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525. The Impact of Switching to Molecular Testing on Clostridium difficile Infection Rates: Large-Scale Assessment Using an Interrupted Time Series Poisson Regression Approach

BACKGROUND: Clostridium difficile is the most common cause of hospital-acquired infections in the United States, affecting over 500,000 patients per year at a cost of nearly $5 billion. The reported incidence of C. difficile infections (CDIs) has increased in recent years, partly due to broad adopti...

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Autores principales: Jabur, Tiago Barbieri Couto, Ilies, Iulian, Baker, Arthur W, Anderson, Deverick J, Benneyan, James
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6255478/
http://dx.doi.org/10.1093/ofid/ofy210.534
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author Jabur, Tiago Barbieri Couto
Ilies, Iulian
Baker, Arthur W
Anderson, Deverick J
Benneyan, James
author_facet Jabur, Tiago Barbieri Couto
Ilies, Iulian
Baker, Arthur W
Anderson, Deverick J
Benneyan, James
author_sort Jabur, Tiago Barbieri Couto
collection PubMed
description BACKGROUND: Clostridium difficile is the most common cause of hospital-acquired infections in the United States, affecting over 500,000 patients per year at a cost of nearly $5 billion. The reported incidence of C. difficile infections (CDIs) has increased in recent years, partly due to broad adoption of polymerase chain reaction (PCR) testing replacing enzyme-linked immunosorbent assay (ELISA) methods. Our aim was to assess the contribution of this change on reported CDI incidence using a large-scale empirical data set. METHODS: We retrospectively analyzed 8 years of CDI surveillance data (2009–2016) collected from 47 hospitals in the Duke Infection Control Outreach Network. During this period, 24 hospitals switched to PCR testing, 10 used ELISA throughout, and 13 used PCR throughout. We used interrupted time series analysis to quantify the relative change in incidence rate (IRR) of CDIs due to the switch from nonmolecular (ELISA) to molecular (PCR) testing. Data were aligned across hospitals at their interruption point, set at the reported test change date or nearest available measurement. Individual hospital and network-wide estimates of the PCR-over-ELISA IRR were determined through Poisson regression, controlling for total patient days, proportion of intensive care unit patient-days as a proxy for acuity, background trends, and previously detected clusters. RESULTS: Average monthly CDI rates significantly increased after the test change from 11.7 to 26.8 per 10,000 patient-days in hospitals that switched to PCR testing. A similar difference was observed between ELISA-only and PCR-only hospitals, which averaged 12.7 and 21.0 CDIs per 10,000 patient-days, respectively. Regression analysis yielded hospital-specific test change IRRs ranging from 0.70 (95% confidence interval [CI]: 0.48–1.02) to 3.64 (CI: 2.77–8.46) (Figure 1) and a network-wide IRR of 1.79 (CI: 1.73–1.90). Results also found an increasing background trend of 0.9 CDIs per 10,000 patient-days per year (CI: 0.7–1.2) (Figure 2), as well as a significant effect of known clusters (IRR of 1.56, CI: 1.48–1.65). CONCLUSION: Hospitals that switched to molecular testing experienced an average post-change increase of 80% in reported CDI rates, similar to that observed during known cluster periods. [Image: see text] [Image: see text] DISCLOSURES: All authors: No reported disclosures.
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spelling pubmed-62554782018-11-28 525. The Impact of Switching to Molecular Testing on Clostridium difficile Infection Rates: Large-Scale Assessment Using an Interrupted Time Series Poisson Regression Approach Jabur, Tiago Barbieri Couto Ilies, Iulian Baker, Arthur W Anderson, Deverick J Benneyan, James Open Forum Infect Dis Abstracts BACKGROUND: Clostridium difficile is the most common cause of hospital-acquired infections in the United States, affecting over 500,000 patients per year at a cost of nearly $5 billion. The reported incidence of C. difficile infections (CDIs) has increased in recent years, partly due to broad adoption of polymerase chain reaction (PCR) testing replacing enzyme-linked immunosorbent assay (ELISA) methods. Our aim was to assess the contribution of this change on reported CDI incidence using a large-scale empirical data set. METHODS: We retrospectively analyzed 8 years of CDI surveillance data (2009–2016) collected from 47 hospitals in the Duke Infection Control Outreach Network. During this period, 24 hospitals switched to PCR testing, 10 used ELISA throughout, and 13 used PCR throughout. We used interrupted time series analysis to quantify the relative change in incidence rate (IRR) of CDIs due to the switch from nonmolecular (ELISA) to molecular (PCR) testing. Data were aligned across hospitals at their interruption point, set at the reported test change date or nearest available measurement. Individual hospital and network-wide estimates of the PCR-over-ELISA IRR were determined through Poisson regression, controlling for total patient days, proportion of intensive care unit patient-days as a proxy for acuity, background trends, and previously detected clusters. RESULTS: Average monthly CDI rates significantly increased after the test change from 11.7 to 26.8 per 10,000 patient-days in hospitals that switched to PCR testing. A similar difference was observed between ELISA-only and PCR-only hospitals, which averaged 12.7 and 21.0 CDIs per 10,000 patient-days, respectively. Regression analysis yielded hospital-specific test change IRRs ranging from 0.70 (95% confidence interval [CI]: 0.48–1.02) to 3.64 (CI: 2.77–8.46) (Figure 1) and a network-wide IRR of 1.79 (CI: 1.73–1.90). Results also found an increasing background trend of 0.9 CDIs per 10,000 patient-days per year (CI: 0.7–1.2) (Figure 2), as well as a significant effect of known clusters (IRR of 1.56, CI: 1.48–1.65). CONCLUSION: Hospitals that switched to molecular testing experienced an average post-change increase of 80% in reported CDI rates, similar to that observed during known cluster periods. [Image: see text] [Image: see text] DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2018-11-26 /pmc/articles/PMC6255478/ http://dx.doi.org/10.1093/ofid/ofy210.534 Text en © The Author(s) 2018. 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
Jabur, Tiago Barbieri Couto
Ilies, Iulian
Baker, Arthur W
Anderson, Deverick J
Benneyan, James
525. The Impact of Switching to Molecular Testing on Clostridium difficile Infection Rates: Large-Scale Assessment Using an Interrupted Time Series Poisson Regression Approach
title 525. The Impact of Switching to Molecular Testing on Clostridium difficile Infection Rates: Large-Scale Assessment Using an Interrupted Time Series Poisson Regression Approach
title_full 525. The Impact of Switching to Molecular Testing on Clostridium difficile Infection Rates: Large-Scale Assessment Using an Interrupted Time Series Poisson Regression Approach
title_fullStr 525. The Impact of Switching to Molecular Testing on Clostridium difficile Infection Rates: Large-Scale Assessment Using an Interrupted Time Series Poisson Regression Approach
title_full_unstemmed 525. The Impact of Switching to Molecular Testing on Clostridium difficile Infection Rates: Large-Scale Assessment Using an Interrupted Time Series Poisson Regression Approach
title_short 525. The Impact of Switching to Molecular Testing on Clostridium difficile Infection Rates: Large-Scale Assessment Using an Interrupted Time Series Poisson Regression Approach
title_sort 525. the impact of switching to molecular testing on clostridium difficile infection rates: large-scale assessment using an interrupted time series poisson regression approach
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6255478/
http://dx.doi.org/10.1093/ofid/ofy210.534
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