Impact of COVID-19 on healthcare-associated infections in Canadian acute-care hospitals: Interrupted time series (2018–2021)
Notice bibliographique
Résumé
Background: Data regarding the effects of the SARS-COV-2 (COVID-19) pandemic on healthcare-associated infections (HAIs) in Canadian acute-care hospitals are limited. We examined the impact of the COVID-19 pandemic on HAIs and antimicrobial resistant organisms in hospitals participating in the Canadian Nosocomial Infection Surveillance Program. Methods: We analyzed 13,406 HAIs including adult mixed intensive care unit (ICU) central-line–associated bloodstream infections (CLABSIs), and healthcare-associated (HA) Clostridioides difficile infection (CDI), methicillin-resistant Staphylococcus aureus (MRSA) bloodstream infections (BSI), vancomycin-resistant Enterococcus (VRE) BSI, and carbapenemase-producing Enterobacterales (CPE) infections collected using standardized case definitions and questionnaires from 29–64 hospitals participating in the Canadian Nosocomial Infection Surveillance Program (CNISP) from January 2018 to December 2021. We used a generalized linear mixed model with quasi-Poisson distribution to assess step and slope changes in monthly HAI rates between the pre–COVID-19 pandemic period (January 1, 2018–February 29, 2020; 26 time points) and the COVID-19 pandemic period (March 1, 2020–December 31, 2021; 22 time points). Results were reported as incidence rate ratios (IRRs) with 95% confidence intervals (CIs) and adjusted for seasonality, hospital clustering, and hospital characteristics of interest. Results: In the CNISP network, 7,352 (55%) HAIs were reported in the prepandemic period and 6,054 (45%) in the pandemic period. Median age was significantly younger during the pandemic period compared to the prepandemic period among patients with HA-CDI, HA-MRSA BSI, and adult mixed ICU CLABSIs, and more than half of cases among all reported HAIs were male (range, 52%–65%). The 30-day all-cause in-hospital mortality rate did not significantly change between the prepandemic and pandemic periods for all reported HAIs and was highest among HA-VRE BSIs (34%). Modeling results indicated that the COVID-19 pandemic was associated with an immediate increase in HA-CDI and adult mixed ICU CLABSI rates whereas HA-MRSA BSI, HA-CPE and HA-VRE BSI rates immediately decreased. However, pandemic status did not have a statistically significant lasting impact on monthly rate trends for all reported HAIs after adjusting for seasonality, clustering, and hospital covariates (Fig. 1 and 2). Adjusted IRRs for all HAIs ranged from 1.00 to 1.01 (95% CI, 0.94–0.99 to 1.01–1.05). Conclusions: Although the COVID-19 pandemic placed a significant burden on the Canadian healthcare system, the immediate impact on monthly rates of HAIs in Canadian acute-care hospitals was not sustained over time. Understanding the epidemiological effects of the COVID-19 pandemic in the context of changing patient populations, and clinical and infection control practices, are essential to inform the continued management and prevention of HAIs in Canadian acute-care settings. Disclosures: None
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,001 |
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 ».