Buprenorphine/naloxone induction for treatment of acute on chronic pain using a micro-dosing regimen: A case report
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Bibliographic record
Abstract
Background Due to its unique pharmacologic properties, efficacy as an analgesic, and role as a first-line medication for the treatment of opioid use disorder, sublingual buprenorphine has emerged as a treatment for patients with concurrent chronic pain and opioid use disorders. One challenge to utilizing buprenorphine is that precipitated opioid withdrawal can result if this medication is initiated in the presence of other opiates with lesser binding affinities. Micro-dosing induction regimens utilize a slower titration to avoid the need for a period of abstinence from other opiates and decrease the risk of precipitated withdrawal.Aims The aim of this article is to present a case where a standardized micro-dosing induction regimen was used to transition a patient from other opiate analgesia to a sublingual formulation of buprenorphine/naloxone.Methods This case took place on an inpatient neurosurgical unit of a Canadian tertiary-care city hospital. Written informed consent was collected prior to a detailed chart review.Results Here we present a case of a postoperative neurosurgical inpatient who was referred to our team for pain management in the context of chronic pain and a past history of opioid use disorder. She was successfully transitioned to buprenorphine/naloxone, replacing all other opioid analgesia, without a period of opioid withdrawal using a micro-dosing induction regimen.Conclusions Sublingual buprenorphine/naloxone can be safe and effective for treatment of chronic pain, particularly for those with past or current opioid use disorder. Micro-dosing provides a preferable induction strategy for patients who are not able to tolerate the requirement for moderate opioid withdrawal prior to initiation with existing regimens.
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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 | 0.001 | 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 it