Is Methicillin-Resistant Staphylococcus aureus More Virulent than Methicillin-Susceptible S. aureus? A Comparative Cohort Study of British Patients with Nosocomial Infection and Bacteremia
Bibliographic record
Abstract
Staphylococcus aureus is the most common cause of hospital-acquired bacteremia. From 1995 through 2000, data on age, sex, patient specialty at time of first bacteremia, primary and secondary sites of infection, delay in initiating antimicrobial therapy, and patient outcome were prospectively recorded for 815 patients with nosocomial S. aureus bacteremia. The proportion of patients whose death was attributable to methicillin-resistant S. aureus (MRSA) was significantly higher than that for methicillin-susceptible S. aureus (MSSA) (11.8% vs. 5.1%; odds ratio [OR], 2.49; 95% confidence interval [CI], 1.46-4.24; P<.001). After adjustment for host variables, the OR decreased to 1.72 (95% CI, 0.92-3.20; P=.09). There was no significant difference between rates of disseminated infection (7.1% vs. 6.2% for MRSA-infected patients and MSSA-infected patients, respectively; P=.63), though the rate of death due to disseminated infection was significantly higher than death due to uncomplicated infection (37% vs. 10% for MRSA-infected patients [P<.001] and 37% vs. 3% for MSSA-infected patients [P<.001]). There was a strong statistical trend toward death due to nosocomial MRSA infection and bacteremia, compared with MSSA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".