Methicillin-resistant <i>Staphylococcus</i> aureus nasal swabs: trends in use and association with outcomes
Bibliographic record
Abstract
Abstract Objective: To investigate patterns of early methicillin-resistant Staphylococcus aureus (MRSA) nasal swab use in US hospitals and the association with de-escalation of MRSA-specific antibiotics. Design: Retrospective cohort study. Setting: PINC-A1 Healthcare Database (2008–2021). Participants: Adults with sepsis present on admission who received invasive mechanical ventilation by hospital day 1. Methods: We assessed interhospital variation and time trends in early polymerase chain reaction-based MRSA nasal swab use using bivariable regression. Next, we used competing risks multivariable regression to assess the association of early (started by hospital day 2) anti-MRSA antibiotic duration with care in a high (≥90%) versus low (<10%) swab use hospital. Results: We included 699,474 patients across 788 hospitals to evaluate trends in early swab use; 151,205 (21.6%) received a swab. Use of swabs varied across hospitals (median use: 6.0% [interquartile range: 0–37.6%; full range: 0%–98.0%]; median odds ratio [95% CI]: 84.7 [63.3–115.6]) and overall use increased over time (3.5% in 2008 quarter 1 increasing to 29.5% in 2021 quarter 4; regression coefficient [95% CI]: 0.14% [0.12%–0.15%]). Considering 41,599 patients (9,796 [23.6%] in 33 hospitals where ≥90% received swabs and 31,763 [76.4%] in 67 hospitals with <10% use), anti-MRSA antibiotic durations were shorter in hospitals where ≥90% (vs < 10%) received a swab (adjusted sub-hazard ratio for discontinuation of antibiotics [95% CI]: 1.17 [1.04–1.31], P = .007). Conclusions: Use of early polymerase chain reaction-based MRSA nasal swabs varied across US hospitals and increased over time. Receiving care in a hospital with higher swab use was associated with shorter anti-MRSA antibiotic duration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".