2453. Wastewater-Based Surveillance of Vancomycin-Resistant Enterococci in Hospitals
Notice bibliographique
Résumé
Abstract Background Vancomycin-resistant Enterococcus (VRE) is an important nosocomial infection that may increase patient morbidity, mortality, and healthcare costs. We have adapted wastewater-based surveillance (WBS) as a novel tool to comprehensively and inclusively monitor the burden of VRE in tertiary acute care hospitals. Herein, we demonstrate our ability to detect, quantify and track VRE dynamically over time across a range of scales. Methods Wastewater (WW) was collected from three hospitals in Calgary, AB: Rockyview General Hospital (RGH; 615 beds), Peter Lougheed Centre (PLC; 517 beds), and Foothills Medical Centre (FMC via three independent sites – A, B, C; 1100 beds). Three WW treatment plants (WWTPs; BBW, PCW, and FCW) serving the entire City of Calgary were sampled as community controls. DNA was extracted from WW pellets obtained following centrifugation. A multiplexed qPCR assay was adapted and used to quantify the abundances of the vanA and vanB resistance gene copies. Copy numbers were assessed as raw (copies per mL of WW processed) or normalized against three fecal biomarker genes: total bacterial 16S rRNA, human 18S rRNA, and Bacteroides HF183 16S rRNA. Differences between hospitals and controls were determined with Mann-Whitney tests (GraphPad Prism version 9.0). Results Samples from the hospitals and WWTPs in Calgary, AB collected over 12 weeks demonstrated that all hospitals had 100-1000X higher mean aggregate abundances of both vanA and vanB relative to community-based WWTPs when assessed as raw or normalized by each fecal biomarker (Figure 1; only total bacterial 16S rRNA is shown, p< 0.001, Mann-Whitney). Within one individual hospital (RGH), each of vanA and vanB abundances follows similar trends over a 12-week period, regardless of whether the values were reported as raw or normalized with the three different fecal biomarker genes (Figure 2; only vanA is shown).Figure 1.Mean aggregate copy numbers of vanA and vanB in wastewater measured by qPCR. VRE vanA and vanB gene abundances normalized as a ratio against total bacterial 16S rRNA copies demonstrate significantly higher abundances of both vanA and vanB in hospitals than the WWTP community controls.Figure 2.Comparison of vanA gene copies assessed as raw versus normalized as measured by qPCR from Rockyview General Hospital (RGH). VRE vanA gene abundances in Rockyview General Hospital (RGH) WW assessed as raw and normalized as a ratio against three different fecal biomarkers (total bacterial 16S rRNA, human 18S rRNA and Bacteroides HF183 16S rRNA) demonstrated similar trends in vanA gene abundances over time. Conclusion WBS is a unique real-time tool that can be adapted to monitor the abundance of VRE across a range of scales. This tool has the potential to augment antimicrobial stewardship and infection prevention and control programs to better understand the contributing factors to selection and colonization. Disclosures All Authors: No reported disclosures
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».