Compatibility of Cloxacillin Sodium with Selected Intravenous Drugs during Simulated Y-Site Administration
Bibliographic record
Abstract
BACKGROUND: Data regarding Y-site compatibility of intravenous (IV) cloxacillin sodium with other drugs are scarce and incomplete. OBJECTIVE: To establish the compatibility of IV cloxacillin with 89 injectable drugs during simulated Y-site administration. METHODS: Cloxacillin sodium (10 mL, 100 mg/mL) was combined with 89 undiluted IV drugs (10 mL, each). Tests were duplicated and performed at room temperature. Visual evaluation and a light obscuration particle count test were performed on 1 of the 2 solutions immediately after mixing. The second mixture underwent visual evaluation after 15 minutes, 1 hour, and 4 hours, followed by a particle count test at 4 hours. Drugs were considered incompatible if the mixture precipitated or became turbid within the 4-hour period or exceeded the particle count limit allowed by Test 1.B of USP <788> initially or at 4 hours. RESULTS: Of the 89 tested drugs, 64 were compatible for up to 4 hours. The remaining 25 drugs were incompatible. Of these incompatible drugs, 16 were identified visually, and 9 were identified by the light obscuration particle count test. CONCLUSIONS: Sixty-four IV drugs were found to be compatible with cloxacillin via simulated Y-site, whereas 25 drugs were found to be incompatible with the antibiotic. The light obscuration particle count test should be used to complement visual evaluation when samples do not precipitate immediately.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".