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Reproducibility of broth microdilution MICs for the novel siderophore cephalosporin, cefiderocol, determined using iron-depleted cation-adjusted Mueller-Hinton broth

2019· article· en· W2942237294 on OpenAlexafffund
Meredith Hackel, Masakatsu Tsuji, Yoshinori Yamano, Roger Echols, James A. Karlowsky, Daniel F. Sahm

Bibliographic record

VenueDiagnostic Microbiology and Infectious Disease · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsUniversity of Manitoba
FundersShionogiDiagnostic Services ManitobaUniversity of Manitoba
KeywordsSerial dilutionBroth microdilutionReproducibilityCephalosporinMicrobiologyBacilliDilutionAntimicrobialChromatographySiderophoreMinimum inhibitory concentrationBiologyChemistryBacteriaMedicineAntibiotics

Abstract

fetched live from OpenAlex

In 2017, the Clinical and Laboratory Standards Institute (CLSI) Subcommittee on Antimicrobial Susceptibility Testing approved the use of iron-depleted cation-adjusted Mueller-Hinton broth (ID-CAMHB) prepared with Chelex® 100 resin (Bio-Rad Laboratories, Hercules, CA) to determine MICs for cefiderocol. The current study examined the reproducibility of cefiderocol MICs generated for 19 clinical isolates of Gram-negative bacilli, with CAMHB produced by three manufacturers; each of the 19 isolates was tested for 10 replicates in ID-CAMHB from each manufacturer. When analyzed by individual media lot, greater than 95% of MIC results were within ± one doubling-dilution of the mode for each of the 19 isolates tested. The remaining 5.0% of MIC results were within ± two doubling-dilutions of the modal MIC. For all media lots combined, 92.2% of MIC results were within ± one doubling-dilution of the modal MIC for each isolate, 99.8% were within ± two doubling-dilutions and 100% were within three doubling-dilutions.

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)0.011
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.012
GPT teacher head0.243
Teacher spread0.232 · 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 designBench or experimental
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

Citations131
Published2019
Admission routes2
Has abstractyes

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