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Record W2143587674 · doi:10.1186/s12890-015-0062-7

Clinical outcomes associated with Staphylococcus aureus and Pseudomonas aeruginosa airway infections in adult cystic fibrosis patients

2015· article· en· W2143587674 on OpenAlexafffund
Heather G. Ahlgren, Andrea Benedetti, Jennifer Landry, Joanie Bernier, Elias Matouk, Danuta Radzioch, Larry C. Lands, Simon Rousseau, Dao Nguyen

Bibliographic record

VenueBMC Pulmonary Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsMcGill Genome CentreMcGill UniversityMcGill University Health Centre
FundersCystic Fibrosis CanadaMcGill University Health CentreMcGill UniversityBurroughs Wellcome Fund
KeywordsMedicineCystic fibrosisPseudomonas aeruginosaStaphylococcus aureusAirwayMicrobiologyImmunologyInternal medicineBacteriaSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Staphylococcus aureus (SA) is the most prevalent organism infecting the respiratory tract of CF children, and remains the second most prevalent organism in CF adults. During early childhood, SA infections are associated with pulmonary inflammation and decline in FEV1, but their clinical significance in adult CF patients is poorly characterized. METHODS: We conducted a retrospective cross-sectional study to determine the association between airway microbiology and clinical outcomes (FEV1, rate of pulmonary exacerbations, CRP levels and clinical scores). RESULTS: In a cohort of 84 adult CF patients, 24 % were infected with SA only, 60 % were infected with PA, and 16 % had neither PA nor SA. CF patients with SA experienced fewer pulmonary exacerbations and lower CRP levels than those with PA. CONCLUSION: In adult CF patients, SA infections alone, in the absence of PA, are a marker of milder disease.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.335
Teacher spread0.304 · 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

Citations78
Published2015
Admission routes2
Has abstractyes

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