Effects of joint mobilization combined with acupuncture on pain, physical function, and depression in stroke patients with chronic neuropathic pain: a randomized controlled trial
Bibliographic record
Abstract
Abstract Objective To investigate the effectiveness of joint mobilization (JM) combined with acupuncture (AC) for treatment pain, physical function and depression in poststroke patients. Methods A total of 69 poststroke patients were randomly assigned to the JM+AC group (n = 23), the JM group (n = 23), and the control group (n = 23). Patients in the JM+AC group and the JM group received JM for 30 minutes, twice a week for 12 weeks, and the JM+AC group received AC for 30 minutes separately once a week. The control group did not receive JM or AC. Pain (visual analog scale, shoulder pain and disability index, Western Ontario and McMaster universities osteoarthritis index), physical function (range of motion, 10-m walking speed test, functional gait assessment, manual function test, activities of daily living scale, instrumental activities of daily living scale), and depression (center for epidemiologic studies depression scale, Beck depression inventory) were assessed for each patient before and after the 12 weeks of intervention. Results Pain and physical function were improved significantly in the JM+AC group compared with the JM and control groups. Physical function and depression were improved significantly in the JM+AC and JM groups compared with the control group. Conclusion The treatment of JM combined with AC improved pain, depression, and physical function of poststroke patients with chronic neuropathic pain in this study. This valuable finding provides empirical evidence for the designing therapeutic interventions and identifying potential therapeutic targets.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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".