Natural Health Product–Drug Interaction Causality Assessment in Pediatric Adverse Event Reports Associated with Attention-Deficit/Hyperactivity Disorder Medication
Bibliographic record
Abstract
Background: Some pediatric patients with attention-deficit/hyperactivity disorder (ADHD) use natural health products (NHPs) such as herbal remedies. Although herbal remedies are generally considered to be safe when they are used appropriately, they may contain active components that can interact with medications being used concurrently, with potential for NHP-drug interactions leading to adverse events. Objectives: The objectives of this study were (1) to identify adverse event reports (AERs) involving commonly used herbal remedies and ADHD prescription medicines in children and adolescents; (2) to evaluate the quality of collected AERs; and (3) to assess whether NHP-drug interactions can be causally linked to reported adverse events. Methods: We systematically searched the FDAble database ( FDAble.com ) for herbal remedies commonly used by patients (4–18 years old) also taking ADHD drugs from 1997 to 2015. We assessed the completeness of the AERs and used three causality assessment tools modified for NHPs (Naranjo Adverse Drug Reaction Probability Scale, HORN Drug Interaction Probability Scale, and World Health Organization Uppsala Monitoring Centre Scale). Results: Of the 23 identified AERs involving both an herbal remedy and an ADHD prescription medication, most involved multiple (>3) substances with inadequate detail to assess multiple potential interactions. Following data extraction and evaluation of completeness, five AERs involving only one herbal remedy and one ADHD medication were evaluated for causality. An NHP-drug interaction was assessed to be probable in one case and to be possible in another. Both these reports involved a methylphenidate formulation and St. John's wort. Conclusions: Eighteen of the 23 identified AERs involving both an herbal remedy and an ADHD drug also involved other multiple ingredient products. The reporting quality was poor for the five AERs examined. Further research is needed to study the interaction between St. John's wort and methylphenidate.
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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 | 0.044 | 0.115 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".