Bibliographic record
Abstract
Abstract Cerebral palsy (CP) has been defined as a disorder affecting body movement, motor skills and postural control. It is caused by damage to the developing fetal or infant brain during pregnancy, at birth or during the first 3–5 years of life. Patients with CP often seek out CAM treatments, such as acupuncture. The objective of this study was to examine the evidence for the safety and effectiveness of acupuncture for CP. Four databases (Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, EMBASE and MEDLINE) were searched for RCTs and systematic reviews (SRs) of acupuncture and CP. Titles and abstracts were screened; articles meeting the selection criteria were retrieved in full. Studies were included if they were SRs or RCTs and evaluated the effectiveness of an acupoint stimulation technique in children with CP. Only English and Chinese language papers were included. The search identified seven studies; six RCTs and one quasi‐RCT that included acupuncture in at least one group. Three of the RCTs compared different types of acupuncture, while four compared acupuncture to another active intervention, including osteopathy, massage, music and play. The evidence of safety and effectiveness for acupuncture and cerebral palsy is difficult to interpret due to poor reporting. When the effectiveness of a treatment is unknown, data about its safety are paramount. With regards to paediatric needle acupuncture, there is reasonable evidence to suggest that it is safe in trained hands. However, the safety of acupoint injection is unknown, particularly when foreign proteins are being injected.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 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".