Antimicrobial use and antimicrobial resistance trends in Canada: 2014
Notice bibliographique
Résumé
Background: There is a global concern that the emergence of antimicrobial resistance (AMR) threatens our ability to treat infectious diseases.The Canadian Antimicrobial Resistance Surveillance System (CARSS) was created in response to the Government of Canada's commitment to address AMR.CARSS integrates information from nine different national surveillance systems for tracking antimicrobial use (AMU) and AMR in both humans and animals to inform AMU/AMR research and policy.Objective: To provide highlights of CARSS data on antimicrobial use in humans and animals, AMR trends in human infections in both hospital and community settings and AMR bacteria found in food production animals. Methods: Information on AMU in humans and animals is purchased and additional information on AMU in animals is collected through the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS). AMR data in humans focuses on first priority organisms. Data on priority organisms for hospital-based AMR is collected through Canadian Nosocomial Infection Surveillance Program (CNISP), Canadian Tuberculosis Laboratory Surveillance System (CTBLSS), Canadian Tuberculosis Reporting System (CTBRS) and CIPARS. Data on communitybased AMR is collected through CTBLSS, CTBRS, CIPARS, the Antimicrobial-resistant Neisseria gonorrhoeae Surveillance System (ARNGSS) and the National Surveillance of Invasive Streptococcal Disease (NSISD). AMR data on animals is collected through CIPARS.Results: In terms of antibiotic usage in 2014, approximately 82% of antimicrobials were directed to food production animals, 18% to humans and less than one percent to companion animals (e.g., pets) and crops.Over the past five years, 73% of antimicrobials distributed to food production animals belonged to the same classes as those used in human medicine.Antibiotic usage in humans has remained relatively stable.Trends in 2014 for AMR in hospitals include declining rates of hospital-acquired Clostridium difficile to 3.4 cases per 1,000 patient admissions, methicillin-resistant Staphylococcus aureus (MRSA) infections to 2.89 cases per 10,000 patient days and vancomycin -resistant Enterococci (VRE) to 0.45 cases per 10,000 patient days.Resistance to a number of antimicrobials used to treat Streptococcus pneumoniae has decreased since the introduction of pneumococcal vaccine in 2010.In contrast, trends in 2014 for AMR in the community included increasing rates of community-acquired N. gonorrhoeae -52.4% of isolates were resistant to at least one antibiotic.Trends for carbapenem-resistant Enterobacteriaceae (CRE) were stable at 0.22 cases per 10,000 patient days.Also, between 2004 and 2014, nine percent of tuberculosis (TB) culture positive cases were resistant to at least one first line anti-tuberculosis drug and this has remained relatively stable over that time.Trends in 2014 for AMR in food production animals showed decreasing resistance of Escherichia coli and Salmonella species to third-generation cephalosporins (ceftriaxone) in poultry associated with a decrease in cephalosporin use on chicken farms but resistance to ciprofloxacin in Campylobacter species in chicken and cattle has been increasing. Conclusion:Overall, antibiotic use in humans has not declined despite concerns about overuse.Although resistance rates of C. difficile, VRE, MRSA and AMR S. pneumoniae have been gradually decreasing, and drug-resistant tuberculosis and CRE have remained stable, community-associated drug-resistant N. gonorrhoeae has been increasing.Although efforts to decrease antibiotic use in animals have been met with some success, AMR continues to occur in fairly high levels in food production animals.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,008 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 source (Gemma direct ou Codex distillé), 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 ».