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Record W2330965877 · doi:10.1017/s0950268816000613

Burden of community-onset bloodstream infections, Western Interior, British Columbia, Canada

2016· article· en· W2330965877 on OpenAlexaffabout
Kevin B. Laupland, Kelsey Pasquill, Elizabeth C. Parfitt, Prenilla Naidu, Lisa Steele

Bibliographic record

VenueEpidemiology and Infection · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsProvincial Laboratory of Public HealthUniversity of AlbertaRoyal Inland HospitalUniversity of Calgary
Fundersnot available
KeywordsMedicineIncidence (geometry)EpidemiologyPopulationBloodstream infectionDemographyPediatricsBacteremiaInternal medicineEnvironmental healthBiology

Abstract

fetched live from OpenAlex

Although community-onset bloodstream infection (BSI) is recognized as a major cause of morbidity and mortality, its epidemiology has not been well defined in non-selected populations. We conducted population-based surveillance in the Interior Health West region of British Columbia, Canada in order to determine the burden associated with community-onset BSI. A total of 1088 episodes were identified for an overall annual incidence of 117·8/100 000 of which 639 (58·7%) were healthcare-associated (HA) and 449 (41·3%) were community-associated (CA) BSIs for incidences of 69·2 and 48·6/100 000, respectively. The incidence of community-onset BSI varied by age and gender and elderly males were at the highest risk. Overall 964 (88·6%) episodes resulted in hospital admission for a median length of stay of 8 days; the total days of acute hospitalization associated with community-onset BSI was 13 530 days or 1465 days/100 000 population per year. The in-hospital mortality rate was 10·6% (102/964) and this was higher for HA-BSI (72/569, 12·7%) compared to CA-BSI (30/395, 7·6%, P = 0·014) episodes. Community-onset BSI, especially HA-BSI, is associated with a major burden of illness.

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 score0.028
Threshold uncertainty score0.204

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.249
Teacher spread0.235 · 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

Citations43
Published2016
Admission routes2
Has abstractyes

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