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Prevalence and Characterization of Macrolide Resistance in Clinical Isolates of <i>Streptococcus pneumoniae</i> and <i>Streptococcus pyogenes</i> from North America

2002· article· en· W2409698911 on OpenAlexaffabout
D. Hoban

Bibliographic record

VenueJournal of Chemotherapy · 2002
Typearticle
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsHealth Sciences CentreManitoba Health
Fundersnot available
KeywordsStreptococcus pyogenesTelithromycinKetolideStreptococcus pneumoniaeErythromycinMicrobiologyEffluxBiologyDrug resistanceMacrolide AntibioticsAntibacterial agentAntibioticsBacteriaGeneticsStaphylococcus aureus

Abstract

fetched live from OpenAlex

Resistance to macrolides is not a new phenomenon but it deserves attention because of the widespread use of these agents and their inclusion in many clinical guidelines for respiratory tract infections. The most common mechanisms by which Streptococcus pneumoniae and Streptococcus pyogenes develop resistance to macrolides is by target site modification (erythromycin ribosome methylase, erm) and efflux of the drug out of the organisms (macrolide efflux, mef). Target site modification may be of greater concern because it confers high-level resistance to all antimicrobials in the macrolide-lincosamide-streptograminB (MLSB) group. The genotype profiles of macrolide-resistant S. pneumoniae and S. pyogenes differ somewhat across regions in the US and between the US and Canada and other countries. There is some evidence for an association between macrolide resistance and treatment failure but this must be researched more fully. S. pneumoniae and S. pyogenes isolates resistant to macrolides are generally susceptible to ketolide antimicrobials because these agents bind more strongly to the relevant domain of the ribosomal subunit (withstanding erm resistance) and are less vulnerable to efflux compared to the macrolides.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.455

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.270
Teacher spread0.256 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations13
Published2002
Admission routes2
Has abstractyes

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