Systematic narrative review of modalities in physiotherapy for managing pain in hip and knee osteoarthritis: A review
Bibliographic record
Abstract
Osteoarthritis (OA) affects 528 million individuals globally, predominantly in knee and hip joints, with a notable impact on females aged over 55, resulting in a substantial economic burden. However, the efficacy of modalities used in physiotherapy to manage OA pain for reducing the need for joint replacement remains an open question, and guidelines differ. Our systematic narrative review, drawing from reputable databases (e.g., PubMed, Cochrane, and CINAHL) with specific Mesh terms investigated evidence from 23 Randomized Controlled Trials (that included a control or a sham group in 30 different protocols) using therapeutic modalities like ultrasound, diathermy, and electrical stimulation for knee and hip OA pain, involving a total of 1055 subjects. We investigated the attainment of minimal clinically important differences in pain reduction, operationalized through a 20% decrement in the Western Ontario and McMaster University Arthritis Index or Visual Analog Scale (VAS) score. Our results indicated that 15 protocols out of 30 reach that level, but there were no statistical differences among modalities. Half of the protocol presented in the literature reached clinical efficiency but studies on hip remains scarce. We recommend a comprehensive, sequential, and multimodal intervention plan for individuals with joint OA with initial transcutaneous electrical nerve stimulation and progressing to a 2-week protocol of continuous ultrasound, potentially combined with deep microwave diathermy. Long-term intervention involves the use of pulsed electrical stimulation. For hip OA, a cautious approach and discussions with healthcare providers about potential benefits of spinal cord nerve stimulation.
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 | 0.007 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".