Chasing the dragon - characterizing cases of leukoencephalopathy associated with heroin inhalation in British Columbia
Bibliographic record
Abstract
An association between leukoencephalopathy, a disease of the white matter of the brain, and smoking heroin is well recognized. This paper describes 27 cases of leukoencephalopathy identified in two cities in British Columbia, Canada 2001-2006; the largest number of geographically and temporally defined reported cases in North America.Twenty cases of leukoencephalopathy were identified in and around Vancouver with onset dates December 2001 to July 2003; seven further cases were identified in Victoria September 2005-August 2006. Twenty (74%) of all cases were male, two couples were reported and eleven cases (55%) had Asian ethnicity. One case reported smoking heroin on a single occasion and developed mild symptoms; all other cases were hospitalized. Thirteen (48%) cases died; all had smoked heroin for a minimum of 3 years. Testing of one available heroin sample identified no substance other than common cutting agents.Although a specific etiology was not identified our study supports the theory of an intermittent exposure to a toxic agent added to the heroin or a combustion by-product. It also suggests a dose response effect rather than genetic predisposition. Collaboration with public health, health professionals, law enforcement and persons who use illegal drugs, will facilitate the early identification of cases to enable timely and complete follow-up including obtaining samples. Testing of implicated heroin samples may allow identification of the contaminant and therefore prevent further cases. It is therefore important to ensure key stakeholders are aware of our findings.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".