Telavancin Activity Against Gram-Positive Bacteria Isolated from Patients with Skin and Skin-Structure Infections
Bibliographic record
Abstract
Telavancin is approved in the United States and Canada for the treatment of complicated skin and skin structure infections (cSSSI) in adults caused by susceptible Gram-positive organisms. The antimicrobial activity of telavancin and comparators was evaluated against 5,027 (2007-2008) Gram-positive bacteria responsible for SSSI in medical centers in Asia-Pacific, European, Latin American, and North American regions. Telavancin was active against Staphylococcus aureus (MIC₅₀(/)₉₀, 0.12/0.25 mg/l; 100.0% susceptible) and coagulase-negative staphylococci (MIC₅₀(/)₉₀, 0.12/0.25 mg/l). telavancin inhibited all Enterococcus faecalis, including four strains displaying a VanB phenotype, at ≤ 1 mg/L (MIC₅₀(/)₉₀, 0.25/0.5 mg/l), except for two isolates with a VanA phenotype (MIC, >2 mg/l). Vancomycin-susceptible and VanB vancomycin-resistant E. faecium were inhibited by telavancin at ≤ 0.25 mg/L, while this drug exhibited elevated MIC values (≥ 0.5 mg/l) against E. faecium of VanA phenotype (MIC₅₀(/)₉₀, 2/>2 mg/l). Telavancin was potent against β-haemolytic streptococci (MIC₅₀(/)₉₀, 0.03/0.12 mg/l; 100.0% susceptible) and viridans group streptococci (MIC₅₀(/)₉₀, 0.03/0.06 mg/l; 100.0% susceptible). These in vitro data document the activity of telavancin against contemporary Gram-positive isolates and support its clinical use for the treatment of cSSSI caused by the indicated pathogens.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".