Effectiveness of Transcranial Direct Current Stimulation in Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: The aim of the study is to assess the effectiveness of transcranial direct current stimulation in knee osteoarthritis. METHODS: The study searched PubMed, Cochrane Library, Embase, and Scopus databases until August 3, 2023, and identified randomized controlled trials evaluating the effects of transcranial direct current stimulation in knee osteoarthritis whose outcomes using pain scores or functional scales. The selected randomized controlled trials were subjected to meta-analysis and risk of bias assessment. RESULTS: Seven randomized controlled trials involving 488 patients were included in this meta-analysis. Compared with the control group, the transcranial direct current stimulation group exhibited significant improvement in pain scores after treatment (standardized mean difference = 1.03; 95% confidence interval: 0.70 to 1.35; n = 359; I2 = 46%), pain scores during follow-up (standardized mean difference = 0.83; 95% confidence interval: 0.21 to 1.45; n = 358; I2 = 86%), and Western Ontario and McMaster Universities Osteoarthritis scores after treatment (standardized mean difference = 4.76; 95% confidence interval: 0.16 to 9.53; n = 319; I2 = 74 % ), but Western Ontario and McMaster Universities Osteoarthritis scores during follow-up did not differ significantly between the groups (standardized mean difference = 0.06; 95% confidence interval: -0.2 to 0.32; n = 225; I2 = 0%). CONCLUSIONS: Transcranial direct current stimulation is a promising therapy for knee osteoarthritis. Further investigation using large-scale, high-quality randomized controlled trials is necessary for optimal transcranial direct current stimulation approach in knee osteoarthritis.
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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".