Management options of chronic low back pain. A randomized blinded clinical trial
Bibliographic record
Abstract
OBJECTIVE: To compare efficacies of 2 active programs in the management of chronic low back pain (CLBP). METHODS: This prospective, stratified, randomized single-blinded controlled study was conducted in the Department of Rehabilitation Medicine, King Abdullah University Hospital, Irbid, Jordan, between February and December 2010. A total of 100 patients were randomized to either 6-weeks of multidisciplinary rehabilitation (group A) or therapist-assisted exercise (group B). At baseline and 6 weeks, the visual analogue scale (VAS) pain score was estimated, as a primary outcome measure. McGill pain score, Oswestry Disability Index (ODI), trunk forward flexion and extension, left and right lateral bending, were applied before and after treatment and were employed as secondary outcome measures. RESULTS: All outcome measures significantly improved in group A after treatment, compared with group B. The VAS, McGill, ODI scores, left and right lateral bending decreased significantly, whereas forward and backward bending increased. A significant number of patients returned to work in group A at the end of 6 weeks, compared with group B. These effects were maintained over 12 and 24 weeks of follow-up. CONCLUSION: Multidisciplinary rehabilitation improved functional indices and pain scale scores in group A compared with B. This would be an effective strategy in CLBP management.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".