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Record W3007877531 · doi:10.1371/journal.pone.0228935

Assessing impact of MALDI mass spectroscopy on reducing directed antibiotic coverage time for Gram-negative organisms

2020· article· en· W3007877531 on OpenAlexaff
Calvin Ka-Fung Lo, Dominik Mertz, Debbie Yamamura, Mark Loeb

Bibliographic record

VenuePLoS ONE · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Identification and Susceptibility Testing
Canadian institutionsMcMaster UniversityHamilton Regional Laboratory Medicine ProgramImpactUniversity of British Columbia
Fundersnot available
KeywordsBacteremiaBlood cultureMedicineAntibioticsGramMatrix-assisted laser desorption/ionizationBloodstream infectionInternal medicineMicrobiologyBacteriaBiologyChemistryDesorption

Abstract

fetched live from OpenAlex

The objective of this study was to assess whether use of matrix assisted laser desorption ionization-time of flight (MALDI-TOF), through improvements in identification time, reduces time to directed antibiotic coverage. We therefore conducted a retrospective review of 377 blood cultures from hospitalized patients with gram negative bacteremia that underwent testing by MALDI-TOF compared to standard identification methods (VITEK 2) for blood cultures from January 2016 to December 2017. We found that MALDI significantly reduced time between blood culture collection to reach pathogen identification and was associated with a significantly reduced time to initiate more specific therapy, with a mean difference of 16.37 hours, 95% CI 10.05 to 22.69 (mean time 50.34 hours (+/- 21.21) vs VITEK: 66.71 hrs (+/- 27.12), p<0.001 as well as a reduced time to discontinue previous therapy (p = 0.004). In conclusion, in reducing time to identification of gram negative bacteremia, MALDI-TOF led to improvements in antibiotic coverage.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.012
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.291
Teacher spread0.247 · 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.

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

Citations5
Published2020
Admission routes1
Has abstractyes

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