ArticleDrug and alcohol dependence2026
Spatiotemporal clustering of state-level opioid, opioid-stimulant, and opioid-benzodiazepine polysubstance deaths across the U.S.: Hierarchical agglomerative clustering analysis.
Article in Drug and alcohol dependence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Daily polysubstance use associated with HIV, HCV, and non-fatal overdose among people who inject drugs: A latent class analysis using nationwide data.Drug and alcohol dependence · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundPolysubstance use continues to complicate the US overdose landscape, with over 107,000 lives lost to drug overdoses in 2022. The present study uses hierarchical agglomerative clustering to identify distinct spatiotemporal profiles of opioid-only, opioid-stimulant, and opioid-benzodiazepine overdose deaths.
methodsWe used de-identified data sourced from the CDC's WONDER Multiple Cause of Death file, covering the period from 2004 to 2022. Hierarchical Agglomerative Clustering was used to classify and assign age-adjusted mortality rate (AAMR) trends for opioid-only, opioid-stimulant, and opioid-benzodiazepine combinations into distinctive clusters based on their temporal and spatial similarities using the dynamic time warping (DTW) metric.
resultsThe opioid-only, opioid-stimulant, and opioid-benzodiazepine clusters each yielded four clusters. The Opioid-only clusters were characterized by states with AAMRs showing the following trajectory patterns of change over time: lower-level, gradual increase (n = 22 states, 43.14%), delayed acceleration (post-2015) (n = 10 states, 19.61%), early rapid increase (n = 18 states, 35.29%), and a higher-level, accelerating trajectory containing only West Virginia. The Opioid-Stimulant clusters were characterized by states with lower-level, gradual increase (n = 33 states, 64.71%), delayed acceleration (post-2015) (n = 9 states, 17.65%), early rapid increase (n = 8 states, 15.69%), and West Virginia, which had a higher-level, accelerating trajectory. The Opioid-Benzodiazepine clusters were characterized as low-level, minimal change (n = 27 states, 52.94%), steady increase (n = 18; 35.29%), early rapid increase with a recent decline (n = 5, 9.80%), and West Virginia, which was characterized as having a higher-level, irregular trajectory denoting substantial variability.
conclusionsThese findings reveal significant spatial and temporal variation, with West Virginia consistently emerging as an outlier with the highest AAMR. These findings further underscore the need for region-specific interventions to curb the growing opioid crisis.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.