[Current status of application of acupuncture in low back pain guidelines].
Bibliographic record
Abstract
OBJECTIVE: To systematically review the current status of application of acupuncture in low back pain guidelines. METHODS: The computer retrieval was conducted in PubMed, Cochrane Library, EMbase, China Journal Full Text Database (CNKI), China Biomedical Literature Database (CBM), VIP, Wanfang, guidelines databases, and the official websites of WHO and academic organizations (American Pain Society, American College of Physicians, etc.). After screening, the basic information and acupuncture-related issues in the guidelines that met the inclusion criteria were extracted and compared by using Excel software. RESULTS: A total of 35 low back pain guidelines were included. ① One guideline was published before 2000, 16 guidelines were published from 2000 to 2010, and 18 guidelines were published from 2011 to 2017; 17 guidelines were published by the United States, 4 by Canada and China, 2 by New Zealand, the United Kingdom, and Europe, and 1 by Netherlands, Philippines, Denmark and Italy. ② Twenty-three guidelines were evidence-based guidelines, which was developed mainly by system review, meta-analysis and expert consultation, involving diagnosis, treatment, primary care of low back pain. ③ Acupuncture was mentioned in 23 guidelines, of them, 7 guidelines recommended acupuncture, 6 guidelines indicated that acupuncture might be considered under certain conditions such as combined with other therapies or patients were interested in acupuncture, however, 10 guidelines did not recommended acupuncture for low back pain. CONCLUSION: The guidelines of low back pain are mainly developed by Europe countries and the United States, and the majority is published in the last 20 years. Among them, 20% of the guidelines have recommend acupuncture for low back pain.
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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 | 0.010 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".