The surge of bromazolam‐related fatalities replacing other novel designer benzodiazepines‐related fatalities in San Francisco
Bibliographic record
Abstract
BACKGROUND AND AIM: Bromazolam, a novel designer benzodiazepine (NBD), exhibits potent sedative, hypnotic and anxiolytic effects, raising concerns regarding its potential for misuse and fatal outcomes, particularly when combined with opioids such as fentanyl. Despite limited documented fatalities globally, its use poses a significant threat, exacerbated by under-reporting and a lack of routine testing. This study analysed NBD-related deaths in a major US city over a 4-year period. METHODS: Analysis of accidental overdose deaths involving NBDs in San Francisco, CA, USA from 2020 to 2023, was performed utilizing medico-legal death investigations including comprehensive forensic toxicology, pathology and demographic information. San Francisco conducts thorough investigations into all non-natural and sudden unexpected deaths, including routine alcohol and drug testing of decedents under its jurisdiction, including etizolam, flualprazolam, flubromazolam and bromazolam analysis. RESULTS: There was a sudden surge in bromazolam-related deaths, with 44 fatalities documented in 2023, contrasting with relatively fewer deaths related to other NBDs. Bromazolam fatalities frequently involved co-ingestion with opioids, primarily fentanyl, and stimulants such as methamphetamine and cocaine. Demographic characteristics indicated a predominance of males, with a significant proportion lacking fixed addresses. Blood concentrations of bromazolam increased during the study period, suggesting heightened availability and/or purity in the community. CONCLUSION: There was a surge in bromazolam-related deaths during 2023 in San Francisco, CA, USA, contrasting with relatively stable numbers of deaths associated with other NBDs over the preceding years. The findings underscore the urgency for enhanced death investigation, testing and reporting to facilitate targeted harm reduction strategies for individuals at risk of bromazolam-related morbidity and mortality.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".