Central-line–Associated Bloodstream Infections Among Adult Intensive Care Unit Patients in Canadian Hospitals, 2011–2018
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».