Association Between Socio-Demographic andHealth Functioning Variables Among Patientswith Opioid Use Disorder Introduced byPrescription: A Prospective Cohort Study
Bibliographic record
Abstract
Background: Prescription opioid misuse in Canada has become a serious public health concern and has contributed to Canada’s opioid crisis. There are thousands of Canadians who are currently receiving treatment for opioid use disorder, which is a chronic relapsing disorder with enormous impact on individuals and society. Objectives: The aim of this study was to compare the clinical and demographic differences between cohorts of patients who were introduced to opioids through a prescription and those introduced to opioids for non-medical purposes. Study Design: This was an observational, prospective cohort study. Setting: The study took place in 19 Canadian Addiction Treatment Centres across Ontario. Methods: We included a total of 976 participants who were diagnosed with Opioid Use Disorder and currently receiving methadone maintenance treatment. We excluded participants who were on any other type of prescription opioid or who were missing their 6-month follow-up urine screens. We measured the participants’ initial source of introduction to opioids along with other variables using the Maudsley Addiction Profile. We also measured illicit opioid use using urine screens at baseline and at 6-months follow-up. Results: Almost half the sample (n = 469) were initiated to opioids via prescription. Women were more likely to be initiated to opioids via a prescription (OR = 1.385, 95% CI 1.027-1.866, P = .033). Those initiated via prescription were also more likely to have post-secondary education, older age of onset of opioid use, less likely to have hepatitis C and less likely to have use cannabis. Chronic pain was significantly associated with initiation to opioids through prescription (OR = 2.720, 95% CI 1.998-3.722, P < .0001). Analyses by gender revealed that men initiated by prescription were less likely to have liver disease and less likely to use cannabis, while women initiated by prescription had a higher methadone dose. Limitations: This project was limited by its study design being observational in nature; no causal relationships can be inferred. Also, the data did not allow determination of the role that the prescribed opioids played in developing opioid use disorder. Conclusions: Our results have revealed that almost half of this methadone maintenance treatment (MMT) population has been introduced to opioids through a prescription. Given that the increasing prescribing rates of opioids has an impact on this at-risk population, alternative treatments for pain should be considered to help decrease this opioid epidemic in Canada. Key words: Opioid use disorder, chronic pain relief, methadone maintenance treatment, prescriptions, male, female
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".