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Record W2977624748 · doi:10.12968/ijpn.2019.25.9.453

Opioid use disorder and chronic pain: challenges for palliative care practice

2019· article· en· W2977624748 on OpenAlexaff
Brenda Peters-Watral

Bibliographic record

VenueInternational Journal of Palliative Nursing · 2019
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsHealth Sciences Centre
Fundersnot available
KeywordsOpioid use disorderPalliative careChronic painMedicineAddictionCancer painPopulationPsychiatryOpioidSubstance abuseCancerIntensive care medicineNursingEnvironmental health

Abstract

fetched live from OpenAlex

Along with a well-documented increase in opioid use disorder (OUD) and a rapidly escalating rate of fatal overdose in North America, inadequate management of chronic pain remains a pervasive problem. The increasing number of individuals living with OUD also experience multiple cancer risk factors, which are related to their substance use, while people with cancer diagnoses have similar risks of current or past addiction as the general population. Recent pain guidelines focus on chronic non-cancer pain and do not include recommendations for cancer pain management. Managing cancer pain at the end of life is more challenging in people with current or past substance use disorder (SUD), especially OUD. Addressing these challenges requires confronting stigmas and stereotypes, building knowledge among palliative care providers and assessing the risks and benefits of opioids for pain management on an individual basis in order to continue to provide the holistic care.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.007
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0040.005
Open science0.0010.007
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.039
GPT teacher head0.374
Teacher spread0.335 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations4
Published2019
Admission routes1
Has abstractyes

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