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Record W2751061328 · doi:10.1093/ofid/ofx163.1452

Staphylococcus aureus Bacteremia (SAB) Management in a Large Metropolitan Integrated Health Region: Quality of Care Determinants (QoCD)

2017· article· en· W2751061328 on OpenAlexaff
John C. Lam, Stephen Robinson, Daniel B. Gregson, Ranjani Somayaji, Lisa Welikovitch, John Conly, Michael D. Parkins

Bibliographic record

VenueOpen Forum Infectious Diseases · 2017
Typearticle
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsAlberta Health ServicesUniversity of Calgary
Fundersnot available
KeywordsMedicineBacteremiaBlood cultureLogistic regressionInternal medicineCohortMethicillin-resistant Staphylococcus aureusRetrospective cohort studyEmergency medicineStaphylococcus aureusAntibiotics

Abstract

fetched live from OpenAlex

SAB is associated with significant morbidity and mortality. We undertook a study to determine how key quality determinants associated with SAB management were completed and to identify factors associated with failure to comply. Adults receiving care within an integrated health region of 1.3 million individuals with SAB from 2012–2014 were included in a retrospective analysis. Detailed chart reviews were performed to capture demographics, microbiology, investigations, treatment, and outcomes. Factors subject to QoCD included: repeat blood cultures, a transthoracic echocardiogram (TTE), infectious disease consultation (IDC), and if empiric MRSA coverage was provided. Multivariate logistic regression (STATA 14.2 (College Stn., TX)) was used to assess for statistically significant factors associated with each quality improvement metric. Between 2012 and 2014, 858 individuals experienced 964 distinct episodes of SAB (19.1% MRSA). The study cohort included patients who survived ≥48 hours (97.6%). Follow-up blood cultures were completed in 832 SAB episodes, of which 68.2% were performed within 48 hours. Factors associated with failure to perform repeat blood cultures included; increasing age (OR 1.01/yr.) and lack of IDC (OR 27.97). Almost 70% of patients underwent at least a TTE (median time from SAB of 2.6 days, IQR 1.14–4.49). Factors associated with failure to perform a TTE included; increasing age (OR 1.01/yr.), co-morbid liver disease (OR 1.92), absence of systemic emboli (OR 2.00), and lack of an IDC (OR 5.36). Empiric MRSA coverage within 48 hours of blood culture occurred in 74.4%. Factors associated with lack of receipt of empiric MRSA coverage included; increasing age (OR 1.03/yr.), declining GFR (OR 1.00) or absence of toxic changes (OR 1.97) on blood work within 24 hours of SAB, lack of IDC (OR 2.07) or identified emboli (OR 2.38). Despite improved compliance with SAB quality improvement metrics only 63.4% of patients were seen by the IDC service; median time from SAB 2.72 days (IQR 1.11–5.76). We identified significant gaps between the treatments and investigations patients received vs. optimal management. IDC was associated with improved attainment of targeted SAB QoCD but was underutilized. All authors: No reported disclosures.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.029
GPT teacher head0.376
Teacher spread0.347 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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