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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">uprinmatus</journal-id><journal-title-group><journal-title xml:lang="ru">Известия Юго-Западного государственного университета. Серия: Управление, вычислительная техника, информатика. Медицинское приборостроение</journal-title><trans-title-group xml:lang="en"><trans-title>Proceedings of the Southwest State University. Series: IT Management, Computer Science, Computer Engineering. Medical Equipment Engineering</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2223-1536</issn><publisher><publisher-name>Юго-Западный государственный университет</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.21869/2223-1536-2026-16-2-209-217</article-id><article-id custom-type="elpub" pub-id-type="custom">uprinmatus-491</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>МОДЕЛИРОВАНИЕ В МЕДИЦИНСКИХ И ТЕХНИЧЕСКИХ СИСТЕМАХ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>MODELING IN MEDICAL AND TECHNICAL SYSTEMS</subject></subj-group></article-categories><title-group><article-title>Прогностическое моделирование неблагоприятных исходов лечения травм коленного сустава у пациентов с сахарным диабетом</article-title><trans-title-group xml:lang="en"><trans-title>Prognostic modeling of adverse outcomes of knee joint injury treatment in patients with diabetes mellitus</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-4477-3975</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Родионова</surname><given-names>С. Н.</given-names></name><name name-style="western" xml:lang="en"><surname>Rodionova</surname><given-names>S. N.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Родионова Софья Николаевна, кандидат технических наук, доцент кафедры биомедицинской инженерии</p><p>Scopus ID: 57195455825</p><p>‘WOS ID: Q-1060-2017</p><p>ул. 50 лет Октября, д. 94, г. Курск 305040</p></bio><bio xml:lang="en"><p>Sofia N. Rodionova, Cand. Sci. (Engineering), Associate Professor at the Department of Biomedical Engineering</p><p>Scopus ID: 57195455825</p><p>WOS ID: Q-1060-2017</p></bio><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0008-7864-4566</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Тишин</surname><given-names>Я. Н.</given-names></name><name name-style="western" xml:lang="en"><surname>Tishin</surname><given-names>Ya. N.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Тишин Ярослав Николаевич, аспирант кафедры биомедицинской инженерии</p><p>ул. 50 лет Октября, д. 94, г. Курск 305040</p></bio><bio xml:lang="en"><p>Yaroslav N. Tishin, Postgraduate at the Department of Biomedical Engineering</p></bio><email xlink:type="simple">tisinaroslav5@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0008-5569-7390</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Бабкин</surname><given-names>А. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Babkin</surname><given-names>A. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Бабкин Андрей Андреевич, аспирант кафедры биомедицинской инженерии</p><p>ул. 50 лет Октября, д. 94, г. Курск 305040</p></bio><bio xml:lang="en"><p>Andrey A. Babkin, Postgraduate at the Department of Biomedical Engineering</p></bio><email xlink:type="simple">babosboxing@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff xml:lang="ru" id="aff-1"><institution>Юго-Западный государственный университет</institution><country>Russian Federation</country></aff><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>07</day><month>08</month><year>2026</year></pub-date><volume>16</volume><issue>2</issue><fpage>209</fpage><lpage>217</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Родионова С.Н., Тишин Я.Н., Бабкин А.А., 2026</copyright-statement><copyright-year>2026</copyright-year><copyright-holder xml:lang="ru">Родионова С.Н., Тишин Я.Н., Бабкин А.А.</copyright-holder><copyright-holder xml:lang="en">Rodionova S.N., Tishin Y.N., Babkin A.A.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://uprinmatus.elpub.ru/jour/article/view/491">https://uprinmatus.elpub.ru/jour/article/view/491</self-uri><abstract><sec><title>Цель исследования</title><p>Цель исследования. Выявление ключевых факторов риска и создание математической модели для прогнозирования результатов лечения травм коленного сустава у пациентов с сахарным диабетом — цели исследования.