Adverse events associated with paediatric use of complementary and alternative medicine: Results of a Canadian Paediatric Surveillance Program survey
Bibliographic record
Abstract
BACKGROUND: Despite many studies confirming that the use of complementary and alternative medicine (CAM) by children is common, few have assessed related adverse events. OBJECTIVE: To conduct a national survey to identify the frequency and severity of adverse events associated with paediatric CAM use. METHODS: Survey questions were developed based on a review of relevant literature and consultation with content experts. In January 2006, the Canadian Paediatric Surveillance Program distributed the survey to all paediatricians and paediatric subspecialists in active practice in Canada. RESULTS: Of the 2489 paediatricians who received the survey, 583 (23%) responded. Respondents reported that they asked patients about CAM use 38% of the time and that patients disclosed this information before being questioned only 22% of the time. Forty-two paediatricians (7%) reported seeing adverse events, most commonly involving natural health products, in the previous year. One hundred five paediatricians (18%) reported witnessing cases of delayed diagnosis or treatment (n=488) that they attributed to the use of CAM. CONCLUSION: While serious adverse events associated with paediatric CAM appear to be rare, delays in diagnosis or treatment seem more common. Given the lack of paediatrician-patient discussion regarding CAM use, our findings may under-represent adverse events. A lack of reported adverse events should not be interpreted as a confirmation of safety. Active surveillance is required to accurately assess the incidence, nature and severity of paediatric CAM-related adverse events. Patient safety demands that paediatricians routinely inquire about the use of CAM.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".