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Record W4406905770 · doi:10.3138/jammi-2023-0038

Vancomycin-resistant <i>Enterococcus faecium</i> prosthetic valve endocarditis treated with daptomycin and ampicillin combination

2025· article· en· W4406905770 on OpenAlexaffvenue
Anish Krishnan, Irina Rajakumar

Bibliographic record

VenueJournal of the Association of Medical Microbiology and Infectious Disease Canada · 2025
Typearticle
Languageen
FieldMedicine
TopicInfective Endocarditis Diagnosis and Management
Canadian institutionsUniversity of CalgaryFraser HealthAlberta Health Services
Fundersnot available
KeywordsDaptomycinMedicineBacteremiaEndocarditisEnterococcus faeciumAmpicillinInfective endocarditisVancomycinEnterococcusIntensive care medicineSurgeryCombination therapyAntibioticsInternal medicineMicrobiologyStaphylococcus aureus

Abstract

fetched live from OpenAlex

Background: (VRE) bacteremia and infective endocarditis (IE) are difficult to treat and associated with high mortality. Methods: We describe a case of a 78-year-old male with VRE prosthetic valve endocarditis treated with combined daptomycin/ampicillin. We review published literature on the treatment of VRE IE and summarize other published case reports of daptomycin combination therapy. Results: Prompt clearance of bacteremia was achieved. Cardiac valve replacement surgery was pursued but was followed by post-operative complications and ultimately the patient did not survive. Conclusion: There is limited published literature on the treatment of VRE IE and an optimal antibiotic regimen has not been established. This case adds to the growing body of literature demonstrating the use of daptomycin and beta-lactam combination therapy for VRE bacteremia and endocarditis. Combination therapy may be an appropriate choice for select cases; however, reports of treatment failure warrant caution.

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)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.002
GPT teacher head0.209
Teacher spread0.206 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the Association of Medical Microbiology and Infectious Disease CanadaSame topicInfective Endocarditis Diagnosis and ManagementFrench-language works237,207