The prognosis of acute and persistent low-back pain: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: Although low-back pain is a highly prevalent condition, its clinical course remains uncertain. Our main objective was to systematically review the literature on the clinical course of pain and disability in patients with acute and persistent low-back pain. Our secondary objective was to investigate whether pain and disability have similar courses. METHODS: We performed a meta-analysis of inception cohort studies. We identified eligible studies by searching MEDLINE, Embase and CINAHL. We included prospective studies that enrolled an episode-inception cohort of patients with acute or persistent low-back pain and that measured pain, disability or recovery. Two independent reviewers extracted data and assessed methodologic quality. We used mixed models to determine pooled estimates of pain and disability over time. RESULTS: Data from 33 discrete cohorts (11 166 participants) were included in the review. The variance-weighted mean pain score (out of a maximum score of 100) was 52 (95% CI 48-57) at baseline, 23 (95% CI 21-25) at 6 weeks, 12 (95% CI 9-15) at 26 weeks and 6 (95% CI 3-10) at 52 weeks after the onset of pain for cohorts with acute pain. Among cohorts with persistent pain, the variance-weighted mean pain score (out of 100) was 51 (95% CI 44-59) at baseline, 33 (95% CI 29-38) at 6 weeks, 26 (95% CI 20-33) at 26 weeks and 23 (95% CI 16-30) at 52 weeks after the onset of pain. The course of disability outcomes was similar to the time course of pain outcomes in the acute pain cohorts, but the pain outcomes were slightly worse than disability outcomes in the persistent pain cohorts. INTERPRETATION: Patients who presented with acute or persistent low-back pain improved markedly in the first six weeks. After that time improvement slowed. Low to moderate levels of pain and disability were still present at one year, especially in the cohorts with persistent pain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.064 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".