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Aminoglycoside nephrotoxicity: do time and frequency of administration matter?

2001· review· en· W1991119253 on OpenAlexaff
Denis Beauchamp, Gaston Labrecque

Bibliographic record

VenueCurrent Opinion in Critical Care · 2001
Typereview
Languageen
FieldMedicine
TopicAntibiotics Pharmacokinetics and Efficacy
Canadian institutionsUniversité LavalCentre hospitalier de l'Université Laval
Fundersnot available
KeywordsNephrotoxicityMedicineAminoglycosideToxicityDosingGentamicinPharmacologyAntibioticsIntensive care medicineInternal medicineBiology

Abstract

fetched live from OpenAlex

Aminoglycosides remains the mainstay in the treatment of gram-negative infections despite their potential oto-and nephrotoxicity although alternatives with equal or better efficacy are available. Several approaches were investigated to decrease aminoglycosides nephrotoxicity. Among them, only the once-daily dosing of aminoglycosides has been brought to the clinic and physicians are now increasingly adopting this approach to reduce the toxicity of these agents. The incidence of aminoglycoside nephrotoxicity can be further reduced in view of the recent data on the circadian variations of their nephrotoxicity. In fact, it has been clearly demonstrated in both experimental animals and humans that the toxicity is maximal when the drug is injected during the rest period compared with the activity period. Thus, injecting aminoglycosides once-daily at the time of the lowest toxicity is actually the most interesting and clinically applicable approach to reduce aminoglycosides toxicity.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.166
GPT teacher head0.484
Teacher spread0.319 · 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
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

Citations71
Published2001
Admission routes1
Has abstractyes

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