Comparative Observational Study on the Effects of Intra-articular Hominis Placenta Pharmacopuncture and Acupoint Hominis Placenta Pharmacopuncture for Knee Osteoarthritis Patients
Bibliographic record
Abstract
The aim of this case report was to observe the effects of intra-articular hominis placenta pharmacopuncture (HPP). Based on the medical records patients who received intra-articular treatment or received acupoint pharmacopuncture treatment, a comparison was made. There were 35 patients who were hospitalized for degenerative osteoarthritis of the knee joint from the 1st October 2019 to 26th September 2020. There were 14 patients who were treated with HPP in the intra-articular joint space (Group A), and 14 patients who were treated with HPP at specific acupoints (Group B). The outcome effects were measured using the Korean Western Ontario and Mc (KWOMAC) the visual analog scale (VAS) before the first treatment, and after the fifth treatment. The KWOMAC (p < 0.001) and the VAS scores (p < 0.001) in Groups A and B significantly improved after treatment compared with before treatment. When comparing Group A improvement with Group B improvement using the KWOMAC there was no statistically significant difference however, when using the VAS scores, Group A treatment was statistically more effective compared with Group B (p = 0.002). This study indicated that HPP may be an effective treatment for knee osteoarthritis. Moreover, intra-articular HPP may be more effective than acupoint HPP for knee osteoarthritis.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".