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External Validation of Three Prediction Tools for Patients at Risk of a Complicated Course of Clostridium difficile Infection: Disappointing in an Outbreak Setting

Published online by Cambridge University Press:  08 June 2017

Yvette H. van Beurden*
Affiliation:
Department of Gastroenterology and Hepatology, VU Medical Center, Amsterdam, The Netherlands Department of Medical Microbiology and Infection Control, VU Medical Center, Amsterdam, The Netherlands
Marjolein P. M. Hensgens
Affiliation:
Department of Internal Medicine, Meander Medical Center, Amersfoort, The Netherlands
Olaf M. Dekkers
Affiliation:
Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands Department of Endocrinology and Metabolic Diseases, Leiden University Medical Center, Leiden, The Netherlands
Saskia Le Cessie
Affiliation:
Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
Chris J. J. Mulder
Affiliation:
Department of Gastroenterology and Hepatology, VU Medical Center, Amsterdam, The Netherlands
Christina M. J. E. Vandenbroucke-Grauls
Affiliation:
Department of Medical Microbiology and Infection Control, VU Medical Center, Amsterdam, The Netherlands
*
Address correspondence to Yvette H. van Beurden, MD, Department of Gastroenterology & Hepatology, VU University medical center, De Boelelaan 1118, Room PK 2 X 132, 1081 HV Amsterdam, The Netherlands (y.vanbeurden@vumc.nl).

Abstract

OBJECTIVE

Estimating the risk of a complicated course of Clostridium difficile infection (CDI) might help doctors guide treatment. We aimed to validate 3 published prediction models: Hensgens (2014), Na (2015), and Welfare (2011).

METHODS

The validation cohort comprised 148 patients diagnosed with CDI between May 2013 and March 2014. During this period, 70 endemic cases of CDI occurred as well as 78 cases of CDI related to an outbreak of C. difficile ribotype 027. Model calibration and discrimination were assessed for the 3 prediction rules.

RESULTS

A complicated course (ie, death, colectomy, or ICU admission due to CDI) was observed in 31 patients (21%), and 23 patients (16%) died within 30 days of CDI diagnosis. The performance of all 3 prediction models was poor when applied to the total validation cohort with an estimated area under the curve (AUC) of 0.68 for the Hensgens model, 0.54 for the Na model, and 0.61 for the Welfare model. For those patients diagnosed with CDI due to non-outbreak strains, the prediction model developed by Hensgens performed the best, with an AUC of 0.78.

CONCLUSION

All 3 prediction models performed poorly when using our total cohort, which included CDI cases from an outbreak as well as endemic cases. The prediction model of Hensgens performed relatively well for patients diagnosed with CDI due to non-outbreak strains, and this model may be useful in endemic settings.

Infect Control Hosp Epidemiol 2017;38:897–905

Type
Original Articles
Copyright
© 2017 by The Society for Healthcare Epidemiology of America. All rights reserved 

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