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Record W3137263837 · doi:10.1093/cid/ciaa1743

Should Therapeutic Drug Monitoring Based on the Vancomycin Area Under the Concentration-Time Curve Be Standard for Serious Methicillin-Resistant <i>Staphylococcus aureus</i> Infections?—No

2020· letter· en· W3137263837 on OpenAlexaff
Sarah C J Jorgensen, Brad Spellberg, Andrew F. Shorr, William F. Wright

Bibliographic record

VenueClinical Infectious Diseases · 2020
Typeletter
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsVancomycinTherapeutic drug monitoringMedicineStaphylococcus aureusIntensive care medicineAntibioticsDrugStewardship (theology)Methicillin-resistant Staphylococcus aureusPharmacologyMicrobiologyBiologyBacteria

Abstract

fetched live from OpenAlex

In this counterpoint we critically appraise the evidence supporting therapeutic drug monitoring based on the vancomycin 24-hour area under the concentration-time curve (AUC24) for serious methicillin-resistant Staphylococcus aureus infections. We reveal methodologically weaknesses and inconsistencies in the data and suggest that, in the absence of clear and convincing evidence of benefit compared with modestly reducing trough targets, alternative strategies are more likely to result in superior safety and efficacy. These include focusing on fundamental antibiotic stewardship to limit vancomycin exposure overall, achieving earlier and more complete source control, and establishing alternative therapeutic options to vancomycin. Implementation of AUC24-based therapeutic drug monitoring will take resources away from these more promising, alternative solutions.

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)0.008
metaresearch head score (Gemma)0.050
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 score0.039
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.050
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0030.004
Open science0.0020.001
Research integrity0.0390.028
Insufficient payload (model declined to judge)0.0040.006

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 head0.071
GPT teacher head0.357
Teacher spread0.286 · 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

Citations22
Published2020
Admission routes1
Has abstractyes

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