АЛГОРИТМ РАННЕЙ ДИАГНОСТИКИ И ПРОГНОЗИРОВАНИЯ МОЧЕКАМЕННОЙ БОЛЕЗНИ У ДЕТЕЙ С УЧЁТОМ ФАКТОРОВ РИСКА И ИММУНОГЕНЕТИЧЕСКОЙ ПРЕДРАСПОЛОЖЕННОСТИ В АМБУЛАТОРНО-ПОЛИКЛИНИЧЕСКИХ УСЛОВИЯХ

Abstract

Objective: To optimize the algorithm for early diagnosis of urolithiasis (UL) in children, considering risk factors, clinical and functional characteristics of the disease, and immunogenetic predisposition in an outpatient setting Methods: The literature on managing children with UL outside the hospital was thoroughly analyzed to achieve the goal. Medical records, risk factors, including immunogenetic predisposition, and clinical and laboratory investigation results of 652 hospitalized children with UL were studied. Additionally, a retrospective study of 379 outpatient records (the control group) and a prospective study of 1275 children (the study group) aged 1 to 18 was conducted. Based on the outpatient records analysis, the effectiveness of current and optimized management algorithms for children with UL was compared Results: As a result of the research, an algorithm for early diagnosis and prediction of UL in children, considering risk factors, including immunogenetic predisposition, was developed. The algorithm evaluates the risk of developing UL based on a thirteen-point checklist that assesses benefits and risks to provide a personalized risk score for each child. Based on this risk score, additional therapeutic interventions are determined for each patient Conclusion: The algorithm developed for early diagnosis and prediction of UL in children helps identify the condition at a preclinical stage in an outpatient setting. This algorithm categorizes patients into low-, moderate-, or high-risk groups and guides their management accordingly Keywords: Urolithiasis in children, early diagnosis, risk factors, prediction of urolithiasis, genetic factors, prelithiasis, outpatient service.