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  • Title: Prospective derivation and validation of a clinical prediction rule for recurrent Clostridium difficile infection.
    Author: Hu MY, Katchar K, Kyne L, Maroo S, Tummala S, Dreisbach V, Xu H, Leffler DA, Kelly CP.
    Journal: Gastroenterology; 2009 Apr; 136(4):1206-14. PubMed ID: 19162027.
    Abstract:
    BACKGROUND & AIMS: Prevention of recurrent Clostridium difficile infection (CDI) is a substantial therapeutic challenge. A previous prospective study of 63 patients with CDI identified risk factors associated with recurrence. This study aimed to develop a prediction rule for recurrent CDI using the above derivation cohort and prospectively evaluate the performance of this rule in an independent validation cohort. METHODS: The clinical prediction rule was developed by multivariate logistic regression analysis and included the following variables: age>65 years, severe or fulminant illness (by the Horn index), and additional antibiotic use after CDI therapy. A second rule combined data on serum concentrations of immunoglobulin G (IgG) against toxin A with the clinical predictors. Both rules were then evaluated prospectively in an independent cohort of 89 patients with CDI. RESULTS: The clinical prediction rule discriminated between patients with and without recurrent CDI, with an area under the curve of the receiver-operating-characteristic curve of 0.83 (95% confidence interval [CI]: 0.70-0.95) in the derivation cohort and 0.80 (95% CI: 0.67-0.92) in the validation cohort. The rule correctly classified 77.3% (95% CI: 62.2%-88.5%) and 71.9% (95% CI: 59.2%-82.4%) of patients in the derivation and validation cohorts, respectively. The combined rule performed well in the derivation cohort but not in the validation cohort (area under the curve of the receiver-operating-characteristic curve, 0.89 vs 0.62; diagnostic accuracy, 93.8% vs 69.2%, respectively). CONCLUSIONS: We prospectively derived and validated a clinical prediction rule for recurrent CDI that is simple, reliable, and accurate and can be used to identify high-risk patients most likely to benefit from measures to prevent recurrence.
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