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Culturing and Maintaining Clostridium difficile in an Anaerobic Environment
Published on: September 15, 2013
Clostridium difficile colitis: an efficient clinical approach to diagnosis
Y C Manabe1, J M Vinetz, R D Moore
1Johns Hopkins School of Medicine, Division of Infectious Diseases, Baltimore, MD 21205, USA.
Clinical factors like antibiotic timing and hospital stay, along with lab findings such as fecal leukocytes, help identify Clostridium difficile colitis. One stool sample is often sufficient to rule out this infection.
Area of Science:
- Infectious Diseases
- Gastroenterology
- Clinical Microbiology
Background:
- Clostridium difficile colitis is a significant healthcare-associated infection.
- Accurate and timely diagnosis is crucial for effective patient management and infection control.
- Identifying predictive factors can aid in clinical decision-making for diagnostic testing.
Purpose of the Study:
- To identify clinical and laboratory variables indicative of Clostridium difficile colitis.
- To determine the optimal number of stool specimens required to exclude the diagnosis.
Main Methods:
- Prospective study involving 268 inpatients with stool specimens tested for C. difficile toxin.
- Utilized enzyme-linked immunoassay (EIA) and tissue-culture assay for toxin detection.
- Assessed clinical data, antibiotic history, hospital stay duration, and fecal leukocyte presence.
Main Results:
- 43 of 268 inpatients tested positive for C. difficile toxin.
- Predictive factors included delayed antibiotic onset, prolonged hospital stay, fecal leukocytes, semiformed stools, and cephalosporin use.
- 79% of positive cases were identified with the first stool specimen; 91% with the second, yielding a 97% negative predictive value for the first sample.
Conclusions:
- Clinical and laboratory data can effectively guide the decision to test for C. difficile toxin.
- These factors also assist in determining when the diagnosis can be reasonably excluded.
- The findings support a targeted approach to C. difficile testing, optimizing resource utilization.
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