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Record W4388673810 · doi:10.1136/bmjopen-2023-074423

Time trends and patterns in opioid prescription use following orthopaedic surgery in Ontario, Canada, from 2004/2005 to 2017/2018: a population-based study

2023· article· en· W4388673810 on OpenAlexafffundabout
Mayilée Cañizares, J. Denise Power, Anthony V. Perruccio, Christian Veillette, Nizar N. Mahomed, Y. Raja Rampersaud

Bibliographic record

VenueBMJ Open · 2023
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsArthritis SocietyUniversity Health Network
FundersArthritis SocietyCanadian Institutes of Health ResearchGovernment of Ontario
KeywordsMedicineMedical prescriptionOpioidOrthopedic surgeryChronic painPopulationElective surgeryAnesthesiaEmergency medicinePhysical therapySurgeryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: Increased use of opioids and their associated harms have raised concerns around prescription opioid use for pain management following surgery. We examined trends and patterns of opioid prescribing following elective orthopaedic surgery. DESIGN: Population-based study. SETTING: Ontario, Canada. PARTICIPANTS: Ontario residents aged 66+ years who had elective orthopaedic surgery from April 2004 to March 2018. PRIMARY AND SECONDARY OUTCOME MEASURES: Postoperative opioid use (short term: within 90 days of surgery, prolonged: within 180 days and chronic: within 1 year), specific opioids prescribed, average duration (days) and amount (morphine milligram equivalents) of the initial prescription by year of surgery. RESULTS: We included 464 460 elective orthopaedic surgeries in 2004/2005-2017/2018: 80% of patients used opioids within 1 year of surgery-25.1% were chronic users. There was an 8% increase in opioid use within 1 year of surgery, from 75.1% in 2004/2005 to 80.9% in 2017/2018: a 29% increase in short-term use and a decline in prolonged (9%) and chronic (22%) use. After 2014/2015, prescribed opioid amounts initially declined sharply, while the duration of the initial prescription increased substantially. Across categories of use, there was a steady decline in coprescription of benzodiazepines and opioids. CONCLUSIONS: Most patients filled opioid prescriptions after surgery, and many continued filling prescriptions after 3 months. During a period of general increase in awareness of opioid harms and dissemination of guidelines/policies aimed at opioid prescribing for chronic pain, we found changes in prescribing practices following elective orthopaedic surgery. Findings illustrate the potential impact of guidelines/policies on shaping prescription patterns in the surgical population, even in the absence of specific guidelines for surgical prescribing.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.059
GPT teacher head0.333
Teacher spread0.274 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations6
Published2023
Admission routes3
Has abstractyes

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