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Record W2135118881 · doi:10.1093/cid/ciu971

Potential Role for Telavancin in Bacteremic Infections Due to Gram-Positive Pathogens: Focus on Staphylococcus aureus

2014· review· en· W2135118881 on OpenAlexaff
G. R. Corey, Eric Rubinstein, Martín E. Stryjewski, Matteo Bassetti, Steven L. Barriere

Bibliographic record

VenueClinical Infectious Diseases · 2014
Typereview
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsUniversity of Manitoba
FundersAstellas PharmaNational Institutes of HealthNabriva TherapeuticsMedicines CompanyTheravance Biopharma USGilead SciencesTeva Pharmaceutical IndustriesAstraZenecaPfizer
KeywordsStaphylococcus aureusBacteremiaMicrobiologyMedicineMethicillin-resistant Staphylococcus aureusBiologyAntibioticsBacteria

Abstract

fetched live from OpenAlex

Staphylococcus aureus bacteremia (SAB) is one of the most common serious bacterial infections and the most frequent invasive infection due to methicillin-resistant S. aureus (MRSA). Treatment is challenging, particularly for MRSA, because of limited treatment options. Telavancin is a bactericidal lipoglycopeptide antibiotic that is active against a range of clinically relevant gram-positive pathogens including MRSA. In experimental animal models of sepsis telavancin was shown to be more effective than vancomycin. In clinically evaluable patients enrolled in a pilot study of uncomplicated SAB, cure rates were 88% for telavancin and 89% for standard therapy. Among patients with infection due to only gram-positive pathogens enrolled in the 2 phase 3 studies of telavancin for treatment of hospital-acquired pneumonia, cure rates for those with bacteremic S. aureus pneumonia were 41% (9/22, telavancin) and 40% (10/25, vancomycin) with identical mortality rates. These data support further evaluation of telavancin in larger, prospective studies of SAB.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.030
GPT teacher head0.380
Teacher spread0.350 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations28
Published2014
Admission routes1
Has abstractyes

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