<i>In vitro</i> Characterization of Oritavancin Clearance from Human Blood by Low-Flux, High-Flux, and Continuous Renal Replacement Therapy Dialyzers
Bibliographic record
Abstract
BACKGROUND: Oritavancin is an investigational lipoglycopeptide antibiotic under clinical development for the treatment of gram-positive bacterial infections. The impact of hemodialysis on plasma concentrations of oritavancin is unknown and may be important in making dosage adjustments in such patients. The present study sought to determine the clearance of oritavancin from human blood by various commercially available dialyzers in an in vitro hemodialysis model. METHODS: Three types each of low-flux (Dicea 130, F6, and Polyflux 14L) and high-flux (Revaclear, Exeltra 150, and Optiflux F160NR) dialyzers and one type of continuous renal replacement therapy (CRRT) dialyzer (Prismaflex M100) were studied. Heparinized human blood containing oritavancin (200 mg/L) was circulated from a reservoir to the dialyzers and back to the reservoir. Fresh dialysate was pumped through the dialyzers in a countercurrent manner. Blood samples from each side of the dialyzers and contaminated dialysate samples were collected at periodic intervals. Oritavancin levels were analyzed by a liquid chromatography/mass spectrometry method with a limit of quantification of 12.5 ng/mL and plasma clearances of oritavancin were calculated. RESULTS: The mean dialytic clearance of oritavancin was insignificant for each of the low-flux, high-flux and CRRT dialyzers. Clinically significant amounts of oritavancin were not detected in dialysate during any of the experimental dialysis sessions. CONCLUSIONS: The clearance of oritavancin from human blood by the dialyzers used in this study is insignificant. Further clinical studies would be required before making changes in dosage of oritavancin in hemodialysis patients.
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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 | 0.001 | 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 | 0.001 | 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".