Buprenorphine: new treatment of opioid addiction in primary care.
Bibliographic record
Abstract
OBJECTIVE: To review the use of buprenorphine for opioid-addicted patients in primary care. QUALITY OF EVIDENCE: The MEDLINE database was searched for literature on buprenorphine from 1980 to 2009. Controlled trials, meta-analyses, and large observational studies were reviewed. MAIN MESSAGE: Buprenorphine is a partial opioid agonist that relieves opioid withdrawal symptoms and cravings for 24 hours or longer. Buprenorphine has a much lower risk of overdose than methadone and is preferred for patients at high risk of methadone toxicity, those who might need shorter-term maintenance therapy, and those with limited access to methadone treatment. The initial dose should be given only after the patient is in withdrawal. The therapeutic dose range for most patients is 8 to 16 mg daily. It should be dispensed daily by the pharmacist with gradual introduction of take-home doses. Take-home doses should be introduced more slowly for patients at higher risk of abuse and diversion (eg, injection drug users). Patients who fail buprenorphine treatment should be referred for methadone- or abstinence-based treatment. CONCLUSION: Buprenorphine is an effective treatment of opioid addiction and can be safely prescribed by primary care physicians.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".