Chasing “chasing the dragon” with MRI: leukoencephalopathy in drug abuse
Bibliographic record
Abstract
UNLABELLED: Spongiform leukoencephalopathy is a rare complication from inhalation of heated heroin vapour, a practice called "chasing the dragon". The MRI findings are considered pathognomonic, making MRI important for diagnosis. This is especially true in busy urban emergency departments where a variety of patients may present obtunded, unable or unwilling to provide a useful history. Even though the MR pattern of "chasing" toxicity is considered pathognomonic, there are mimickers. We compare the MRI findings of two classic cases of chasing leukoencephalopathy with one case of mimickery from cocaine exposure only. All three cases had diffuse symmetrical white matter changes. MR spectroscopy (MRS) in chasing patients showed increased lactic acid and myo-inositol, decreased N-acetyl aspartate and creatine, normal to slightly decreased choline, and normal lipid peak. MRS in the cocaine exposure patient showed marked increase in lactic acid and lipids. MR perfusion in one chasing patient was normal. IN CONCLUSION: (1) All three cases have MR findings suggestive of spongiform leukoencephalopathy. MRS may help differentiate toxicity due to inhaled heroin from other non-heroin related toxicities. (2) Discordance between perfusion and spectroscopy in one chasing patient adds evidence that the disease is due to impaired energy metabolism at the cellular level. (3) MR findings of spongiform leukoencephalopathy secondary to chasing heroin can progress despite apparent abstinence of the drug and during clinical improvement, suggesting the MR changes may represent an evolving injury.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".