Outpatient Treatment of Chronic Designer Benzodiazepine Use: A Case Report
Bibliographic record
Abstract
BACKGROUND: Novel psychoactive substances, such as designer benzodiazepines unapproved for therapeutic purposes, are an emerging concern worldwide. They have unknown or unpredictable pharmacological properties. Using a case example, we discuss the use of "Xanax bars," which now generally do not contain the pharmaceutical alprazolam. We describe the difficulty in detecting these substances and the development of a use disorder including adverse outcomes such as seizures when stopped. The evidence for management is anecdotal. CASE: We describe the case of a male of approximately 25 years of age with alcohol and sedative-hypnotic use disorder related to illicit "Xanax bars," whose point of care urinalysis did not identify benzodiazepines and whose broad-spectrum urinalysis identified the presence of flualprazolam, a novel designer benzodiazepine. He suffered a subacute withdrawal seizure and responded to treatment with loading doses of diazepam and naltrexone. DISCUSSION: Although previous literature has focused on poisoning and intoxication (including coma), there are few studies examining treatment options for chronic designer benzodiazepine use. Standard approaches, such as conversion to a longer-acting benzodiazepine with a prolonged taper, are risky with designer benzodiazepines due to the unknown level of tolerance and risk of overdosing the patient. Illicit "Xanax" is not equivalent to prescribed alprazolam and cannot be converted and tapered. To be cautious, supervised benzodiazepine tapers or anticonvulsants should be explored as treatment strategies, based on their use in pharmaceutical benzodiazepine use disorders. Inpatient acute withdrawal management should be considered, and anticonvulsants may play a role in the first 4 to 6 weeks of treatment.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| 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".