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A Risk Score to Predict Clostridioides difficile Infection
BACKGROUND: Clostridioides difficile infection (CDI) is a major cause of severe diarrhea. In this retrospective study, we identified CDI risk factors by comparing demographic and clinical characteristics for Kaiser Permanente Northern California members ≥18 years old with and without laboratory-conf...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953654/ https://www.ncbi.nlm.nih.gov/pubmed/33738316 http://dx.doi.org/10.1093/ofid/ofab052 |
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author | Aukes, Laurie Fireman, Bruce Lewis, Edwin Timbol, Julius Hansen, John Yu, Holly Cai, Bing Gonzalez, Elisa Lawrence, Jody Klein, Nicola P |
author_facet | Aukes, Laurie Fireman, Bruce Lewis, Edwin Timbol, Julius Hansen, John Yu, Holly Cai, Bing Gonzalez, Elisa Lawrence, Jody Klein, Nicola P |
author_sort | Aukes, Laurie |
collection | PubMed |
description | BACKGROUND: Clostridioides difficile infection (CDI) is a major cause of severe diarrhea. In this retrospective study, we identified CDI risk factors by comparing demographic and clinical characteristics for Kaiser Permanente Northern California members ≥18 years old with and without laboratory-confirmed incident CDI. METHODS: We included these risk factors in logistic regression models to develop 2 risk scores that predict future CDI after an Index Date for Risk Score Assessment (IDRSA), marking the beginning of a period for which we estimated CDI risk. RESULTS: During May 2011 to July 2014, we included 9986 CDI cases and 2 230 354 members without CDI. The CDI cases tended to be older, female, white race, and have more hospitalizations, emergency department and office visits, skilled nursing facility stays, antibiotic and proton pump inhibitor use, and specific comorbidities. Using hospital discharge as the IDRSA, our risk score model yielded excellent performance in predicting the likelihood of developing CDI in the subsequent 31–365 days (C-statistic of 0.848). Using a random date as the IDRSA, our model also predicted CDI risk in the subsequent 31–365 days reasonably well (C–statistic 0.722). CONCLUSIONS: These results can be used to identify high-risk populations for enrollment in C difficile vaccine trials and facilitate study feasibility regarding sample size and time to completion. |
format | Online Article Text |
id | pubmed-7953654 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-79536542021-03-17 A Risk Score to Predict Clostridioides difficile Infection Aukes, Laurie Fireman, Bruce Lewis, Edwin Timbol, Julius Hansen, John Yu, Holly Cai, Bing Gonzalez, Elisa Lawrence, Jody Klein, Nicola P Open Forum Infect Dis Major Articles BACKGROUND: Clostridioides difficile infection (CDI) is a major cause of severe diarrhea. In this retrospective study, we identified CDI risk factors by comparing demographic and clinical characteristics for Kaiser Permanente Northern California members ≥18 years old with and without laboratory-confirmed incident CDI. METHODS: We included these risk factors in logistic regression models to develop 2 risk scores that predict future CDI after an Index Date for Risk Score Assessment (IDRSA), marking the beginning of a period for which we estimated CDI risk. RESULTS: During May 2011 to July 2014, we included 9986 CDI cases and 2 230 354 members without CDI. The CDI cases tended to be older, female, white race, and have more hospitalizations, emergency department and office visits, skilled nursing facility stays, antibiotic and proton pump inhibitor use, and specific comorbidities. Using hospital discharge as the IDRSA, our risk score model yielded excellent performance in predicting the likelihood of developing CDI in the subsequent 31–365 days (C-statistic of 0.848). Using a random date as the IDRSA, our model also predicted CDI risk in the subsequent 31–365 days reasonably well (C–statistic 0.722). CONCLUSIONS: These results can be used to identify high-risk populations for enrollment in C difficile vaccine trials and facilitate study feasibility regarding sample size and time to completion. Oxford University Press 2021-02-04 /pmc/articles/PMC7953654/ /pubmed/33738316 http://dx.doi.org/10.1093/ofid/ofab052 Text en © The Author(s) 2021. 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 | Major Articles Aukes, Laurie Fireman, Bruce Lewis, Edwin Timbol, Julius Hansen, John Yu, Holly Cai, Bing Gonzalez, Elisa Lawrence, Jody Klein, Nicola P A Risk Score to Predict Clostridioides difficile Infection |
title | A Risk Score to Predict Clostridioides difficile Infection |
title_full | A Risk Score to Predict Clostridioides difficile Infection |
title_fullStr | A Risk Score to Predict Clostridioides difficile Infection |
title_full_unstemmed | A Risk Score to Predict Clostridioides difficile Infection |
title_short | A Risk Score to Predict Clostridioides difficile Infection |
title_sort | risk score to predict clostridioides difficile infection |
topic | Major Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7953654/ https://www.ncbi.nlm.nih.gov/pubmed/33738316 http://dx.doi.org/10.1093/ofid/ofab052 |
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