Physical Compatibility of High-Concentration Bupivacaine with Hydromorphone, Morphine, and Fentanyl
Bibliographic record
Abstract
Physical Compatibility of High-Concentration Bupivacaine with Hydromorphone, Morphine, and FentanylIn the field of oncology and in the setting of chronic pain, there are subsets of patients whose pain is refractory to usual drug dosages.Instead, to achieve acceptable pain control, combinations of local anesthetics and narcotics at elevated concentrations are required.Although there is some literature on the compatibility of various combinations of these drugs, our institution needed data for these more concentrated solutions.To ensure patient safety and to ensure that acceptable expiry data were available, we performed physical compatibility testing for these more highly concentrated solutions.We conducted a physical compatibility study of the various concentrations of bupivacaine used in the hospital with hydromorphone, morphine, or fentanyl, as listed in Table 1.The solutions were adjusted to volume with normal saline (Baxter Corporation, Mississauga, Ontario; lot W8F25B1, expiry September 2009) and were packaged in either polypropylene syringes (BD, Franklin Lakes, New Jersey; lot 8353527) or non-DEHP (di(2-ethylhexyl) phthalate) bags (Intravia, Baxter Concentration of Concentration of Storage Container pH Over Study Bupivacaine*
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 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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".