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Arch Dis Child ; 105(10): 957-963, 2020 10.
Article in English | MEDLINE | ID: mdl-32424002

ABSTRACT

OBJECTIVE: To determine the diagnostic accuracy of calprotectin to diagnose inflammatory bowel disease (IBD) in children in whom general practitioners (GPs) suspected IBD. DESIGN: Prospective observational cohort study of a new calprotectin-based primary care referral pathway. SETTING: 48 GP practices and gastroenterology secondary care services at the Royal Devon and Exeter NHS Foundation Trust in the South-West of England, UK. PATIENTS: 195 children aged between 4 and 18 years referred on the pathway between January 2014 and August 2017 for investigation of gastrointestinal symptoms were included. INTERVENTIONS: Primary-care-driven faecal calprotectin testing. Primary and secondary care records over 12 months from the point of calprotectin testing were used as the reference standard. MAIN OUTCOME MEASURES: Diagnostic accuracy of calprotectin testing to detect IBD. RESULTS: 7% (13/195) tested patients were diagnosed with IBD. Using our prespecified cut-off of 100 µg/g, calprotectin had a diagnostic accuracy of 91% (95% CI 86% to 95%) with a sensitivity for distinguishing IBD from non-IBD of 100% (95% CI 75% to 100%), a specificity of 91% (95% CI 85% to 94%), a positive predictive value of 43% (95% CI 25% to 63%) and a negative predictive value of 100% (95% CI 98% to 100%). Calprotectin testing had no effect on the time to diagnosis, but a negative test contributed to saved referrals and was associated with fewer diagnostic tests in secondary care. CONCLUSIONS: Calprotectin testing of children with suspected IBD in primary care accurately distinguishes IBD from a functional gut disorder, reduces secondary care referrals and associated diagnostic healthcare utilisation.


Subject(s)
Feces/chemistry , Inflammatory Bowel Diseases/diagnosis , Leukocyte L1 Antigen Complex/metabolism , Adolescent , Biomarkers/metabolism , Child , Child, Preschool , Cohort Studies , Female , Humans , Male , Predictive Value of Tests , Referral and Consultation/statistics & numerical data , Sensitivity and Specificity
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