Prognosis and Course of Disability in Patients With Chronic Nonspecific Low Back Pain: A 5- and 12-Month Follow-up Cohort Study
Bibliographic record
Abstract
BACKGROUND: Few data are available on the course of and predictors for disability in patients with chronic nonspecific low back pain (CNSLBP). OBJECTIVE: The purpose of this study was to describe the course of disability and identify clinically important prognostic factors of low-back-pain-specific disability in patients with CNSLBP receiving multidisciplinary therapy. DESIGN: A prospective cohort study was conducted. METHODS: A total of 1,760 patients with CNSLBP who received multidisciplinary therapy were evaluated for their course of disability and prognostic factors at baseline and at 2-, 5-, and 12-month follow-ups. Recovery was defined as 30% reduction in low back pain-specific disability at follow-up compared with baseline and as absolute recovery if the score on the Quebec Back Pain Disability Scale (QBPDS) was ≤20 points at follow-up. Potential prognostic factors were identified using multivariable logistic regression analysis. RESULTS: Mean patient-reported disability scores on the QBPDS ranged from 51.7 (SD=15.6) at baseline to 31.7 (SD=15.2), 31.1 (SD=18.2), and 29.1 (SD=20.0) at 2, 5, and 12 months, respectively. The prognostic factors identified for recovery at 5 and 12 months were younger age and high scores on disability and on the 36-Item Short-Form Health Survey (SF-36) (Physical and Mental Component Summaries) at baseline. In addition, at 5-month follow-up, a shorter duration of complaints was a positive predictor, and having no comorbidity and less pain at baseline were additional predictors at 12-month follow-up. LIMITATIONS: Missing values at 5- and 12-month follow-ups were 11.1% and 45.2%, respectively. CONCLUSION: After multidisciplinary treatment, the course of disability in patients with CNSLBP continued to decline over a 12-month period. At 5- and 12-month follow-ups, prognostic factors were identified for a clinically relevant decrease in disability scores on the QBPDS.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".