A Simple Method for Quantifying Fentanyl, Sufentanil, or Morphine in Discard Syringes From Anesthesia Procedures
Bibliographic record
Abstract
Fentanyl, sufentanil, and morphine are commonly used in the conduct of anesthesia. Medical staff working with these drugs are at high risk of addiction. To detect and prevent diversion, a method was developed to quantify these drugs in discard syringes using the BioRad REMEDi HS Drug Profiling System. For fentanyl, the lowest concentration detected is 0.1 microg/mL, and the assay is linear to 5.0 microg/mL; the within-run coefficient of variation (CV) is 0.9% (n = 5), and between-run CV is 2.5% (n = 20). For sufentanil, the lowest concentration detected is 0.5 microg/mL, and the assay is linear to 11.0 microg/mL; the within-run CV is 2.0% (n = 5), and the between-run CV is 2.4% (n = 20). For morphine, the lowest concentration detected is 0.5 microg/mL, and the assay is linear to 10.0 microg/mL; the within-run CV is 11.6% (n = 5), and between-run CV is 11.3% (n = 20). Other drugs commonly used in the operating room were checked for cross-reactivity on the REMEDi HS; none cross-reacted. The REMEDi HS can be used for rapid, accurate quantification of fentanyl, sufentanil, and morphine in discard syringes from anesthesia procedures or related medical applications.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".