Компьютерная система для дифференциальной диагностики лизосомных болезней накопления на основе методов искусственного интеллекта

Aim. To improve the efficiency of diagnosis of hereditary lysosomal storage diseases using an intelligent computerbased decision support system.Materials and methods. Descriptions of 35 clinical cases from the literature and depersonalized data of 52 patients from electronic health records were used as material for clinical testing of the computer diagnostic system. Knowledge engineering techniques have been used to extract, structure, and formalize knowledge from texts and experts. Literary sources included online databases and publications (in Russian and English). On this basis, for each clinical form of lysosomal diseases, textological cards were created, the information in which was corrected by experts. Then matrices were formed, including certainty factors (coefficients) for the manifestation, severity, and relevance of signs for each age group (up to 1 year, from 1 to 3 years inclusive, from 4 to 6 years inclusive, 7 years and older). The knowledge base of the expert system was implemented on the ontology network and included a disease model with reference variants of clinical forms. Decision making was carried out using production rules.Results. The expert computer system was developed to support clinical decision-making at the pre-laboratory stage of differential diagnosis of lysosomal storage diseases. The result of its operation was a ranked list of hypotheses, reflecting the degree of their compliance with reference descriptions of clinical disease forms in the knowledge base. Clinical testing was carried out on cases from literary sources and patient data from electronic health records. The criterion for assessing the effectiveness of disease recognition was inclusion of the verified diagnosis in the list of five hypotheses generated by the system. Based on the testing results, the accuracy was 87.4%.Conclusion. The expert system for the diagnosis of hereditary diseases has shown fairly high efficiency at the stage of compiling a differential diagnosis list at the pre-laboratory stage, which allows us to speak about the possibility of its use in clinical practice.Цель – повышение эффективности диагностики наследственных лизосомных болезней накопления с использованием интеллектуальной компьютерной системы поддержки принятий решений.Материалы и методы. В качестве материала для клинической апробации компьютерной диагностической системы использованы описания 35 клинических случаев из литературы и данные 52 пациентов из электронных медицинских карт (в деперсонифицированном виде). Методы инженерии знаний использовались для извлечения, структуризации и формализации знаний из текстов и у экспертов. Литературные источники включали онлайн-базы данных и публикации (русско- и англоязычные). На этой основе для каждой клинической формы лизосомных болезней были сформированы текстологические карты, информация которых корректировалась экспертами. Затем формировались матрицы, включающие факторы уверенности (коэффициенты) для манифестации, выраженности и релевантности признаков по каждой из возрастных групп (до 1 года, от 1 года до 3 лет включительно, от 4 до 6 лет включительно, 7 лет и старше). База знаний экспертной системы реализована на онтологической сети и включает модель заболевания с эталонными вариантами клинических форм. Принятие решений осуществляется с использованием продукционных правил.Результаты. Разработана экспертная компьютерная система поддержки принятия клинических решений на долабораторном этапе дифференциальной диагностики лизосомных болезней накопления. Результатом ее работы является ранжированный перечень диагностических гипотез, отражающий степень их соответствия эталонным описаниям клинических форм болезней в базе знаний. Проведена апробация системы на случаях из литературных источников и на данных пациентов из электронных медицинских карт. Критерием для оценки эффективности распознавания болезни было вхождение верифицированного диагноза в перечень из пяти гипотез, выдаваемых системой. По итогам проведенной апробации точность составила 87,4%.Заключение. Экспертная система для диагностики наследственных болезней показала достаточно высокую эффективность на этапе формирования дифференциально-диагностического ряда на долабораторном этапе, что позволяет говорить о возможности ее использования в клинической практике

Prevalence and time trends of neural tube defects in regions of the Russian Federation

Neural tube defects – a group of severe congenital malformations with a high level of mortality, childhood disability. The average prevalence of these defects is approximately 1 per 1000 births. The main measures to reduce the prevalence of neural tube defects are primary and secondary prevention measures, the effectiveness of which can be determined by congenital malformations monitoring.Research purpose. To determine the prevalence of neural tube defects, as well as trends in their prevalence for 2011 to 2017 in the Russian Federation according to monitoring of congenital malformations.Results. The total prevalence of anencephaly among newborns and fetuses was 4.63 (95% confidence interval - CI 4.40–4.88) per 10000 births, spina bifida – 6.18 (95% CI 5.91–6.46) and encephalocele 1.34 (95% CI 1.21–1.47). At the same time, the prevalence of anencephaly only among live births was 0.11 (95% CI 0.08–0.15) per 10000, spina bifida – 2.24 (95% CI 2.08–2.41) and encephalocele – 0 25 (95% CI 0.20–0.31). The decrease in prevalence of birth defects among live births compared with the total prevalence is provided by a high level of detection of these defects by ultrasound examination during pregnancy with the subsequent elimination of the affected fetuses. The maximum proportion of eliminated fetuses is observed for anencephaly (90.5%), for encephalocele the proportion of aborted fetuses is 77.4% and for spina bifida – 59.3%. Over the 7-year period, the multidirectional prevalence trends were noted: the increasing trend for total prevalence of neural tube defects and the decreasing trend for prevalence of these defects among live-born children.Conclusion. Estimates of the prevalence of neural tube defects in Russian Federation regions are obtained. The dynamics of the studied defects prevalence indicates that the decreasing of neural tube defects prevalence among live births is associated with secondary prevention measures

