Device-associated infections in Canadian acute-care hospitals from 2009 to 2018
Bibliographic record
Abstract
BACKGROUND: Healthcare-associated infections (HAIs) pose a serious risk to patient safety and quality of care. The Canadian Nosocomial Infection Surveillance Program (CNISP) conducts national surveillance of HAIs at sentinel acute-care hospitals across Canada. This report provides an overview of 10 years of Canadian data on the epidemiology of select device-associated HAIs. METHODS: Over 40 hospitals submitted data between 2009 and 2018 for hip and knee surgical site infections (SSIs), cerebrospinal fluid shunt SSIs, paediatric cardiac SSIs and/or central line-associated bloodstream infections (CLABSIs). Counts, rates, patient and hospital characteristics, as well as pathogen distributions and antimicrobial susceptibilities are presented. RESULTS: (14%) were the most frequently reported pathogens. Gram-positive pathogens represented 68% of identified pathogens, gram-negative pathogens represented 22% and fungi represented 9%. CONCLUSION: Understanding the national burden of device-associated HAIs is essential for developing and maintaining benchmark rates for informing infection and prevention control and antimicrobial stewardship policies and programs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".