Uptake of slow‐release oral morphine as opioid agonist treatment among hospitalised patients with opioid use disorder
Bibliographic record
Abstract
Abstract Introduction Buprenorphine and methadone are highly effective first‐line medications for opioid agonist treatment (OAT) but are not acceptable to all patients. We aimed to assess the uptake of slow‐release oral morphine (SROM) as second‐line OAT among medically ill, hospitalised patients with opioid use disorder who declined buprenorphine and methadone. Methods This study included consecutive hospitalised patients with untreated moderate‐to‐severe opioid use disorder referred to an inpatient addiction medicine consultation service, between June 2018 and September 2019, in Nova Scotia, Canada. We assessed the proportion of patients initiating first‐line OAT (buprenorphine or methadone) in‐hospital, and the proportion initiating SROM after declining first‐line OAT. We compared rates of outpatient OAT continuation (i.e., filling outpatient OAT prescription or attending first outpatient OAT clinic visit) by medication type, and compared OAT selection between patients with and without chronic pain, using χ 2 tests. Results Thirty‐four patients were offered OAT initiation in‐hospital; six patients (18%) also had chronic pain. Twenty‐one patients (62%) initiated first‐line OAT with buprenorphine or methadone. Of the 13 patients who declined first‐line OAT, seven (54%) initiated second‐line OAT with SROM in‐hospital. Rates of outpatient OAT continuation after hospital discharge were high (>80%) and did not differ between medications ( P = 0.4). Patients with co‐existing chronic pain were more likely to choose SROM over buprenorphine or methadone ( P = 0.005). Discussion and Conclusions The ability to offer SROM (in addition to buprenorphine or methadone) increased rates of OAT initiation among hospitalised patients. Increasing access to SROM would help narrow the opioid use disorder treatment gap of unmet need.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".