Adverse events associated with paediatric massage therapy: a systematic review
Bibliographic record
Abstract
INTRODUCTION: Massage therapy (MT) is frequently used in children. No study has systematically assessed its safety in children and adolescents. We systematically review adverse events (AEs) associated with paediatric MT. METHODS: We searched seven electronic databases from inception to December 2018. We included studies if they (1) were primary studies published in a peer-reviewed journal, (2) involved children aged 0-18 years and (3) a type of MT was used for any indication. No restriction was applied to language, year of publication and study design. AEs were classified based on their severity and association to the intervention. RESULTS: Literature searches identified 12 286 citations, of which 938 citations were retrieved for full-text evaluation and 60 studies were included. In the included studies, 31 (51.6%) did not report any information on AEs, 13 (21.6%) reported that no AE occurred and 16 studies (26.6%) reported at least one AE after MT. There were 20 mild events (grade 1) that resolved with minimal intervention, 26 moderate events (grades 2-3) that required medical intervention, and 18 cases of severe AEs (grades 4-5) that resulted in hospital admission or prolongation of hospital stay; of these, 17 AEs were volvulus in premature infants, four of which were ultimately fatal events. CONCLUSION: We identified a range of AEs associated with MT use, from mild to severe. Unfortunately, the majority of included studies did not report if an AE occurred or not, leading to publication bias. This review reports an association between abdominal massage with volvulus without malrotation in preterm infants; it is still to be defined if this is casual or not, but our findings warrant caution in the use of abdominal massage in preterm infants.
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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 | 0.007 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".