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Record W2792045681 · doi:10.1155/2018/7567914

Successful Treatment of High-Level Aminoglycoside-Resistant <i>Enterococcus faecalis</i> Bacteremia in a Preterm Infant with Ampicillin and Cefotaxime

2018· article· en· W2792045681 on OpenAlexaff
Jennifer Tam, Santina J. Lee, Vibhuti Shah, Shaun K. Morris

Bibliographic record

VenueCase Reports in Infectious Diseases · 2018
Typearticle
Languageen
FieldMedicine
TopicInfective Endocarditis Diagnosis and Management
Canadian institutionsMount Sinai HospitalUniversity of ManitobaCanada Research ChairsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsAmpicillinEnterococcus faecalisCefotaximeMedicineBacteremiaAminoglycosideAntibioticsEnterococcusPopulationVancomycinMicrobiologyPediatricsIntensive care medicineBiologyStaphylococcus aureusBacteria

Abstract

fetched live from OpenAlex

Enterococcal bloodstream infections are usually treated with single-agent antibiotics. In persistent infections, synergistic combination therapy is often required with a beta-lactam and an aminoglycoside antibiotic. High-level aminoglycoside-resistant (HLAR) enterococci are increasingly prevalent and preclude the use of this combination. The use of ampicillin with a third-generation cephalosporin to treat endovascular HLAR Enterococcus infections is becoming more established in the adult population; however, the literature on treatment of such infections in children remains scarce. We report a preterm neonate with persistent HLAR Enterococcus faecalis bacteremia from day of life 9 to 17 despite treatment with ampicillin and vancomycin. On day of life 17, antibiotic treatment was switched to ampicillin and cefotaxime, with subsequent clearance of blood cultures on day of life 20. To our knowledge, this is the first report illustrating the use of ampicillin and cefotaxime for an HLAR E. faecalis infection in a neonate.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.012
GPT teacher head0.260
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations2
Published2018
Admission routes1
Has abstractyes

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