Bibliographic record
Abstract
Objectives: The knee pain is the main reason of getting acupuncture treatment. In order to have confidence in the results of a study, it is necessary to establish that questionnaire is both valid and reliable in questionnaire related study. The aim of this study was to review the instruments that are currently in sue for assessing the knee joint. Methods: A literature study was performed to choose appropriate scales for assessment for pain and the function of the knee. Theoretically based scales were selected for review. Therefore, 18 scales for knee and 9 scale for pain were reviewed. the status of scales involved in knee treatment of acupuncture throughout several countries was evaluated. Results & Conclusion: Lysholm Knee Scoring Scale, Cincinnati knee rating system(CKRS) are adequate for ligament injury in knee. International Knee Documentation Committee scoring system(IKDC) may become a publication requirement for journals in view of the international standing of the committee. The available outcome measure for use in osteoarthritis are Western Ontario and McMaster Universities Osteoarthritis Index(WOMAC), Lequesne Functional Severity Index(LFI) and Knee Injury and Osteoarthritis Outcome Score(KOOS), and in rheumatoid arthritis are McMaster-Toronto Arthritis patient function preference questionnaire(MACTAR), Quality of Life-Rheumatoid Arthritis Scale(QoL-RA Scale). Visual analog scale(VAS), verbal rating scale(VRS) are commonly used for the standard pain scale. For long term follow-up study The Medical Outcomes Study Short Form-36(SF-36), Arthritis Impact Measurement Scales(AIMS), Health Assessment Questionnaire(HAQ) should be included. Each measurement has its own composition and characteristics. Their validity, reliability, responsiveness and practical characteristics were already evaluated. We found 20 domestic and 28 overseas papers about knee treatment using acupuncture assessed with knee scales.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".