Diagnostic Algorithm for Pancreatic Pathology in Сhildren with Allergic Diseases

• Main Author: I.V. Karpushenko
• Format: Article
• Language: English
• Published: Publishing House Zaslavsky 2016-08-01
• Series: Zdorovʹe Rebenka
• Subjects: pancreas; food sensitization; diagnosis
• Online Access: http://childshealth.zaslavsky.com.ua/article/view/78954
• ISSN: 2224-0551; 2307-1168

Introduction. An increase in the incidence of allergic diseases worldwide, their direct relationship with the defeat of the digestive organs with the formation of functional disorders and inflammatory processes, their earlier manifestation determine the relevance and necessity of studying early diagnosis of these diseases in children. Objective. Improving the quality of the diagnosis of pancreatic pathology in children with allergic diseases. Materials and methods. The study involved 169 children aged 3 to 17 years, the main group consisted of 105 children with allergic diseases, control one — of 64 children. Verification of allergy: skin tests, specific immunoglobulins and total immunoglobulin E. Examination of the pancreas: determining the levels of α-amylase, trypsin, blood lipase, extended coprotest, postprandial hyperemia during ultrasound study. Diagnostic algorithm has been created using heterogeneous consistent procedures by Wald-Genkin. Results. We have determined the diagnostic coefficient, according to which pancreatic pathology is confirmed: by postprandial hyperemia 5–15 %, inhomogenous ultrasound structure of the pancreas with increased or decreased echogenicity; constipation or stool with signs of amylorrhea and iodofilic flora; in the early medical history — exudative-catarrhal anomaly constitution; complaints of moderate pain after a meal or not-related to it, with localization around the umbilicus or in the right upper quadrant; dyspeptic syndrome; moderate palpable pain sensitivity in the epigastrium, in the projection of the pancreas and along the colon; the presence of skin and the absence of respiratory allergy manifestations; pre-school age; elevated levels of trypsin and blood amylase; family history of digestive diseases; asthenovegetative syndrome; pathology of the pregnancy and labor, poor nutrition, concomitant somatic pathology; female gender, normal levels of total immunoglobulin E. Conclusions. The algorithm enables to diagnose pancreatic pathology with 95% probability, to approach the therapy differentially, to create risk group and to prevent the development of chronic process.