A scoping review of the evidence for efficacy of acupuncture in companion animals
Bibliographic record
Abstract
Acupuncture has become increasingly popular in veterinary medicine. Within the scientific literature there is debate regarding its efficacy. Due to the complex nature of acupuncture, a scoping review was undertaken to identify and categorize the evidence related to acupuncture in companion animals (dogs, cats, and horses). Our search identified 843 relevant citations. Narrative reviews represented the largest proportion of studies (43%). We identified 179 experimental studies and 175 case reports/case series that examined the efficacy of acupuncture. Dogs were the most common subjects in the experimental trials. The most common indication for use was musculoskeletal conditions, and the most commonly evaluated outcome categories among experimental trials were pain and cardiovascular parameters. The limited number of controlled trials and the breadth of indications for use, outcome categories, and types of acupuncture evaluated present challenges for future systematic reviews or meta-analyses. There is a need for high-quality randomized controlled trials addressing the most common clinical uses of acupuncture, and using consistent and clinically relevant outcomes, to inform conclusions regarding the efficacy of acupuncture in companion animals.
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 | 0.012 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".