902Hospital Characteristics and Infection Prevention and Control Strategies Associated with Methicillin-Resistant Staphylococcus aureus (MRSA) and Clostridium difficile Infection (CDI) in Canadian Hospitals
Bibliographic record
Abstract
Background. Measurement of the prevalence of antibiotic resistance assesses the associated burden of disease while also identifying vulnerable patient populations and monitoring the effectiveness of interventions. The objective of this study was to determine institutional characteristics, and infection prevention and control (IP&C) policies associated with MRSA colonization/infection, and C. difficile infection. Methods. In November 2012 a point-prevalence survey of MRSA and CDI was done in adult inpatients at Canadian acute-care hospitals with ≥50 beds. Information was also obtained regarding institutional characteristics and IP&C policies of each participating facility. Logistic regression models were designed using variables selected a priori and two-tailed p values less than 0.05 were considered significant. Results. 132 (56% of eligible) hospitals representing all 10 Canadian provinces participated in the survey and were included in the analysis. 60% of facilities were located within the central region of Canada (Ontario and Quebec), the majority (54%) had fewer than 200 beds, and were non-teaching hospitals (68%). The median prevalence of MRSA colonization/infection was 3.9% (range: 0-26.8%) and median MRSA infection prevalence was 0.3% (range: 0-4.9%). The presence of pediatrics in the hospital (p = 0.001), performing targeted vs universal admission screening (p < 0.001), routine placement of MRSA carriers in a private room (p < >0.001), routine use of surgical masks by staff caring for patients with MRSA (p = 0.005), decolonization with mupirocin (p < 0.001), and enhanced environmental cleaning of MRSA rooms (p = 0.006) were independently associated with a lower prevalence of MRSA colonization/infection. The median prevalence of CDI for participating facilities was 0.9% (0-5.5%). Teaching hospitals (p = 0.011) and facilities with a shorter turn-around-time (< 24 hrs) for C. difficile toxin assay results (p = 0.012) were associated with a higher prevalence of CDI. Conclusion. Although hospital characteristics are inalterable, this study identified IP&C policies that may be used to limit the spread of antibiotic resistance in acute-care hospitals. Disclosures. A. E. Simor, Pfizer Canada Inc.: Grant Investigator and Scientific Advisor, Grant recipient and honoraria; Cubist Pharmaceuticals: Scientific Advisor, honoraria
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 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) | 0.003 | 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".