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Record W4402326614 · doi:10.1093/cid/ciae458

Is More Always Better? Rethinking Monotherapy for <i>Enterococcus faecalis</i> Infective Endocarditis

2024· letter· en· W4402326614 on OpenAlexaff
Connor Prosty, Todd C. Lee, Emily G. McDonald

Bibliographic record

VenueClinical Infectious Diseases · 2024
Typeletter
Languageen
FieldMedicine
TopicInfective Endocarditis Diagnosis and Management
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsMedicineEnterococcus faecalisInfective endocarditisEndocarditisEnterococcusMicrobiologyIntensive care medicineInternal medicineAntibioticsBacteriaStaphylococcus aureus

Abstract

fetched live from OpenAlex

To the Editor—We read with great interest the article by Danneels et al [1] reporting on 1 of the largest observational cohorts of patients with Enterococcus faecalis infective endocarditis (EFIE). Mortality and relapse rates were compared across different treatment regimens and amoxicillin-ceftriaxone and amoxicillin-gentamicin appeared to be comparable. However, the amoxicillin monotherapy group (n = 9) had numerically higher mortality (3/9; adjusted hazard ratio = 1.94; 95% confidence interval [CI] = .56–6.74) and relapse (3/9; adjusted sub-hazard ratio = 2.38; 95% CI = .57–10.05) than amoxicillin-gentamicin. Based on these results, the authors suggested that amoxicillin monotherapy should not be used for EFIE. We wish to highlight some counterarguments to this position. First and foremost, the results were underpowered to draw conclusions. Second, there was likely confounding by indication. Adjunctive therapy is recommended as the standard of care for EFIE by the European Society of Cardiology guidelines [2, 3]. Given that this study was observational, the reason for which the amoxicillin group received monotherapy may have been related to factors inherently tied to a poorer outcome, such as prognosis or renal function. Along these lines, the models for mortality and relapse did not adjust for other important confounders such as paravalvular complications and embolic phenomena [4, 5]. Third, the analyses did not consider treatment as a time-dependent variable, which introduces immortal time bias. Adjunctive therapy is recommended for the treatment of EFIE and not E faecalis bacteremia without infective endocarditis (IE) [2]. Thus, adjunctive therapy may only be administered following a diagnosis of IE, whereas monotherapy is often administered at the outset for a positive culture with E faecalis. The difference in “time zero” between adjunctive and monotherapy groups renders the adjunctive group “immortal” to the outcome of death during the time between a positive culture for E faecalis to the administration of adjunctive therapy, whereas the monotherapy group can experience death throughout this time frame [6]. Finally, there was the potential for misclassification bias. The classification criteria in this study were not strictly defined a priori. For example, 3 patients classified as amoxicillin monotherapy received amoxicillin for only 13.3% of antibiotic days. These patients accounted for 2 of the 3 deaths, including a death after 1 day of amoxicillin monotherapy preceded by 25 days of daptomycin and levofloxacin. Given these limitations, we posit that a randomized controlled trial of monotherapy versus adjunctive therapy for EFIE is both ethical and needed, especially considering that both adjunctive ceftriaxone and gentamicin are associated with higher toxicity, cost, as well as the potential for increased colonization with resistant organisms [7–9].

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)0.003
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.041
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0050.004
Open science0.0020.002
Research integrity0.0410.040
Insufficient payload (model declined to judge)0.0090.006

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 head0.055
GPT teacher head0.386
Teacher spread0.331 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations3
Published2024
Admission routes1
Has abstractno

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