Community- versus healthcare-acquired bloodstream infections at Groote Schuur Hospital, Cape Town, South Africa
Notice bibliographique
Résumé
BACKGROUND: Bloodstream infections (BSIs) cause considerable morbidity and mortality. The epidemiology of bacterial infections differs in community and hospital settings. Regular surveillance and reporting of pathogens and antimicrobial susceptibility can assist in appropriate management of BSIs. OBJECTIVES: To describe the distribution of organisms and of antibiotic susceptibility among isolates from blood cultures at a tertiary academic hospital during a 1-year period, stratifying by place of infection acquisition. METHODS: This was a retrospective descriptive study of bloodstream isolates from cultures from adults (>13 years of age) routinely submitted between 1 October 2011 and 30 September 2012 to the clinical laboratory at Groote Schuur Hospital, Cape Town, South Africa. Community-acquired infections were compared with healthcare-acquired infections, defined as infections developing at least 48 hours after admission or within 3 months of admission to a healthcare facility. Frequencies and proportions of infecting organisms are presented, along with susceptibility results for selected pathogens. The hospital-acquired isolates were stratified by ward (emergency, general medical or general surgical ward or intensive care unit (ICU)) to determine organism frequency and susceptibility patterns by hospital ward. RESULTS: Among adults, 740 non-duplicate pathogens were isolated from BSIs. Nearly three-quarters of infections were healthcare acquired. Enterobacteriaceae and non-fermentative Gram-negative bacilli were predominant among healthcare-acquired pathogens (39.2% and 28.5%, respectively), while Enterobacteriaceae and Gram-positive organisms were the most common among community-acquired pathogens (39.2% and 54.3%, respectively). The majority of community-acquired Enterobacteriaceae were highly susceptible to antibiotics (gentamicin 95.6%, ceftriaxone 96.1% and ciprofloxacin 92.2%), whereas 64.6% of healthcare-associated isolates were susceptible to gentamicin, 58.5% to ceftriaxone and 70% to ciprofloxacin. All community-acquired Staphylococcus aureus isolates v. 52.4% of healthcare-acquired isolates were susceptible to cloxacillin. The susceptibility of healthcare-acquired Pseudomonas aeruginosa and Acinetobacter baumanii complex isolates was <80% to all antibiotics with the exception of colistin. Klebsiella spp., S. aureus and Escherichia coli were the commonest causes of healthcare-acquired infections in all areas outside of the ICUs, whereas Acinetobacter was common in the ICUs and rare in all other areas. CONCLUSION: The distinction between community- and healthcare-acquired infections is critical in antibiotic selection because narrow-spectrum agents can be utilised for community-acquired infections. The considerable antibiotic resistance of healthcare-acquired pathogens highlights the importance of infection prevention and control. This type of surveillance could be incorporated into routine laboratory practice.
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 | 0,000 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 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 ».