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Record W2100755238 · doi:10.1017/s0950268806007631

Burden of community-onset bloodstream infection: a population-based assessment

2006· article· en· W2100755238 on OpenAlexaffabout
Kevin B. Laupland, Dan Gregson, W. Ward Flemons, Devan Hawkins, Terry Ross, Deirdre L. Church

Bibliographic record

VenueEpidemiology and Infection · 2006
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsCalgary Laboratory ServicesUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsMedicineCase fatality rateInterquartile rangePopulationBacteremiaStreptococcus pneumoniaeIncidence (geometry)PediatricsMortality rateEmergency medicineInternal medicineEnvironmental healthAntibiotics

Abstract

fetched live from OpenAlex

Although community-onset bloodstream infection (BSI) is recognized to be a major cause of morbidity and mortality, there is a paucity of population-based studies defining its overall burden. We conducted population-based laboratory surveillance for all community-onset BSI in the Calgary Health Region during 2000-2004. A total of 4467 episodes of community-onset BSI were identified for an overall annual incidence of 81.6/100,000. The three species, Escherichia coli, Staphylococcus aureus, and Streptococcus pneumoniae were responsible for the majority of community-onset BSI; they occurred at annual rates of 25.8, 13.5, and 10.1/100,000, respectively. Overall 3445/4467 (77%) episodes resulted in hospital admission representing 0.7% of all admissions to major acute care hospitals. The subsequent hospital length of stay was a median of 9 (interquartile range, 5-15) days; the total days of acute hospitalization attributable to community-onset BSI was 51,146 days or 934 days/100,000 annually. Four hundred and sixty patients died in hospital for a case-fatality rate of 13%. Community-onset BSI is common and has a major patient and societal impact. These data support further efforts to reduce the burden of community-onset BSI.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.063
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.046
GPT teacher head0.376
Teacher spread0.330 · 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 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

Citations122
Published2006
Admission routes2
Has abstractyes

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