Effects of low-intensity pulsed ultrasound on knee osteoarthritis: A systematic review and meta-analysis of randomized controlled trials
Bibliographic record
Abstract
Objective To systemically review the effects of low-intensity pulsed ultrasound (LIPUS) on pain relief and functional recovery in patients with knee osteoarthritis (KOA). Data sources PubMed, Web of Science, Cochrane Library, Physiotherapy Evidence Database (PEDro), and China National Knowledge Infrastructure (CNKI) were used from inception to 18 March 2022. Review Methods Meta-analysis was performed to evaluate pain and function recovery between control and LIPUS groups. Standardized mean difference (SMD) or mean difference (MD) and 95% confidence interval (CI) were calculated, and data were combined using the fixed or random-effect model. Results Thirteen studies involving 807 patients with KOA were included. Patients’ outcomes treated by LIPUS were improved significantly, including Visual analog scale (VAS) score (MD = −0.95, 95% CI: −1.43 to −0.48， P < 0.001), Western Ontario and McMaster Universities Osteoarthritis index (WOMAC) score (MD = −4.35, 95% CI: −8.30 to −0.40, P = 0.0309), Lysholm score (SMD = 1.59, 95% CI: 1.29 to 1.90, P < 0.001), Lequesne index (MD = −1.33, 95% CI: −1.69 to −0.96, P < 0.001), Range of motion (ROM) (MD = 2.43, 95% CI: 0.39 to 4.46, P = 0.0197) and 50 meter walking time (SMD = 1.48, 95% CI: 0.46 to 2.49, P = 0.0044). Subgroup analyses showed monotherapy of LIPUS produced a better effect on reducing VAS score ( P = 0.0213), and the shorter therapeutic period (≤4 weeks) produced a more significant effect on raising the WOMAC score ( P = 0.0083). Conclusion LIPUS was beneficial for pain relief and functional knee recovery and maybe as an alternative therapy in KOA rehabilitation.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.028 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".