=1.01; 95%CI=1.003-1.033), having a longer duration of LBP(OR=1.001; 95%CI=1.000-1.001), having had previous LBP (OR=1.61; 95%CI=1.04-2.49), having less fear avoidance beliefs related to both work (OR=0.98; 95%CI=0.96-0.99) and physical activity (OR=0.98; 95%CI=0.96-0.996), and having less LBP-related disability (OR=0.98; 95%CI=0.96-0.99) than people with clear classifications.
The studies from which patient data were drawn had different inclusion criteria and clinical settings.
People receiving unclear classifications appear to be less affected by their LBP (lower disability and fear avoidance beliefs), despite typically having a longer duration of LBP. Future studies should investigate if modifying the algorithm to possibly exclude these people or provide them with a different intervention improves outcomes.
Source: http://ptjournal.apta.org/cgi/content/short/ptj.20120263v1?rss=1
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