Acupuncture for fibromyalgia: An evidence map 针灸治疗纤维肌痛:证据图
Bibliographic record
Abstract
The body of research on acupuncture as a treatment strategy for fibromyalgia (FM) is steadily growing. This evidence map identifies, describes, and summarizes the current status of studies conducted to evaluate the efficacy of acupuncture for FM, identify research gaps, and provide information that could guide the design of future studies. Seven electronic databases–Cochrane Library, PubMed, Embase, China Biomedical Literature Database, VIP, Wanfang Database, and Chinese National Knowledge Infrastructure–were searched for relevant articles on acupuncture for FM. The search period was from the dates of inception of the databases to December 19, 2022. Original clinical studies and systematic reviews on the use of acupuncture-related modalities for the treatment of FM were included. The basic information, quality assessments, and evidence maps of the included studies are presented as charts and bubble plots. The quality assessment tools used for evaluating the different types of studies included in the present study were Cochrane Collaboration's tool, Canadian Institute of Health Economics quality appraisal tool, and A MeaSurement Tool to Assess systematic Reviews 2. Fifty studies were included in this study. Of these, 39 (78.00%) were randomized controlled trials (RCTs), 6 (12.0%) were case series, and 5 (10.0%) were systematic reviews. The included studies focused on manual acupuncture and conventional treatment in the treatment and control groups, respectively. The outcomes analyzed in the RCTs included pain (94.9%), sleep quality (46.2%), depression (46.2%), physical function (46.2%), stiffness (35.9%), well-being (35.9%), work status (35.9%), anxiety (33.3%), fatigue (33.3%), quality of life (17.9%), and overall effective rate (10.3%). The methodological quality of most of the studies was low or critically low regardless of the study design. In most studies, the therapeutic effect of acupuncture was significantly superior to that of the comparator. This evidence map suggests that acupuncture-related modalities may be promising options for FM management. However, various studies on this topic have a high risk of bias or are of low quality. Further evidence-based research should be conducted to rigorously examine the efficacy of acupuncture for FM and promote generalizability of the findings.
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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 | 0.017 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.039 | 0.031 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| 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".