Central-line–Associated Bloodstream Infections Among Adult Intensive Care Unit Patients in Canadian Hospitals, 2011–2018
Bibliographic record
Abstract
Background: Nosocomial central-line–associated bloodstream infections (CLABSIs) are an important cause of morbidity and mortality in hospitalized patients. CLABSI surveillance establishes rates for internal and external comparison, identifies risk factors, and allows assessment of interventions. Objectives: To determine the frequency of CLABSIs among adult patients admitted to intensive care units (ICUs) in CNISP hospitals and evaluate trends over time. Methods: CNISP is a collaborative effort of the Canadian Hospital Epidemiology Committee, the Association of Medical Microbiologists and Infectious Disease Canada and the Public Health Agency of Canada. Since 1995, CNISP has conducted hospital-based sentinel surveillance of healthcare-associated infections. Overall, 55 CNISP hospitals participated in ≥1 year of CLABSI surveillance. Adult ICUs are categorized as mixed ICUs or cardiovascular (CV) surgery ICUs. Data were collected using standardized definitions and collection forms. Line-day denominators for each participating ICU were collected. Negative-binomial regression was used to test for linear trends, with robust standard errors to account for clustering by hospital. We used the Fisher exact test to compare binary variables. Results: Each year, 28–42 adult ICUs participated in surveillance (27–37 mixed, 6–8 CV surgery). In both mixed ICUs and CV-ICUs, rates remained relatively stable between 2011 and 2018 (Fig. 1). In mixed ICUs, CLABSI rates were 1.0 per 1,000 line days in 2011, and 1.0 per 1,000 line days in 2018 (test for linear trend, P = .66). In CV-ICUs, CLABSI rates were 1.1 per 1,000 line days in 2011 and 0.8 per 1,000 line days in 2018 ( P = .19). Case age and gender distributions were consistent across the surveillance period. The 30-day all-cause mortality rate was 29% in 2011 and in 2018 (annual range, 29%–35%). Between 2011 and 2018, the percentage of isolated microorganisms that were coagulase-negative staphylococci (CONS) decreased from 31% to 18% ( P = .004). The percentage of other gram-positive organisms increased from 32% to 37% ( P = .34); Bacillus increased from 0% to 4% of isolates and methicillin-susceptible Staphylococcus aureus from 2% to 6%). The gram-negative organisms increased from 21% to 27% ( P = .19). Yeast represented 16% in 2011 and 18% in 2018; however, the percentage of yeast that were Candida albicans decreased over time (58% of yeast in 2011 and 30% in 2018; P = .04). Between 2011 and 2018, the most commonly identified species of microorganism in each year were CONS (18% in 2018) and Enterococcus spp (18% in 2018). Conclusions: Ongoing CLABSI surveillance has shown stable rates of CLABSI in adult ICUs from 2011 to 2018. The causative microorganisms have changed, with CONS decreasing from 31% to 18%. Funding: CNISP is funded by the Public Health Agency of Canada. Disclosures: Allison McGeer reports funds to her for studies, for which she is the principal investigator, from Pfizer and Merck, as well as consulting fees from Sanofi-Pasteur, Sunovion, GSK, Pfizer, and Cidara.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".