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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">inovmed</journal-id><journal-title-group><journal-title xml:lang="ru">Инновационная медицина Кубани</journal-title><trans-title-group xml:lang="en"><trans-title>Innovative Medicine of Kuban</trans-title></trans-title-group></journal-title-group><issn pub-type="epub">2541-9897</issn><publisher><publisher-name>Scientific Research Institute – Ochapovsky Regional Clinical Hospital No. 1</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.35401/2541-9897-2024-9-4-68-76</article-id><article-id custom-type="elpub" pub-id-type="custom">inovmed-989</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>ОРИГИНАЛЬНЫЕ СТАТЬИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ORIGINAL ARTICLES</subject></subj-group></article-categories><title-group><article-title>Анализ прогностических факторов летальности у пациентов с желудочно-кишечными кровотечениями: применение методов машинного обучения</article-title><trans-title-group xml:lang="en"><trans-title>Analysis of Prognostic Factors for Mortality in Patients With Gastrointestinal Bleeding: Application of Machine Learning Tools</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0008-3042-3019</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Исмати</surname><given-names>А. О.</given-names></name><name name-style="western" xml:lang="en"><surname>Ismati</surname><given-names>A. O.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Исмати Амир Олимович - базовый докторант, ассистент кафедры хирургических заболеваний.</p><p>Самарканд</p></bio><bio xml:lang="en"><p>Amir O. Ismati - Basic Doctoral Student, Assistant Professor at the Department of Surgical Diseases, Samarkand State Medical University.</p><p>Samarkand</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/0000-0002-8486-7159</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Аносов</surname><given-names>В. Д.</given-names></name><name name-style="western" xml:lang="en"><surname>Anosov</surname><given-names>V. D.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Аносов Виктор Давидович - к. м. н., заместитель главного врача по хирургической помощи.</p><p>Москва</p></bio><bio xml:lang="en"><p>Viktor D. Anosov - Cand. Sci. (Med.), Deputy Chief Physician for Surgical Care, O.M. Filatov City Clinical Hospital No. 15.</p><p>Moscow</p></bio><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-4409-4315</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Мамараджабов</surname><given-names>С. Э.</given-names></name><name name-style="western" xml:lang="en"><surname>Mamarajabov</surname><given-names>S. E.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Мамараджабов Собиржон Эргашевич - д. м. н., декан факультета международного образования, заведующий кафедрой хирургических заболеваний, педиатрический факультет.</p><p>140100, Самарканд, ул. Амира Темура, 18</p></bio><bio xml:lang="en"><p>Sobirjon E. Mamarajabov - Dr. Sci. (Med.), Dean of the Faculty of International Education, Head of the Department of Surgical Diseases, Samarkand State Medical University.</p><p>Amir Temur ko’chasi, 18, Samarkand, 140100</p></bio><email xlink:type="simple">sobirjon_mamarajabov@mail.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Самаркандский государственный медицинский университет</institution><country>Узбекистан</country></aff><aff xml:lang="en"><institution>Samarkand State Medical University</institution><country>Uzbekistan</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>Городская клиническая больница № 15 им. О.М. Филатова</institution><country>Россия</country></aff><aff xml:lang="en"><institution>O.M. Filatov City Clinical Hospital No. 15</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2024</year></pub-date><pub-date pub-type="epub"><day>30</day><month>12</month><year>2024</year></pub-date><volume>0</volume><issue>4</issue><fpage>68</fpage><lpage>76</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Исмати А.О., Аносов В.Д., Мамараджабов С.Э., 2024</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="ru">Исмати А.О., Аносов В.Д., Мамараджабов С.Э.</copyright-holder><copyright-holder xml:lang="en">Ismati A.O., Anosov V.D., Mamarajabov S.E.</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://www.innovmedkub.ru/jour/article/view/989">https://www.innovmedkub.ru/jour/article/view/989</self-uri><abstract><sec><title>Введение</title><p>Введение: Лечение пациентов с желудочно-кишечными кровотечениями из верхних отделов желудочно-кишечного тракта является непростой задачей ввиду широкого спектра причин, вызвавших данное состояние, а также факторов, способных оказывать влияние на исходы госпитализации.</p></sec><sec><title>Цель</title><p>Цель: Исследование степени влияния факторов на 30-дневные исходы стационарного лечения с использованием методов машинного обучения.</p></sec><sec><title>Материалы и методы</title><p>Материалы и методы: Был собран ретроспективный набор данных у 101 пациента, включающий клинико-анамнестические, лабораторные, инструментальные показатели. В последующем база данных была разделена по этиологии желудочно-кишечных кровотечений на две группы: язвенные, варикозные. Полученные выборки были обработаны с помощью инструментов машинного обучения в два этапа: импутация при помощи модели MICE (multiple imputation by chained equations), анализ важности факторов при помощи модели Random Forest.</p></sec><sec><title>Результаты</title><p>Результаты: Согласно выполненному исследованию среди наиболее прогностически ценных показателей, вне зависимости от типа кровотечения, были не только хорошо известные предикторы летальности, а также факторы, подающие надежды на роль предикторов в научном сообществе: уровень креатинина, артериальное давление, АЧТВ, уровень сознания, показатели мочевины, лактата, а также коморбидности, уровни прокальцитонина, ферритина, общего белка крови.</p></sec><sec><title>Заключение</title><p>Заключение: Применение прогрессивных методов статистического анализа подтвердило значимость популярных и проверенных предикторов летальности, внесло вклад в развитие не только исследуемых научным сообществом в последние времена новых предикторов, но и еще неисследованных.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Introduction</title><p>Introduction: Treatment of upper gastrointestinal bleeding (UGIB) is a complex challenge due to the wide range of causes and factors affecting hospitalization outcomes.</p></sec><sec><title>Objective</title><p>Objective: To study the impact of various factors on 30-day hospital outcomes using machine learning (ML) tools.</p></sec><sec><title>Materials and methods</title><p>Materials and methods: We compiled a retrospective data set that includes clinical, laboratory, and imaging data of 101 patients. The database was divided into 2 groups by UGIB etiology: ulcer and variceal bleedings. Both etiological groups were processed using ML tools in 2 steps: imputation by the MICE (multiple imputation by chained equations) model and factor importance analysis using the Random Forest model.</p></sec><sec><title>Results</title><p>Results: Analysis revealed that the most prognostically valuable parameters in both groups were well-known mortality predictors and emerging predictive factors, such as creatinine, blood pressure, activated partial thromboplastin time, level of consciousness, urea, lactate, comorbidity status, procalcitonin, ferritin, and total protein.</p></sec><sec><title>Conclusions</title><p>Conclusions: The application of advanced tools confirmed the significance of popular and validated mortality predictors and contributed to the development of predictors, both explored and unexplored ones.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>желудочно-кишечное кровотечение</kwd><kwd>исходы</kwd><kwd>предиктор</kwd><kwd>летальность</kwd><kwd>прогностически значимый</kwd></kwd-group><kwd-group xml:lang="en"><kwd>gastrointestinal bleeding</kwd><kwd>outcomes</kwd><kwd>predictor</kwd><kwd>mortality</kwd><kwd>prognostic significance</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">Kamboj AK, Hoversten P, Leggett CL. 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