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Record W2111788014 · doi:10.1017/s0950268812001872

A population-based study of the epidemiology and clinical features of methicillin-resistant <i>Staphylococcus aureus</i> infection in Pennsylvania, 2001–2010

2012· article· en· W2111788014 on OpenAlexfundno aff
Joan A. Casey, Sara E. Cosgrove, Walter F. Stewart, Jonathan Pollak, Brian S. Schwartz

Bibliographic record

VenueEpidemiology and Infection · 2012
Typearticle
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsnot available
FundersNational Institute of Environmental Health SciencesJohns Hopkins Bloomberg School of Public HealthSchool of Medicine, New York UniversityYork UniversityJohns Hopkins University
KeywordsMedicineEpidemiologyIncidence (geometry)Staphylococcus aureusMethicillin-resistant Staphylococcus aureusPopulationInternal medicineLogistic regressionAntibioticsEnvironmental healthMicrobiologyBiology

Abstract

fetched live from OpenAlex

No U.S. general population-based study has characterized the epidemiology and risk factors, including skin and soft tissue infection (SSTI), for healthcare-associated (HA) and community-associated (CA) methicillin-resistant Staphylococcus aureus (MRSA). We estimated the incidence of HA- and CA-MRSA and SSTI over a 9-year period using electronic health record data from the Geisinger Clinic in Pennsylvania. MRSA cases were frequency-matched to SSTI cases and controls in a nested case-control analysis. Logistic regression was used to assess risk factors, while accounting for antibiotic administration. We identified 1713 incident CA- and 1506 HA-MRSA cases and 78 216 SSTI cases. On average, from 2005 to 2009, the annual incidence of CA-MRSA increased by 34%, HA-MRSA by 7%, and SSTI by 4%. Age, season, community socioeconomic deprivation, obesity, smoking, previous SSTI, and antibiotic administration were identified as independent risk factors for CA-MRSA.

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)0.010
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.067
GPT teacher head0.385
Teacher spread0.319 · 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.

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

Citations67
Published2012
Admission routes1
Has abstractyes

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