Mother’s age as a risk factor of birth defects

Objective. To analyze the age structure of the mothers of children with birth defects and to assess the age-related risks of chromosomal and non-chromosomal congenital anomalies.Material and methods. The authors analyzed the data from 23 regional registers of birth defects from 2011 to 2018. There were total 5 047 468 births during this period. The authors calculated the incidence and relative risks of chromosomal and non-chromosomal birth defects in different age groups of mothers: under 20, from 20 to 34, from 35 to 39, 40–44, and above 45 years old.Results. The incidence of chromosomal abnormalities significantly increases with the mother’s age. The relative risk (RR) of chromosomal abnormalities in different age groups: 4,67 (95% CI 4,44–4,92) in Group 35-39, 15,00 (95% CI 14,10–15,96) in Group 40–44, and 26,49 (95% CI 21,89–32,07) in Group ≥45 as compared with the main age group of 20–34 years old. The authors also revealed the dependence of the non-chromosomal birth defects on the age of the mother: RR 1,15 (95% CI 1,08–1,23) in Group <20 years, RR 1,18 (95% CI 1,13–1,23) in Group 35–39, RR 1,35 (95% CI 1,24–1,47) in Group 40–44, and RR 2,03 (95% CI 1,47–2,79) in Group ≥ 45 years old.Conclusion. The study demonstrates the dependence of chromosomal and non-chromosomal birth defects on the mother’s age

The value of genetic analysis in the study of the nature of congenital malformations

Congenital malformations are the main cause of infant and child morbidity and mortality worldwide. Most congenital malformations are represented by non-syndromic forms, their etiology has not yet been studied. However, the latest genetic technologies have opened up new possibilities in the study of congenital malformations. The article presents latest achievements in the genetics of non-syndromic forms of congenital malformations. Genome-wide association study (GWAS) is an effective method for identifying gene variants associated with a predisposition to the congenital malformations; this method helps to identify correlations between single nucleotide polymorphism (SNP) and certain malformations. Numerous studies demonstrate that in addition to SNP the copy number variations (CNV) play an important role in the etiology of some birth defects (for example, congenital heart defects). It has been established that 5—10% of isolated congenital heart defects can be associated with rare CNV. Next-generation sequencing (NGS) is expected to play important role in the identification of birth defect etiology. The authors have obtained the first data on the genes involved in the development of malformations such as congenital heart defects, neural tube defects, facial clefts

Trends in the incidence of congenital malformations in the Russian Federation (according to the 2006—2012 Congenital Malformations Monitoring Base data)

The paper presents the results of analyzing the data of congenital malformation monitoring in 31 regions of the Russian Federation during 2006—2012. The analysis of the common database has yielded rates of all malformation cases notified in their departments, as well as those of a group of selective defects (21 identified forms), allowing for comparing inter- and intraregional comparisons. The rate of all registered malformations was 23.04 per 1000 births. The variations in the overall rate of malformations in the period under study are not statistically significant. The estimates for the rates of individual malformation forms in the Russian registry are given in comparison with the EUROCAT data

WEB APPLICATION «CONGENITAL MALFORMATIONS» TO IMPROVE THE LEVEL OF DOCTORS’ KNOWLEDGE AND TRAINING OF STUDENTS

The article describes the electronic educational resources – multimedia training system for congenital malformations and developmental anomalies. The work objective is an integrated approach to self-training and testing that combines the traditional principle of the control of knowledge and graphic tests with animation elements that provides high-quality remote to increase knowledge. We describe the structure of the system, screenshots, as well as Web-technology used for its development. The functionality of the system and the experience of Internet-based applications to improve the skills of doctors and students are given training. Criterion for assessing the level of knowledge of students on the basis of test results, taking into account the complexity of tests offered have been proposed. Evaluating the effectiveness of the use of distance training system allows us to conclude that multimedia training system «Congenital malformations» can be successfully applied for remote medical information support medical genetic counselors and physicians of different specialties involved in diagnosing congenital malformations in children and for training students – future doctors

First report of microcephaly-capillary malformations syndrome in Russia

Background: Microcephaly-capillary malformation (MIC-CAP) syndrome is a newly described autosomal recessive syndrome characterized by microcephaly, multiple cutaneous capillary malformations, intractable epilepsy and profound developmental delay. We present the first description of MIC-CAP syndrome in Russia. Patient: We describe a 6-month-old girl with severe congenital microcephaly, intractable epilepsy (infantile spasms), multiple cutaneous capillary malformations and facial abnormalities. Genetic studies revealed the presence of new STAMPB gene mutations in the compound heterozygous state: c.273delA and the intron replacement c.204-5 C > G. Conclusions: This report presents a case of MIC-CAP syndrome with earlier unreported new mutations of the STAMPB gene. Keywords: Microcephaly, Capillary malformations, Epilepsy, Deep developmental delay, STAMBP gen