Journal
AMERICAN JOURNAL OF INFECTION CONTROL
Volume 51, Issue 8, Pages 879-883Publisher
MOSBY-ELSEVIER
DOI: 10.1016/j.ajic.2022.12.004
Keywords
Antibiotic-associated diarrhea; Clostridioides difficile infection; Hospital-onset; Children
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This study aimed to identify predictors of hospital-onset Clostridioides difficile infection (CDI) in pediatric patients with antibiotic-associated diarrhea (AAD) and develop a predictive scoring system for at-risk patients. The scoring system, based on identified predictors including abdominal pain, prolonged hospitalization, prolonged antibiotic use, and specific antibiotics received, can be easily used by clinicians to identify AAD patients likely to have CDI.
Background: This study aimed to determine the predictors of hospital-onset Clostridioides difficile infection (CDI) in pediatric patients with antibiotic-associated diarrhea (AAD) and to develop a predictive scoring system to identify at-risk patients. Methods: This retrospective case-control study included patients aged =2-18 years with AAD who underwent C. difficile polymerase chain reaction testing >3 days after hospital admission. Patients with hospital-onset CDI were selected as cases and matched with the control patients without CDI. Univariate and multi-variate logistic regressions were used to determine predictors of CDI and to construct a prediction score for the outcomes of interest. Results: Sixty-five patients with hospital-onset CDI and 130 controls were enrolled. Independent predictors for CDI identified and combined into the prediction score included abdominal pain (adjusted odds ratio [95% confidence interval]: 7.940 [3.254-19.374]), hospitalization for >= 14 days before the onset of diarrhea (3.441 [1.034-11.454]), antibiotic use for >= 10 days before the onset of diarrhea (6.775 [1.882-24.388]), receipt of meropenem (4.001 [1.098-14.577]) and clindamycin (14.842 [4.496-49.000]). The area under the receiver operating characteristic curve for this score was 0.883. Conclusions: The presented scoring system can be easily applied by clinicians at the bedside to decide which patients with AAD are likely to have CDI. (c) 2022 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
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