Epidemiology and Outcome of Pneumonia Caused by Methicillin-Resistant Staphylococcus aureus (MRSA) in Canadian Hospitals
Bibliographic record
Abstract
BACKGROUND: MRSA remains a leading cause of hospital-acquired (HAP) and healthcare-associated pneumonia (HCAP). We describe the epidemiology and outcome of MRSA pneumonia in Canadian hospitals, and identify factors contributing to mortality. METHODS: Prospective surveillance for MRSA pneumonia in adults was done for one year (2011) in 11 Canadian hospitals. Standard criteria for MRSA HAP, HCAP, ventilator-associated pneumonia (VAP), and community-acquired pneumonia (CAP) were used to identify cases. MRSA isolates underwent antimicrobial susceptibility testing, and were characterized by pulsed-field gel electrophoresis (PFGE) and Panton-Valentine leukocidin (PVL) gene detection. The primary outcome was all-cause mortality at 30 days. A multivariable analysis was done to examine the association between various host and microbial factors and mortality. RESULTS: A total of 161 patients with MRSA pneumonia were identified: 90 (56%) with HAP, 26 (16%) HCAP, and 45 (28%) CAP; 23 (14%) patients had VAP. The mean (± SD) incidence of MRSA HAP was 0.32 (± 0.26) per 10,000 patient-days, and of MRSA VAP was 0.30 (± 0.5) per 1,000 ventilator-days. The 30-day all-cause mortality was 28.0%. In multivariable analysis, variables associated with mortality were the presence of multiorgan failure (OR 8.1; 95% CI 2.5-26.0), and infection with an isolate with reduced susceptibility to vancomycin (OR 2.5, 95% CI 1.0-6.3). CONCLUSIONS: MRSA pneumonia is associated with significant mortality. Severity of disease at presentation, and infection caused by an isolate with elevated MIC to vancomcyin are associated with increased mortality. Additional studies are required to better understand the impact of host and microbial variables on outcome.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".