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Record W1969301715 · doi:10.3201/eid1209.060397

Fluoroquinolones and Risk for Methicillin-Resistant<i>Staphylococcus aureus</i>, Canada

2006· article· en· W1969301715 on OpenAlexaffabout
Louiselle LeBlanc, Krystel Toulouse, Marie-France Ouellette, Marie‐Andrée Coulombe, Marie-Pier Corriveau, M.-E. Alary

Bibliographic record

VenueEmerging infectious diseases · 2006
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMedicineMethicillin-resistant Staphylococcus aureusAntimicrobialClostridium difficileStaphylococcus aureusInternal medicineRetrospective cohort studyColonizationHazard ratioConfidence intervalRisk factorMicrobiologyIntensive care medicineAntibioticsBiologyBacteria

Abstract

fetched live from OpenAlex

Receipt of fluoroquinolones was the predominant risk factor for Clostridium difficile-associated disease (CDAD) during an epidemic in Quebec, Canada. To determine the role of antimicrobial drugs in facilitating healthcare-associated methicillin-resistant Staphylococcus aureus (MRSA) colonization and infection and to compare this role with their effects on methicillin-susceptible S. aureus infection and CDAD, we conducted a retrospective cohort study of patients in a Quebec hospital. For 7371 episodes of care, data were collected on risk factors, including receipt of antimicrobial drugs. Crude and adjusted hazard ratios (AHR) were calculated by Cox regression. Of 150 episodes of MRSA colonization and 23 of MRSA infection, fluoroquinolones were the only antimicrobials that increased risk for colonization (AHR 2.57, 95% confidence interval [CI] 1.84-3.60) and infection (AHR 2.49, 95% CI 1.02-6.07). Effect of antimicrobial drugs on MRSA colonization and infection was similar to effect on CDAD and should be considered when selecting antimicrobial drugs to treat common infections.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.265
Teacher spread0.255 · 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 designObservational
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

Citations70
Published2006
Admission routes2
Has abstractyes

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