Assessment of Oritavancin Activity in Combination with Beta-Lactams against Vancomycin-Resistant Enterococci
Bibliographic record
Abstract
Background. Optimal treatments for infections caused by vancomycin-resistant enterococci (VRE) remain to be elucidated. Combinations of beta-lactams (BLs) and lipopeptides or glycopeptides exhibit synergy against VRE, as do combinations of gentamicin and BLs or glycopeptides. Because the lipoglycopeptide oritavancin (ORI) demonstrates in vitro activity against VRE, we assessed potentiation of its activity in combination with BLs against VRE. Methods. Clinical isolates of E. faecium (Efm) VanA (n = 5) and VanB (n = 5) and E. faecalis (Efa) VanA (n = 6) and VanB (n = 5) were used in checkerboard experiments of ORI and the BLs ceftaroline (CPT), meropenem (MER) or penicillin (PEN). Potentiation of ORI activity was defined as a lowering of ORI MIC by at least two doubling dilutions in the combination, relative to the MIC of ORI alone, with the constraint that the MIC of the BLs in the combination had to be ≤32 µg/mL. Time-kill kinetics (TKK) were performed following CLSI guidelines. Potentiation of ORI activity in combination with BLs in TKK was defined as a ≥2-log decrease in colony-forming units (CFU)/mL from the starting inoculum in addition to a ≥1-log decrease in CFU/mL from the most active single agent at 24 hours. Results. ORI MIC range against the VREs was 0.004–1 µg/ml. MER MIC ranges were 512–1024 µg/ml (Efm VanA), 512–1024 µg/ml (Efm VanB), 16–128 µg/ml (Efa VanA) and 64–128 µg/ml (Efa VanB). CPT MIC ranges were 256–1024 µg/ml (Efm VanA), 64–1024 µg/ml (Efm VanB), 4–128 µg/ml (Efa VanA) and 16–128 µg/ml (Efa VanB). PEN MIC ranges were 1024–2048 µg/ml (Efm VanA), 256–512 µg/ml (Efm VanB), 4–128 µg/ml (Efa VanA) and 8–16 µg/ml (Efa VanB). Of the 21 VRE isolates tested, CPT, MER and PEN potentiated ORI MICs against 11, 11 and 8 isolates, respectively (Table), with the BL MICs being ≤32 µg/ml in each combination. ORI activity was potentiated by BL against the majority of Efa VanA, Efa VanB and Efm VanA isolates. BLs did not potentiate ORI activity against Efm VanB (Table). In TKK, potentiation by ORI-BL combinations compared to single agents was observed for VRE isolates. Conclusion. MER, CPT and PEN potentiated ORI in vitro activity against VRE, with the exception of Efm VanB. Several of the VREs with high (≥256 µg/mL) BL MICs showed potentiation of ORI activity at BL MICs of ≤32 µg/mL. Disclosures. F. Arhin, The Medicines Company: Employee, Salary D. Lalonde Seguin, The Medicines Company: Consultant, Salary A. Belley, The Medicines Company: Employee, Salary G. Moeck, The Medicines Company: Employee, Salary
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".