Rehabilitation for chronic low back pain
Bibliographic record
Abstract
Editor—We have misgivings about the conclusions drawn by Guzman et al on multidisciplinary rehabilitation for chronic low back pain.1 Low back pain problems are as heterogeneous as the wider category of chronic pain, and in disregarding systematic reviews and meta-analyses of multidisciplinary rehabilitation in chronic pain Guzman et al have missed a large body of relevant evidence, including trials of cost effectiveness.2,3 Standard quality criteria used for randomised controlled trials cannot be applied in an unmodified form to psychological treatments, which constitute important components of multidisciplinary rehabilitation. The impossibility of blinding patients and therapists need not lower standards. Several trials reviewed employed recognised methods for establishing treatment equivalence: patient rating of treatment credibility or expectations; manualised treatments; blind rating by experts of treatment excerpts; and close supervision of therapists. It is disappointing to see the Cochrane Back Review Group continuing to apply inappropriate criteria and thereby misjudging methodological quality of trials. Variability in outcome arises from heterogeneity among patients, differences in treatment, and their interaction, not only from length of treatment. Content of treatment is far more important than the total time of the programme. Physical treatment alone, as Guzman et al say, is a weak way to change behaviour, particularly in relation to work and use of health care. Patients who have become fearful of further pain and damage, and who are disabled as much by their fears and misapprehensions as by the pain itself,4 need psychologically based treatment, which is still in short supply. The emphasis on return to work as the primary outcome is inappropriate when the population includes homemakers, as did several of the trials reviewed. Disability or function is a broader issue and includes the important, but neglected issue, of change in use of healthcare resources. An undue focus on return to work to define effectiveness leads to restricting access to treatment for non-workers, particularly among older patients. Guzman et al acknowledge that their conclusions may not apply in primary care, but patients are better defined by their level of disability than by the setting in which they are seen, and their treatment defined not by hours but by its adequacy to restore as near as possible normal function, whether in secondary prevention of recently injured workers or chronically disabled non-workers.5 This review offers clinicians little help in selecting the right level of treatment for patients with low back pain.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.055 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.011 | 0.021 |
| Insufficient payload (model declined to judge) | 0.021 | 0.012 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".