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A Risk Score to Predict Clostridioides difficile Infection.


ABSTRACT:

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.

SUBMITTER: Aukes L 

PROVIDER: S-EPMC7953654 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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A Risk Score to Predict <i>Clostridioides difficile</i> Infection.

Aukes Laurie L   Fireman Bruce B   Lewis Edwin E   Timbol Julius J   Hansen John J   Yu Holly H   Cai Bing B   Gonzalez Elisa E   Lawrence Jody J   Klein Nicola P NP  

Open forum infectious diseases 20210204 3


<h4>Background</h4><i>Clostridioides difficile</i> 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.<h4>Methods</h4>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 Assess  ...[more]

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