Kratom exposures managed by the British Columbia poison centre, 2012–2019: a descriptive analysis
Bibliographic record
Abstract
BACKGROUND: Kratom, a plant indigenous to Southeast Asia, which has been used both recreationally and in the treatment of pain and opioid dependence, has received little scrutiny in the United States and almost none in Canada. We analyzed calls to the British Columbia poison centre to describe caller-declared exposures to kratom and the acute health effects of these exposures. METHODS: For this descriptive analysis, we accessed electronic records, including transcriptions and extracted variables, of calls specifying kratom exposure managed by the BC Drug and Poison Information Centre (DPIC) from 2012 to 2019. We describe changes in case numbers, reasons for exposure, concurrent drug exposures and clinical outcomes over the study period. RESULTS: = 17, 53%). A total of 27 cases (84%) involved ingestion, with online distributors and local stores named as sources of procurement. A concurrent drug exposure was identified in 13 (41%) cases. There were no deaths; in 1 case, the exposed individual was intubated to manage agitation following kratom withdrawal. INTERPRETATION: We observed a steady increase in kratom-related poison centre calls from 2012 to 2019, especially in young adult males. Rising call numbers may reflect increasing availability of kratom and may be a consequence of BC's opioid crisis, with kratom used by some to lessen symptoms of opioid withdrawal.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".