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Record W3157480201 · doi:10.1097/yco.0000000000000712

The opioid overdose crisis as a global health challenge

2021· review· en· W3157480201 on OpenAlexaff
Michael Krausz, Jean N. Westenberg, Kimia Ziafat

Bibliographic record

VenueCurrent Opinion in Psychiatry · 2021
Typereview
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineDrug overdoseOpioid overdoseConsumption (sociology)FentanylEnvironmental healthOpioidHealth careMedical emergencyBusinessEconomic growthPoison controlEconomicsPharmacology(+)-Naloxone

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: To assess the current state of the opioid overdose crisis along three major axes: drug markets and patterns of use, the effectiveness of systems of care, and international developments. RECENT FINDINGS: Overdose is a major contributor to mortality and disability among people who use drugs. The increasing number of opioid overdoses in North America especially is an indication of changing drug markets and failing regional systems of care. Globally, we see three clusters of overdose prevalence: (1) a group of countries led by the United States with historically high rates of opioid overdose, (2) a group of countries with increasing rates within a concerning range, (3) a group with very low rates. The contamination of street drugs, the quality and accessibility of treatment, and the overall system of care all contribute to the prevalence of overdose. SUMMARY: Drug markets and pattern of consumption in parts of the world are shifting towards contamination and opioids like fentanyl as the drug of choice, which dismantles insufficient and largely ineffective systems of care. Furthermore, outside of North America, more countries like Estonia, Lithuania, Sweden, Finland, and Norway show very concerning numbers. Without a consistent system response, effects will be devastating.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.814
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.069
GPT teacher head0.465
Teacher spread0.396 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations94
Published2021
Admission routes1
Has abstractyes

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