Impact of California’s Senate Bill 27 on Antimicrobial-Resistant Escherichia coli Urinary Tract Infection in Humans: Protocol for a Study of Methods and Baseline Data
Notice bibliographique
Résumé
BACKGROUND: Overuse of antibiotics contributes to antimicrobial resistance (AMR) and is a growing threat to human health worldwide. Previous work suggests a link between antimicrobial use in poultry and human AMR extraintestinal pathogenic Escherichia coli (E coli) urinary tract infections (UTIs). However, few US-based studies exist, and none have comprehensively assessed both foodborne and environmental pathways using advanced molecular and spatial epidemiologic methods in a quasi-experimental design. Recently, California enacted Senate Bill 27 (SB27), which changed previous policy to require a veterinarian's prescription for the use of antibiotic drugs, and which banned antibiotic use for disease prevention in livestock. This provided an opportunity to evaluate whether SB27 will result in a reduction in antimicrobial-resistant infections in humans. OBJECTIVE: We describe in detail the methods implemented to achieve the overarching objective of this study to evaluate the impact of SB27 on downstream antibiotic resistance rates in human UTIs. METHODS: A summary of the overall approach and the partnerships between Columbia University, George Washington University (GWU), Johns Hopkins Bloomberg School of Public Health, Kaiser Permanente Southern California (KPSC) Research and Evaluation, the Natural Resources Defense Council, Sanger Institute at Stanford University, Sutter Health Center for Health Systems Research, the University of Cambridge, and the University of Oxford is presented. The collection, quality control testing, and shipment of retail meat and clinical samples are described. Retail meat (chicken, beef, turkey, and pork) was purchased from stores throughout Southern California from 2017 to 2021. After processing at KPSC, it was shipped to GWU for testing. From 2016 to 2021, after clinical specimens were processed for routine clinical purposes and immediately before discarding, those with isolated colonies of E coli, Campylobacter, and Salmonella from KPSC members were collected and processed to be shipped for testing at GWU. Detailed methods of the isolation and testing as well as the whole-genome sequencing of the meat and clinical samples at GWU are described. KPSC electronic health record data were used to track UTI cases and AMR patterns among the cultured specimens. Similarly, Sutter Health electronic health record data were used to track UTI cases in its Northern California patient population. RESULTS: From 2017 to 2021, overall, 12,616 retail meat samples were purchased from 472 unique stores across Southern California. In addition, 31,643 positive clinical cultures were collected from KPSC members during the same study period. CONCLUSIONS: Here, we presented data collection methods for the study, which was conducted to evaluate the impact of SB27 on downstream antibiotic resistance rates in human UTI. To date, it is one of the largest studies of its kind to be conducted. The data collected during this study will be used as the foundation for future analyses specific to the various objectives of this large body of work. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/45109.
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 | 0,055 | 0,048 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,003 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,008 | 0,003 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,006 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,049 | 0,014 |
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 ».