Burns from illegal cannabis oil manufacturing: a case series
Bibliographic record
Abstract
BACKGROUND: The increasing consideration of cannabis legalization in Canada and the United States has motivated physicians to assess its prospective impact on the health care system. Health care providers in the burns community are concerned about injuries sustained as a result of the illegal manufacturing of cannabis oil because it involves highly flammable reagents. METHODS: We report a retrospective case series of patients with cannabis oil burns (identified by evidence of combustion during cannabis oil manufacturing) treated from April 2012 to March 2014 at the Foothills Medical Centre in Calgary, Alberta, Canada. We compare the characteristics of these patients with those of patients admitted over the same period with any burns. RESULTS: We found that 12 (out of 161 patients) admitted over the review period sustained burns from cannabis oil manufacturing. Compared with patients in the total burn group, patients with cannabis oil burns were younger (75% and 48% were younger than 41 years in the group with cannabis oil burns and the total burn group, respectively), were more likely to be male (83% in the group with cannabis oil burns v. 74% in the total burn group) and sustained burns over a larger percentage of their total body surface area (24% v. 9%). Patients with cannabis oil burns also required extensive surgical management (skin grafting in 75% of cases) and spent a substantial amount of time (mean 32 d) in the burn unit. INTERPRETATION: Burns from illegal cannabis oil manufacturing are large, require extensive management and involve younger patients than burns in general. Given that the frequency of cannabis oil burns may increase in Canada after legalization, Canadian burn centres are encouraged to monitor and report on cases with this injury mechanism.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".