Predicting Clostridium difficile Toxin in Hospitalized Patients With Antibiotic-Associated Diarrhea
- 1 April 2007
- journal article
- Published by Cambridge University Press (CUP) in Infection Control & Hospital Epidemiology
- Vol. 28 (4) , 377-381
- https://doi.org/10.1086/513723
Abstract
Objective.: Clostridium difficile infection is implicated in 20%-30% of cases of antibiotic-associated diarrhea. Studying hospitalized patients who received antibiotic therapy and developed diarrhea, our objective was to compare the clinical characteristics of patients who developed C. difficile–associated diarrhea (CDAD) with those of patients with a negative result of a stool assay for C. difficile toxin.Methods.: A prospective study was done with a cohort of 217 hospitalized patients who had received antibiotics and developed diarrhea. Patients with CDAD were defined as patients who had diarrhea and a positive result for C. difficile toxin A/B by an enzyme immunoassay of stool. The variables that yielded a significant difference on univariate analysis between patients with a positive assay result and patients with a negative assay result were entered into a logistic regression model for prediction of C. difficile toxin.Setting.: A 900-bed tertiary care medical center.Results.: Of 217 patients, 52 (24%) had a positive result of assay for C. difficile toxin A/B in their stool. The logistic regression model included impaired functional capacity, watery diarrhea, use of a proton pump inhibitor, use of a histamine receptor blocker, leukocytosis, and hypoalbuminemia. The area under the receiver operating characteristic curve for the model as a predictor of a positive result for the stool toxin assay was 0.896 (95% confidence interval, 0.661-1.000; P<.001), with 95% specificity and 68% sensitivity.Conclusions.: Our results may help clinicians to predict the risk of CDAD in hospitalized patients with antibiotic-associated diarrhea, to guide careful, specific empirical therapy, and to direct early attention to infection control issues.Keywords
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