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Record W4389032047 · doi:10.1093/ofid/ofad500.805

744. Changing Molecular Epidemiology of Staphylococcus aureus Bacteremia in a Metropolitan Area in Canada

2023· article· en· W4389032047 on OpenAlexaffabout
Thi Mui Pham, Tatum D. Mortimer, Dan Gregson, Sören Wacker, Bruce J. Walker, Ashlee M. Earl, Ian A. Lewis, Yonatan H. Grad

Bibliographic record

VenueOpen Forum Infectious Diseases · 2023
Typearticle
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsClindamycinCloxacillinMedicineIncidence (geometry)CiprofloxacinErythromycinBacteremiaStaphylococcus aureusAntibioticsAntibiotic resistanceInternal medicinePopulationEpidemiologyMicrobiologyStaphylococcal infectionsPenicillinBacteriaBiologyEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Background The incidence of Staphylococcus aureus bacteremia (SAB) has increased in Alberta over the past two decades. It is unclear whether this trend reflects the expansion of a single strain or multiple strains and how much it has been influenced by changes in antibiotic use and resistance. Methods We used data from 5,881 S. aureus isolates representative of all SAB episodes from patients in the greater Calgary region from 2006-2019. Bacteremia episodes were defined as all positive isolates collected from a patient within a 30-day period. Each episode was categorized as community-onset (within 48 hours after admission) or hospital-onset (after 48 hours post admission). Isolates for which sequencing was successful (97.8%) were assigned strain and clonal complex (CC) designations. We computed the incidence of strains and antimicrobial susceptibility to cloxacillin, clindamycin, erythromycin, and ciprofloxacin. Antibiotic prescribing rates for the region were obtained from Alberta Health Services. Results SAB incidence increased from 30 to 40 per 100,000 population. The prevalence of resistance to cloxacillin, clindamycin, erythromycin, and ciprofloxacin fluctuated and decreased from a maximum of 31.8% to 15.6%, 28.2% to 19.2%, 39.1% to 27.5%, and 37.4% to 15%, respectively, by the end of the study period. An overall increase in S. aureus antibiotic susceptibility was driven primarily by an increased incidence of susceptible sub-lineages within several strains (CC30, CC5, CC8, CC45, CC15, CC97) mainly causing community-onset SAB. The incidence of SAB resistant to all four antibiotics decreased over the study period due to a decline in community and hospital-onset infections by one resistant sub-lineage of CC5; from 4.1 to 0.3 per 100,000 population, and was associated with a decline in community antibiotic prescribing for beta-lactamase resistant penicillins, lincosamides, macrolides, and fluoroquinolones (from 6.07 to 3.07, 17.5 to 16, 77 to 73.6, and 55.6 to 40.3 age-standardized number of dispensation per 1,000 population). Incidence rate of Staphylococcus aureus bacteremia per 100,000 Calgary residents stratified by community- and hospital-acquired infections. Bacteremia episodes were defined as all isolates collected from a patient within a 30-day period, and the incident isolate represents the first isolate from each episode. Prevalence of resistance to cloxacillin, clindamycin, erythromycin, and ciprofloxacin between 2006 and 2019. Points represent the proportion of incident isolates resistant to the respective antibiotic. Solid lines are smoothing curves using the loess method. Grey bands represent 95% confidence intervals. Incidence rate of Staphylococcus aureus bacteremia per 100,000 Calgary residents stratified by onset of infection. Points represent the incidence rate, dashed lines are linear interpolations between points, solid lines represent smoothing curves using the loess method. Grey bands represent 95% confidence intervals. Clonal complex designations in brackets represent the clonal complex assigned to the majority of the isolates for the respective strain. Conclusion From 2006-2019, Calgary observed a decline in community antibiotic use, a reduction in the incidence of a resistant strain, and a greater increase in the incidence of community-onset SAB caused by several antibiotic susceptible strains. Disclosures Dan Gregson, MD, BioMerieux Canada: Advisor/Consultant Yonatan H. Grad, MD, PhD, Day Zero Diagnostics: Board Member|GSK: Advisor/Consultant

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 score0.024
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.302
Teacher spread0.281 · 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".

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Citations0
Published2023
Admission routes2
Has abstractyes

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