Influential factors analysis on the curative effect of standard acupuncture in patients with knee osteoarthritis
Bibliographic record
Abstract
Objective: To analyze the influential factors on patients with knee osteoarthritis by standard acupuncture treatment. Methods: Patients with knee osteoarthritis were recruited from the outpatient department. All patients were treated by use of 8 acupuncture points and received standard acupuncture treatment for a period of 4 weeks. The osteoarthritis indexes brought by western ontario and McMasters universities were used to assess the patients at the start of the experiment and after 4-week of experiment. According to the improvement rate of WOMAC scores, patients were allocated to ineffective group, effective group and markedly effective group. The factors that may influence the efficacy were analyzed. Results: 152 of the 182 patients enrolled from Feb 6, 2011 to Jul 17, 2012 completed the trial, with ineffective group accounting for 45 cases, effective group 53 cases and markedly effective group 54 cases. Kellgren-Lawrence degree showed significant differences among the groups(P0.05). Kellgren-Lawrence degree in ineffective group was higher than that in markedly effective group. There was no much difference of the sex, age, body mass index, level of education, duration of disease, target knees, times of acupuncture, medications and syndrome differentiation among the groups. Conclusion: The curative effect of standard acupuncture in patients with knee osteoarthritis can be influenced by severity of Kellgren-Lawrence degree. To patients with severe knee osteoarthritis, satisfactory effects can hardly be achieved by merely standard acupuncture.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".