A Novel Treatment Method for Ankylosing Spondylitis Combined With Sacroiliac Joint Bone Marrow Edema
Bibliographic record
Abstract
Objective: To investigate whether high-energy extracorporeal shock wave therapy (ESWT) combined with conventional oral medicine as a potential novel therapeutic approach for the treatment of ankylosing spondylitis (AS)combined with sacroiliac joint bone marrow edema. Materials & Methods: 40 patients were divided into two groups and were treated with or without ESWT in combination with conventional oral medicine. A visual analog scale (VAS) score of spinal pain, as well as indicators of spinal mobility, Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and Bath Ankylosing Spondylitis Functional Index (BASFI) scores, inflammatory index (C-reactive protein, blood cell sedimentation rate), and other indicators were compared between the two groups. The Spondyloarthritis Research Consortium of Canada (SPARCC) scoring system was used to evaluate pain and structural damage in the sacroiliac joint. Results: (1) After one month of treatment (T1), VAS, BASDAI, BASFI, and SPARCC scores were lower in both groups than at the start of treatment (T0) (P < 0.05), with greater decreases observed in the treatment group (P < 0.05). (2) Also, at T1, indicators of spinal mobility for the two groups were improved (P < 0.05). (3) ESR and C-reactive protein levels for the two groups decreased significantly at T1 versus T0 (P < 0.05). Conclusion: ESWT combined with oral medication can significantly relieve pain and improve clinical functional symptoms for patients with AS. It can also reduce sacroiliac joint bone marrow edema and control the inflammatory reaction in the sacroiliac joint, which represents a novel, effective, reliable, and safe clinical treatment therapeutic method. Keywords: Ankylosing spondylitis, Sacroiliac joint, extracorporeal shock wave therapy, oral medicine.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".