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Record W4393869573 · doi:10.1017/cts.2024.271

297 Antibiotic prescribing for inpatients with community-acquired bacterial pneumonia (CABP) due to methicillin-resistant Staphylococcus aureus (MRSA) in the All of Us database: Are there differences by age, sex, race, and ethnicity?

2024· article· en· W4393869573 on OpenAlexfundno aff
Corbyn Gilmore, Christopher R. Frei

Bibliographic record

VenueJournal of Clinical and Translational Science · 2024
Typearticle
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsnot available
FundersCanadian Centre for Applied Research in Cancer ControlNorthwestern University
KeywordsStaphylococcus aureusAntibioticsMedicinePneumoniaMicrobiologyBiologyInternal medicineBacteria

Abstract

fetched live from OpenAlex

OBJECTIVES/GOALS: The purpose of this work is to assess antibiotic prescribing for inpatients with community-acquired bacterial pneumonia (CABP) due to methicillin-resistant Staphylococcus aureus (MRSA) in the All of Us database. The goal of this research is to determine if different subgroups are more or less likely to receive anti-MRSA antibiotics. METHODS/STUDY POPULATION: This is a retrospective cohort study of inpatients with CABP due to MRSA from 2/1/2011 to 7/1/2022 in the All of Us database. Cases will be excluded for other treatment settings, other pathogens, and other types of pneumonia. Patients will be stratified by age, sex, race, and ethnicity. The proportion of patients who received anti-MRSA antibiotic therapy will be compared within groups with the chi-square statistic. Significant associations between patient characteristics and anti-MRSA prescribing (p < 0.05) will be assessed using multivariate logistic regression, with subgroup as the independent variable, anti-MRSA prescribing as the dependent variable, and divergent baseline characteristics as potential confounders. Odds ratios (OR) and 95% confidence intervals (95% CI) will be calculated. RESULTS/ANTICIPATED RESULTS: Previous research by our group has demonstrated differences in guideline-concordant, empiric antibiotic prescribing, for inpatients with CABP in the All of Us database; however, guideline-concordant empiric antibiotics for CABP do not routinely cover for MRSA. Anti-MRSA antibiotics are recommended if the patient has known MRSA or risk factors for MRSA. Investigations of disparity in anti-MRSA prescribing have been limited, especially since the abandonment of the healthcare-associated pneumonia (HCAP) categorization. Since the All of Us database contains information on CABP pathogens, we can study sub-types of CABP; therefore, we now hypothesize that the proportion of inpatients who received anti-MRSA antibiotics for CABP, due to MRSA, in the All of Us database, will differ by age, race, sex, and ethnicity. DISCUSSION/SIGNIFICANCE: This is one of the first studies to evaluate antibiotic prescribing for CABP due to MRSA in the All of Usdatabase. Identifying and understanding differences in care, such as possible discrepancies in anti-MRSA prescribing by age, sex, race, or ethnicity, is essential to develop targeted interventions to address disparities in health outcomes.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.633
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.099
GPT teacher head0.385
Teacher spread0.286 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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