The Anatomy of Spontaneously Reported Dietary Supplement Adverse Events and a Standardized Process to Score and Interpret Collected Events
Bibliographic record
Abstract
Enforcement of the 2006 Dietary Supplement and Nonprescription Drug Consumer Protection Act (DSNDCPA) began in December 2007. FDA published guidance documents regarding compliance and reporting of “serious” events but there has been no guidance on how “serious” and “non-serious” reported events are being evaluated by FDA or others so as to insure that products are meeting expectations of safety, warranting consumer confidence. Experience to date demonstrates a high variability in quality and integrity of reported incidents and there is no recognized method regarding scoring of events by experts so as to assess potential associations between alleged adverse events and product use. Without such a scoring and evaluation system, collected data represents unconfirmed allegations of product use and injury, rendering benchmarking between and across product lines an exercise in futility. The SafetyCall International Poison Center, an academically affiliated, multidisciplinary, triple licensed medical practice composed of clinicians with specific expertise in clinical medicine and toxicology, natural product pharmacology and consumer product safety has designed a system to score spontaneously reported adverse incidents involving botanicals containing dietary supplements. Using six common parameters to gauge association including expectedness, temporality, biologic plausibility, de-challenge, re-challenge, and consideration of confounding variables, a standardized scoring system has been developed. The system was successfully piloted with a proprietary blend dietary supplement and provides a means for manufacturers to benchmark their product safety experience. Description and application of the scoring system will be presented along with representative scoring of actual adverse events represented in the new FDA adverse event database.
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 | 0.023 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".