Hostname: page-component-76fb5796d-x4r87 Total loading time: 0 Render date: 2024-04-27T04:34:10.050Z Has data issue: false hasContentIssue false

Use of Varying Single-Nucleotide Polymorphism Thresholds to Identify Strong Epidemiologic Links Among Patients with Methicillin-Resistant Staphylococcus aureus (MRSA)

Published online by Cambridge University Press:  02 November 2020

Ioannis Zacharioudakis
Affiliation:
Bellevue Hospital/New York University
Dan Ding
Affiliation:
NYU Langone Health
Fainareti Zervou
Affiliation:
NYU
Anna Stachel
Affiliation:
NYU Langone Health
Sarah Hochman
Affiliation:
NYU Langone Health
Stephanie Sterling
Affiliation:
NYU
Jennifer Lighter
Affiliation:
NYU Langone Health
Maria Aguero-Rosenfeld
Affiliation:
NYU Langone Health
Bo Shopsin
Affiliation:
NYU Langone Medical Center
Michael Phillips
Affiliation:
NYU Langone Medical Center
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Background: Whole-genome sequencing (WGS) has a high discriminatory power in confirming outbreaks. Outbreak investigation models that categorize the possibility of an outbreak based on the degree of genetic relatedness of isolates are highly dependent on the single-nucleotide polymorphism (SNP) threshold used. Methods: NYU Langone Medical center is a 725-bed academic center that has implemented WGS of methicillin-resistant Staphylococcus aureus (MRSA) isolates since 2016. Patients admitted to a medical or intensive care unit were screened on admission and transfer. The first surveillance and clinical MRSA isolate during each hospitalization was sequenced. We conducted a retrospective analysis to identify strong epidemiologic links among patients involved in genetically related clusters. We used different SNP thresholds to define genetic relatedness to identify the optimal threshold that should prompt an outbreak investigation. We considered strong hospital epidemiologic links sharing the same room or unit or having resided in the same room or unit within 7 days. A pairwise analysis was conducted to compare the epidemiologic links among patients involved in genetically related clusters. Results: Among 1,070 isolates, our analysis focused on 777 belonging to USA100 and USA300 clones. For USA100 isolates, we identified 8, 14, and 20 clusters comprising of 16, 29, and 42 patients when the threshold for genetic relatedness was set at 20, 40, and 60 SNP differences, respectively. Patients identified in a cluster yielded a strong hospital epidemiologic link in 62.5%, 87.5%, and 91.7% of cases (Fig. 1). For USA300 isolates, SNP differences of 10, 20, and 30 were used, identifying 20, 34, and 40 clusters of 43, 79, and 127 patients. The expansion of the threshold from 10 to 30 resulted in a decrease of the percentage of pairwise analyses with a strong hospital epidemiologic link from 57.7% to 13.6% by increasing 13-fold the number of analyses that were conducted to identify only 3 times more cases with strong epidemiologic links (Fig. 2). Conclusions: The results of our study indicate that SNPs thresholds determined by intrapatient variability of MRSA isolates might need to be tailored to the individual setting to guide infection control interventions because optimal thresholds might vary depending on characteristics of the population, MRSA isolates, and screening practices. Establishing conservative thresholds might allow the identification and quantification over time of the locations (eg, rooms or units) where transmission is occurring as well as the investigation of the clusters without strong epidemiologic links that might be valuable in elucidating unrecognized routes of transmission.

Funding: None

Disclosures: None

Type
Poster Presentations
Copyright
© 2020 by The Society for Healthcare Epidemiology of America. All rights reserved.