Fecal calprotectin for diagnosis of organic bowel diseases :- Medznat
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Fecal calprotectin can help predict organic bowel diseases

Fecal calprotectin can help predict organic bowel diseases Fecal calprotectin can help predict organic bowel diseases
Fecal calprotectin can help predict organic bowel diseases Fecal calprotectin can help predict organic bowel diseases

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The risk of large bowel organic disease can be estimated via fecal calprotectin levels.

The use of fecal calprotectin (FC) can be a useful marker in predicting organic bowel diseases, a prospective observational study in the Journal of Gastroenterology and Hepatology suggested. Given the requirement for an objective evaluation to distinguish between organic gastrointestinal diseases and functional bowel symptoms, this study examined the diagnostic precision of FC to predict organic gastrointestinal diseases.

The stool samples of patients within 24 hours prior to colonoscopy were collected. A commercial kit was utilized for measuring FC. In the case of normal colonoscopy but raised FC, the upper endoscopy analysis was continued. Out of 429 people, 270 were reported to have FC above 50 μg/g. Out of these 270 patients, 86 had noteworthy colonoscopy pathological findings.

For diagnosing organic colonoscopy or upper endoscopy disease, the sensitivity was 91.7%, specificity was 55.6%, positive predictive value (PPV) was 57.0% and negative predictive value (NPV) was 91.2%. In the case of colon cancer, high-risk polyp, and inflammation, the NPV of FC were 98.7%, 96.2%, and 98.1%, correspondingly. The NPV of FC in case of changed bowel routines or abdominal pain in the prediction of colon cancer was 93.8% and inflammation was 100%.

Therefore, a negative FC test could be utilized as a screening tool to prioritize the requirement for future examination, especially in the setting of abdominal pain and changed bowel routines, Yee Man Kan et al. concluded.

Source:

Journal of Gastroenterology and Hepatology

Article:

Diagnostic accuracy of fecal calprotectin in predicting significant gastrointestinal diseases

Authors:

Yee Man Kan et al.

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