Physiotherapy-led care versus physician-led care for persons with low back pain: A systematic review
Bibliographic record
Abstract
OBJECTIVE: To summarise the evidence on the effect of physiotherapy-led versus physician-led care on clinical outcomes, healthcare use, and costs in persons with low back pain. DATA SOURCES: PubMed, Web of Science, CINAHL, Embase, and PEDro were systematically searched with the latest search performed in July 2024. Reference lists of articles were hand-searched. REVIEW METHODS: Studies comparing clinical outcomes, healthcare use, or costs between adults with low back pain first consulting a physiotherapist and those first consulting a physician were included. Methodological quality was assessed with the Newcastle-Ottawa Scale. Study design, clinical setting, patient characteristics, and group effects were extracted. Findings on outcomes assessed in two or more studies were synthesised narratively. Certainty of evidence was determined using the GRADE approach. RESULTS: Eighteen studies comprising 1,481,980 persons with low back pain were included. Most studies were non-randomised retrospective or prospective cohort studies. In primary care (15 studies), consistent evidence, though of mostly very low certainty, indicated that physiotherapy-led care leads to higher patient satisfaction, less use of medication, injections and imaging, fewer physician's visits, lower total healthcare costs, and less sick leave compared to physician-led care, without increased harm. In emergency care (three studies), evidence of very low certainty showed that physiotherapy-led care leads to shorter waiting and treatment times, and fewer hospital admissions. CONCLUSION: Physiotherapy-led care is a clinically, time- and cost-effective care pathway for low back pain, although the certainty of evidence was overall very low. Further high-quality research with a greater focus on clinical outcomes is warranted.
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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 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".