[Electronic focusing high-nergy extracorporeal shockwave combined with conventional oral medicine for the treatment of ankylosing spondylitis].
Bibliographic record
Abstract
OBJECTIVE: To observe the progress of disease activity and sacroiliac joint imaging in patients with ankylosing spondylitis treated by extracorporeal shockwave combined with conventional oral medicine, and find a new safe and effective therapeutic method. METHODS: The clinical data of 30 patients with ankylosing spondylitis treated from January 2018 to December 2018 were retrospectively analyzed. Including 20 males and 10 females, aged from 18 to 50 years with an average of (34.50±9.60) years. All 30 patients had different degrees of sacroiliac joint bone marrow edema on MRI before treatment. Thirty patients were divided into treatment group and control group according to different treatment methods. Among them, 15 cases in control group were treated with non-steroidal anti-inflammatory drugs and sulfasalazine enteric-coated tablets, for the 15 cases in treatment group, in addition to oral medicine in line with control group, electronic focusing high-energy extracorporeal shockwave therapy was added. The course of disease, age, pre- and post-treatment erythrocyte sedimentation rate, C-reactive protein in the two groups were analyzed; and visual analogue scale (VAS) and spondyloarthritis research consortium Canada (SPARCC) scoring system were used to evaluate the pain of the sacroiliac joint and the structural damage of the sacroiliac joint;Bath ankylosing spondylitis disease activity index (BASDAI) was calculated. RESULTS: All patients were followed up for at least 3 months. One month after treatment, VAS, and SPARCC scores in treatment group were significantly better than in control group (P<0.05). After 1 month of treatment, there was no significant difference in BASDAI, erythrocyte sedimentation rate and C-reactive protein between two groups(P>0.05). VAS, BASDAI, SPARCC, erythrocyte sedimentation rate, and C-reactive protein of all patients after treatment were significantly improved compared with those before treatment (P< 0.01). CONCLUSION: Electronic focusing high-energy extracorporeal shockwave combined with conventional oral medicine in the treatment of ankylosing spondylitis has a good clinical effect in rapidly relieving pain, improving disease activity, and preventing imaging progress. In addition, it is safe and non-invasive, which is worthy of clinical application.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".