Refining cause of death attribution among opioid, opioid‐stimulant and stimulant acute toxicity deaths
Bibliographic record
Abstract
BACKGROUND AND AIMS: Deaths attributed to a combination of opioids and stimulants have risen dramatically in recent years, largely attributed to fentanyl, yet little is understood about which drug class is primarily responsible. Attributing death to acute substance toxicity is complex and lacks clear standards. We aimed to determine whether additional causes of death and other significant conditions among deaths attributed to fentanyl were similar regardless of stimulant involvement, and distinct from deaths involving stimulants without opioids. DESIGN: Cross-sectional analysis using records from the California Electronic Death Registration System. SETTING AND CASES: Unintentional acute toxicity deaths involving fentanyl or stimulants (methamphetamine or cocaine) occurring in San Francisco, USA, during 2013-2023. MEASUREMENTS: We compared demographic characteristics and causes of death or other significant conditions (cardiovascular, cerebrovascular, other medical cause, or no other additional cause) among five mutually exclusive groups of deaths: stimulants without opioids (stimulant-only), fentanyl with stimulants (fentanyl-stimulant), fentanyl without stimulants (fentanyl-only), other opioids (e.g., heroin, oxycodone) with stimulants ("other opioid-stimulant"), and other opioids without stimulants ("other opioids-only"). We conducted separate unadjusted and adjusted multivariable logistic regression models for each outcome (cardiovascular, cerebrovascular, other medical, or no additional cause). The primary analysis included results for the fentanyl groups. FINDINGS: Of 4475 deaths attributed to acute opioid and/or stimulant toxicity, 24% involved stimulants-only, 45% fentanyl-stimulants, and 12% fentanyl-only; the remaining 20% involved other opioids. Stimulant-only decedents were the oldest (mean age 54 years), followed by fentanyl-stimulant (47 years) and fentanyl-only (44 years; p < 0.001 for all). The adjusted odds of having cardiovascular, cerebrovascular, or other medical causes of death (adjusted odds ratios [aORs] from 0.03 to 0.52, with 95% confidence intervals [CIs] from 0.01 to 0.68) were lower and the odds of no additional cause of death (aORs from 2.53 to 3.31, with 95% CIs from 2.00 to 3.40) were higher for both groups of deaths involving fentanyl compared with deaths attributed to stimulants-only. There were no statistically significant differences in causes of death when comparing fentanyl-only with fentanyl-stimulant deaths. Findings were similar for other opioid deaths. CONCLUSION: In San Francisco, USA, causes of death and other significant condition characteristics among deaths attributed to fentanyl appear to be similar regardless of the involvement of stimulants, but are markedly different from deaths involving stimulants without opioids. When reporting on drug-related mortality and developing interventions, deaths attributed to a combination of fentanyl and stimulants may be appropriately considered in the context of opioid overdose prevention, while deaths attributed to stimulants without opioids may require a response focused on preventing and treating underlying chronic medical conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".