The Safety of Pediatric Acupuncture: A Systematic Review
Bibliographic record
Abstract
CONTEXT: Acupuncture is increasingly used in children; however, the safety of pediatric acupuncture has yet to be reported from systematic review. OBJECTIVE: To identify adverse events (AEs) associated with needle acupuncture in children. METHODS: Eighteen databases were searched, from inception to September 2010, irrespective of language. Inclusion criteria were that the study (1) was original peer-reviewed research, (2) included children from birth to 17 years, inclusively, (3) involved needle acupuncture, and (4) included assessment of AEs in a child. Safety data were extracted from all included studies. RESULTS: Of 9537 references identified, 450 were assessed for inclusion. Twenty-eight reports were included, and searches of reference lists identified 9 additional reports (total: 37). A total of 279 AEs were identified, 146 from randomized controlled trials, 95 from cohort studies, and 38 from case reports/series. Of the AEs, 25 were serious (12 cases of thumb deformity, 5 infections, and 1 case each of cardiac rupture, pneumothorax, nerve impairment, subarachnoid hemorrhage, intestinal obstruction, hemoptysis, reversible coma, and overnight hospitalization), 1 was moderate (infection), and 253 were mild. The mild AEs included pain, bruising, bleeding, and worsening of symptoms. We calculated a mild AE incidence per patient of 168 in 1422 patients (11.8% [95% confidence interval: 10.1-13.5]). CONCLUSIONS: Of the AEs associated with pediatric needle acupuncture, a majority of them were mild in severity. Many of the serious AEs might have been caused by substandard practice. Our results support those from adult studies, which have found that acupuncture is safe when performed by appropriately trained practitioners.
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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 | 0.009 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".