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2387. Learning the Influence of Individual Clostridioides difficile Infections

BACKGROUND: Healthcare-associated Clostridioides difficile infection (C diff infection, or CDI) imposes a substantial burden on the healthcare system. The impact of an individual C diff infection on onward transmission is not well understood. We developed a model of incident infections using self-ex...

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Autores principales: Mu, Emily, Makar, Maggie, West, Lauren R, Guttag, John, Rosenberg, David C, Shenoy, Erica S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6810728/
http://dx.doi.org/10.1093/ofid/ofz360.2065
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author Mu, Emily
Makar, Maggie
West, Lauren R
Guttag, John
Rosenberg, David C
Shenoy, Erica S
author_facet Mu, Emily
Makar, Maggie
West, Lauren R
Guttag, John
Rosenberg, David C
Shenoy, Erica S
author_sort Mu, Emily
collection PubMed
description BACKGROUND: Healthcare-associated Clostridioides difficile infection (C diff infection, or CDI) imposes a substantial burden on the healthcare system. The impact of an individual C diff infection on onward transmission is not well understood. We developed a model of incident infections using self-exciting stochastic processes, known as Hawkes processes. These models can be used to improve our understanding of the factors that affect the likelihood of new infections to result in additional infections. METHODS: All patients admitted to a large urban hospital between January 2013 and June 2014 were included. We used Hawkes processes to model the influence of each new CDI case (index infection) on transmission to other patients resulting in additional CDI. We developed separate Hawkes processes for each unit in the hospital to understand the differential impact of a C diff case across units. Units included both semi- and private-room wards, intensive care units, an emergency department, and specialty units such as oncology. RESULTS: The magnitude of influence of an index infection on additional infections in the 2 days prior to a C diff test being sent varied across units. Results for an oncology unit, the emergency department, and an all private-room unit are provided (Table 1). An index infection in the emergency department demonstrated the greatest influence, leading to the largest number of additional infections, and increasing in the days leading up to the C diff test being sent. The impact 2 days prior to sample collection was similar across all unit types, and remained constant for oncology unit patients. CONCLUSION: We used Hawkes processes to model the impact of an index C diff infection on onward transmission. We identified differential impacts associated with the unit where the index patient was located in the days leading up to diagnosis. These differences, which could relate to unit-specific factors such as cleaning practices, patient turnover rates, use of portable medical equipment, antibiotic use, and other factors that vary across units, suggest that interventions aimed at controlling CDI may need to consider unit-specific approaches. [Image: see text] DISCLOSURES: All authors: No reported disclosures.
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spelling pubmed-68107282019-10-28 2387. Learning the Influence of Individual Clostridioides difficile Infections Mu, Emily Makar, Maggie West, Lauren R Guttag, John Rosenberg, David C Shenoy, Erica S Open Forum Infect Dis Abstracts BACKGROUND: Healthcare-associated Clostridioides difficile infection (C diff infection, or CDI) imposes a substantial burden on the healthcare system. The impact of an individual C diff infection on onward transmission is not well understood. We developed a model of incident infections using self-exciting stochastic processes, known as Hawkes processes. These models can be used to improve our understanding of the factors that affect the likelihood of new infections to result in additional infections. METHODS: All patients admitted to a large urban hospital between January 2013 and June 2014 were included. We used Hawkes processes to model the influence of each new CDI case (index infection) on transmission to other patients resulting in additional CDI. We developed separate Hawkes processes for each unit in the hospital to understand the differential impact of a C diff case across units. Units included both semi- and private-room wards, intensive care units, an emergency department, and specialty units such as oncology. RESULTS: The magnitude of influence of an index infection on additional infections in the 2 days prior to a C diff test being sent varied across units. Results for an oncology unit, the emergency department, and an all private-room unit are provided (Table 1). An index infection in the emergency department demonstrated the greatest influence, leading to the largest number of additional infections, and increasing in the days leading up to the C diff test being sent. The impact 2 days prior to sample collection was similar across all unit types, and remained constant for oncology unit patients. CONCLUSION: We used Hawkes processes to model the impact of an index C diff infection on onward transmission. We identified differential impacts associated with the unit where the index patient was located in the days leading up to diagnosis. These differences, which could relate to unit-specific factors such as cleaning practices, patient turnover rates, use of portable medical equipment, antibiotic use, and other factors that vary across units, suggest that interventions aimed at controlling CDI may need to consider unit-specific approaches. [Image: see text] DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2019-10-23 /pmc/articles/PMC6810728/ http://dx.doi.org/10.1093/ofid/ofz360.2065 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Abstracts
Mu, Emily
Makar, Maggie
West, Lauren R
Guttag, John
Rosenberg, David C
Shenoy, Erica S
2387. Learning the Influence of Individual Clostridioides difficile Infections
title 2387. Learning the Influence of Individual Clostridioides difficile Infections
title_full 2387. Learning the Influence of Individual Clostridioides difficile Infections
title_fullStr 2387. Learning the Influence of Individual Clostridioides difficile Infections
title_full_unstemmed 2387. Learning the Influence of Individual Clostridioides difficile Infections
title_short 2387. Learning the Influence of Individual Clostridioides difficile Infections
title_sort 2387. learning the influence of individual clostridioides difficile infections
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6810728/
http://dx.doi.org/10.1093/ofid/ofz360.2065
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