The Effects of Korean Medicine Treatment for Meniscus Tears: A Retrospective Chart Review
Bibliographic record
Abstract
Changes in symptoms and dysfunction related to meniscus tears following the use of Korean medicine for ≥ 4 days were studied. The medical charts of 53 cases of diagnosed meniscus tears (magnetic resonance imaging) with an admission Numeric Rating Scale (NRS) score ≥ 4, between 2017 and 2022 were retrospectively reviewed. Treatments included acupuncture, pharmacopuncture, herbal treatment, Chuna therapy, and physiotherapy. The NRS, Western Ontario and McMaster Universities Osteoarthritis Index, and European Quality of Life 5 Dimensions were performed at admission and discharge. There were 42 females and 11 males in this study. Patients were more likely to be in their 60s (38.18%), have an unknown etiology (81.13%), and have complex tears (50.94%). After receiving a combination of alternative Korean medicine during hospitalization, the mean NRS score improved from 6.82 ± 1.19 to 3.66 ± 1.83 (p < 0.001), the Western Ontario and McMaster Universities Osteoarthritis Index score improved from 46.47 ± 20.99 to 37.98 ± 19.23 (p < 0.001), and the mean European Quality of Life Five Dimensions score improved from 0.61 ± 0.18 to 0.68 ± 0.14 (p < 0.001) after treatment. These results suggest that Korean medicine treatment of meniscus tears alleviated pain and improved physical function.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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".