Effects of dry needling in an exercise program for older adults with knee osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Few studies have investigated the dry needling (DN) approach on knee osteoarthritis (KO) patients. The study's aim was to evaluate the short-term efficacy of adding DN to a therapeutic exercise protocol in the treatment of KO in older adults. METHODS: A double-blind, pilot clinical trial with parallel groups [NCT02698072] was carried out for 12 weeks of treatment and follow-up. Twenty patients aged 65 years and older with myofascial trigger points (MTrPs) in the muscles of the thigh were recruited from older-adult care centers and randomly assigned to a DN + Exercise group or a Sham-DN + Exercise group. The Numeric Rating Scale (NRS; primary outcome) and Western Ontario and McMaster Universities Osteoarthritis Index questionnaire (WOMAC) were assessed before and after the intervention. RESULTS: The NRS (analysis of variance, ANOVA) showed statistically significant differences in the time factor (F = 53.038; P < .0001; ηp = 0.747). However, it did not show a significant change in the group-time interaction (F = 0.082; P = .777; ηp = 0.005). The WOMAC scores (ANOVA) showed statistically significant differences in the time factor for total score WOMAC questionnaire (F = 84.826; P < .0001; ηp = 0.825), WOMAC pain (F = 90.478; P < .0001; ηp = 0.834), WOMAC stiffness (F = 14.556; P < .001; ηp = 0.447), and WOMAC function (F = 70.872; P < .0001; ηp = 0.797). However, it did not show a statistically significant change in the group-time interaction. CONCLUSION: Despite the pain intensity and disability clinically relevant improvement for both DN and Sham-DN combined with exercise, 6 sessions of DN added to a therapeutic exercise program for older adults with KO did not seem to improve pain intensity and functionality.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".