Use of a liquid chromatography-tandem mass spectrometry method to assess the concentration of epinephrine, norepinephrine, and phenylephrine stored in plastic syringes
Bibliographic record
Abstract
Abstract Objectives There are concerns about the potency of epinephrine (EPI), norepinephrine (NE), and phenylephrine (PE) stored in syringes for later infusions in clinical care. The objective of our study was to optimize a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to determine the concentrations EPI, NE, and PE dissolved in normal saline and stored in 50 mL 3-part Becton Dickinson syringes. Methods Medications were diluted in normal saline to 80 μg/mL for EPI and NE, and 100 μg/mL for PE. The solutions were stored in syringes for 0 (fresh), 3, and 7 days in a medical refrigerator. United States Pharmacopeia grade EPI, NE, and PE and their deuterium-labeled analogs were used as calibration standards. Stored samples and standards were diluted and analyzed by LC-MS/MS operated in selected reaction monitoring mode. Results The calculated limit of quantification for EPI, NE and PE were well below the concentrations used in clinical practice. The coefficient of variation remained below 12 % for all samples. The standard linear calibration regressions for EPI, NE, and PE had r 2 values of between 0.96 and 0.98 (p < 0.001). EPI and NE stored in the refrigerator remained within 10 % of the of their initial concentrations at all time points. The concentration of PE in syringe decreased by 19.85 % at 3 days, with no further decrease at 7 days, compared to fresh PE. Conclusions The sample preparation steps and optimized LC-MS/MS method allowed simple and reliable measurements of EPI, NE, and PE.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".