Clostridium difficile classification overestimates hospital-acquired infections.

J Hosp Infect

Research School of Population Health, Australian National University, Canberra, Australia.

Published: August 2018

Background: Clostridium difficile infections occur frequently among hospitalized patients, with some infections acquired in hospital and others in the community. International guidelines classify cases as hospital-acquired if symptom onset occurs more than two days after admission. This classification informs surveillance and infection control, but has not been verified by empirical or modelling studies.

Aim: To assess current classification of C. difficile acquisition using a simulation model as a reference standard.

Methods: C. difficile transmission was simulated in a range of hospital scenarios. The sensitivity, specificity and precision of classifications that use cut-offs ranging from 0.25 h to 40 days were calculated. The optimal cut-off that correctly estimated the proportion of cases that were hospital acquired and the balanced cut-off that had equal sensitivity and specificity were identified.

Findings: The recommended two-day cut-off overestimated the incidence of hospital-acquired cases in all scenarios and by >100% in the base scenario. The two-day cut-off had good sensitivity (96%) but poor specificity (48%) and precision (52%) to identify cases acquired during the current hospitalization. A five-day cut-off was balanced, and a six-day cut-off was optimal in the base scenario. The optimal and balanced cut-offs were more than two days for nearly all scenarios considered (ranges: four to nine days and two to eight days, respectively).

Conclusion: Current guidelines for classifying C. difficile infections overestimate the proportion of cases acquired in hospital in all model scenarios. To reduce misclassification bias, an infection should be classified as being acquired prior to admission if symptoms begin within five days of admission.

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http://dx.doi.org/10.1016/j.jhin.2017.12.014DOI Listing

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