The efficacy and safety of Yijinjing exercise in the adjuvant treatment of ankylosing spondylitis
Bibliographic record
Abstract
BACKGROUND: Ankylosing spondylitis (AS) is a chronic systemic autoimmune disease with high disability rate. Conventional treatment regimens have long medication cycles and are associated with adverse reactions. Therapeutic exercise is also considered to be an effective treatment for AS. Evidence suggests that Yijinjing as a low-energy exercise has advantages in adjuncting AS, but there is a lack of standard clinical studies to evaluate its efficacy and safety. METHODS: This is a prospective randomized controlled trial to investigate the efficacy and safety of Yijinjing in the adjuvant treatment of AS. Approved by the Clinical Research Ethics Association of our hospital, patients were randomly divided into treatment or control groups in a ratio of 1:1. The treatment group received 4-month Yijinjing training on the basis of conventional treatment, while the control group received conventional treatment and maintained their current lifestyle. The outcome indicators included: activity index, functional ability, Bath Ankylosing Spondylitis Metrology Index, adverse reaction, etc. Finally, SPASS 22.0 software was used for statistical analysis of the data. DISCUSSION: This study evaluated the clinical efficacy of Yijinjing exercise in the adjuvant treatment of AS, and the results of our study will provide a reference for the clinical use of Yijinjing exercise as an effective complementary alternative for the treatment of AS.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".