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Record W4380201598 · doi:10.1007/s40262-023-01264-0

Antifungal Dosing in Critically Ill Patients on Extracorporeal Membrane Oxygenation

2023· review· en· W4380201598 on OpenAlexaff
Haifa Lyster, Kiran Shekar, Kevin Watt, Anna Reed, Jason A. Roberts, Mohd H. Abdul‐Aziz

Bibliographic record

VenueClinical Pharmacokinetics · 2023
Typereview
Languageen
FieldMedicine
TopicAntibiotics Pharmacokinetics and Efficacy
Canadian institutionsUniversity of Waterloo
FundersNational Health and Medical Research CouncilEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentMedical Research CouncilUniversity of Queensland
KeywordsDosingExtracorporeal membrane oxygenationMedicineCritically illIntensive care medicineAntifungalPopulationDrugAntifungal drugsExtracorporealAntifungal drugPharmacokineticsTherapeutic drug monitoringCritical illnessVolume of distributionPharmacologyAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

Extracorporeal membrane oxygenation (ECMO) is an established advanced life support system, providing temporary cardiac and/or respiratory support in critically ill patients. Fungal infections are associated with increased mortality in patients on ECMO. Antifungal drug dosing for critically ill patients is highly challenging because of altered pharmacokinetics (PK). PK changes during critical illness; in particular, the drug volume of distribution ( V d ) and clearance can be exacerbated by ECMO. This article discusses the available literature to inform adequate dosing of antifungals in this patient population. The number of antifungal PK studies in critically ill patients on ECMO is growing; currently available literature consists of case reports and studies with small sample sizes providing inconsistent findings, with scant or no data for some antifungals. Current data are insufficient to provide definitive empirical drug dosing guidance and use of dosing strategies derived from critically patients not on ECMO is reasonable. However, due to high PK variability, therapeutic drug monitoring should be considered where available in critically ill patients receiving ECMO to prevent subtherapeutic or toxic antifungal exposures.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.966
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.181
GPT teacher head0.483
Teacher spread0.303 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations31
Published2023
Admission routes1
Has abstractyes

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