</p></sec><sec><title>Методы</title><p>Методы. Для решения поставленной задачи использован комплекс методов, позволяющих учитывать множество факторов, влияющих на риск травматизации колена у пациентов с сахарным диабетом. В их числе — дескриптивная статистика для характеристики выборки (среднее значение, стандартное отклонение, медиана, квартили), корреляционный анализ коэффициентов Спирмена и Пирсона для выявления взаимосвязей между переменными, а также логистическая регрессия и методы машинного обучения (Random Forest и SVM) для построения и оценки прогностических моделей. Такой подход обеспечивает глубокое изучение взаимосвязей между клиническими и функциональными показателями, что позволяет создать точные и надёжные прогностические модели. В результате это способствует улучшению оценки риска и разработки индивидуальных профилактических подходов, а также персонализированных методов терапии, что значительно повышает эффективность лечения.</p></sec><sec><title>Результаты</title><p>Результаты. Обнаружена корреляция между уровнем HbA1c и частотой инфекционных осложнений (г = 0,68, р &lt; 0,01). Разработана математическая модель, позволяющая прогнозировать неблагоприятный исход лечения с точностью до 89 % (AUC = 0,89). Прогностическая модель выявила ключевые факторы риска неблагоприятных исходов лечения, включая уровень HbATc, превышающий 7,5 %, ИМТ более 30 кг/m2 и возраст старше 60 лет.</p></sec><sec><title>Заключение</title><p>Заключение. В данной работе прогностическая модель работает с точностью 86 %, что является хорошим диагностическим показателем и инструментом оценки риска для решения важной задачи медицинского прогнозирования и профилактики осложнений.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Purpose of research</title><p>Purpose of research. The objectives of the study are to identify key risk factors and create a mathematical model for predicting treatment outcomes for knee injuries in patients with diabetes mellitus.</p></sec><sec><title>Methods</title><p>Methods. To solve this problem, a set of methods was used to take into account many factors affecting the risk of knee injury in patients with diabetes mellitus. These include descriptive statistics for sample characteristics (such as mean, standard deviation, median, quartiles), correlation analysis of Spearman and Pearson coefficients to identify relationships between variables, as well as logistic regression and machine learning methods (Random Forest and SVM) for building and evaluating predictive models. This approach provides an in-depth study of the relationships between clinical and functional indicators, which makes it possible to create accurate and reliable predictive models. As a result, this contributes to improved risk assessment and the development of individual preventive approaches, as well as personalized therapies, which significantly increases the effectiveness of treatment.</p></sec><sec><title>Results</title><p>Results. A correlation was found between the level of HbA1c and the frequency of infectious complications (r = 0,68, p &lt; 0,01). A mathematical model was developed that allows predicting an unfavorable treatment outcome with an accuracy of 89 % (AUC = 0,89). The prognostic model identified key risk factors for adverse treatment outcomes, including HbA1c levels exceeding 7,5 %, BMI over 30 kg/m2 and age over 60 years.</p></sec><sec><title>Conclusion</title><p>Conclusion. In this work the predictive model works with an accuracy of 86 %, which is a good diagnostic indicator and a risk assessment tool for solving the important task of medical forecasting and prevention of complications.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>сахарный диабет</kwd><kwd>травмы коленного сустава</kwd><kwd>факторы риска</kwd><kwd>прогностическое моделирование</kwd><kwd>машинное обучение</kwd><kwd>медицинские информационные системы</kwd></kwd-group><kwd-group xml:lang="en"><kwd>diabetes mellitus</kwd><kwd>knee injuries</kwd><kwd>risk factors</kwd><kwd>predictive modeling</kwd><kwd>machine learning</kwd><kwd>medical information systems</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Determining the Threshold for HbA1c as а Predictor for Adverse Outcomes After Тоtal Joint Arthroplasty: A Multicenter, Retrospective Study / M. Tarabichi, N. 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