Methicillin-resistant/methicillin-sensitive Staphylococcus aureus bacteremia
Bibliographic record
Abstract
OBJECTIVE: To examine the differences between the clinical presentation, management and outcome of persons bacteremic with methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-sensitive Staphylococcus aureus (MSSA), after controlling for age, sex and primary diagnosis. METHODS: A review of the clinical records and laboratory data of all MRSA and MSSA bacteremic patients. Fifty matched case-control pairs were further analyzed looking for differences between the 2 populations. The study was carried out in a 500-bed adult tertiary care institution in southwestern Ontario, Canada, between 1994 and 1999. RESULTS: On univariate analysis a) duration of hospitalization prior to bacteremia, b) concomitant polymicrobial bacteremia, c) time to appropriate treatment, were significantly greater in the MRSA infected population. Attributable mortality was also higher, 36%-20%, but this did not achieve significance (p=0.1). On multiple logistic regression analysis, a), b) and c) remained significantly different. CONCLUSION: In a 1:1 matched case-control study of Staphylococcus aureus bacteremia, those infected with MRSA became bacteremic later in their hospital stay, more often had a polymicrobial bacteremia and were appropriately treated later. Although mortality attributable to the MRSA bacteremia was greater, this difference did not achieve significance.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".