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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">antibiotics</journal-id><journal-title-group><journal-title xml:lang="ru">Антибиотики и Химиотерапия</journal-title><trans-title-group xml:lang="en"><trans-title>Antibiot Khimioter = Antibiotics and Chemotherapy</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">0235-2990</issn><publisher><publisher-name>ООО «Издательство ОКИ»</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.37489/0235-2990-2025-70-11-12-5-13</article-id><article-id custom-type="edn" pub-id-type="custom">ZHYIUU</article-id><article-id custom-type="elpub" pub-id-type="custom">antibiotics-1303</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>ЭКСПЕРИМЕНТАЛЬНЫЕ ИССЛЕДОВАНИЯ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>EXPERIMENTAL STUDIES</subject></subj-group></article-categories><title-group><article-title>Оценка аналитической чувствительности и времени детекции роста микроорганизмов с применением автоматизированных систем для гемокультивирования — результаты сравнительного исследования</article-title><trans-title-group xml:lang="en"><trans-title>Assessment of Analytical Sensitivity and Detection Time of Microbial Growth Using Automated Blood Culture Systems — Results of the Comparative Study</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-1473-1982</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Попов</surname><given-names>Д. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Popov</surname><given-names>D. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Попов Дмитрий Александрович — д. м. н., профессор РАН, заведующий микробиологической (бактериологической) лабораторией ФГБУ «НМИЦ ССХ им. А.Н. Бакулева» Минздрава России.</p><p>Москва</p></bio><bio xml:lang="en"><p>Dmitry A. Popov — D. Sc. in Medicine, Professor of the Russian Academy of Sciences, Head of the Microbiological (Bacteriological) Laboratory, A. N. Bakulev National Medical Research Center for Cardiovascular Surgery of the Ministry of Health of the Russian Federation.</p><p>Moscow</p></bio><email xlink:type="simple">dapopov@bakulev.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0007-1513-2865</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Осокина</surname><given-names>Р. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Osokina</surname><given-names>R. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Осокина Регина Агзамовна — врач клинический фармаколог ФГБУ «НМИЦ ССХ им. А.Н. Бакулева» Минздрава России.</p><p>Москва</p></bio><bio xml:lang="en"><p>Regina A. Osokina — clinical pharmacologist, A. N. Bakulev National Medical Research Center for Cardiovascular Surgery of the Ministry of Health of the Russian Federation.</p><p>Moscow</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/0009-0000-1034-4577</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Вострикова</surname><given-names>Т. Ю.</given-names></name><name name-style="western" xml:lang="en"><surname>Vostrikova</surname><given-names>T. Yu.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Вострикова Татьяна Юрьевна — к. м. н., врач-бактериолог микробиологической (бактериологической) лаборатории ФГБУ «НМИЦ ССХ им. А.Н. Бакулева» Минздрава России.</p><p>Москва</p></bio><bio xml:lang="en"><p>Tatiana Yu. Vostrikova — Ph. D. in Medicine, clinical bacteriologist at the Microbiological (Bacteriological) Laboratory A.N. Bakulev National Medical Research Center for Cardiovascular Surgery of the Ministry of Health of the Russian Federation.</p><p>Moscow</p></bio><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ФГБУ Национальный медицинский исследовательский центр сердечно-сосудистой хирургии им. А.Н. Бакулева Министерства здравоохранения Российской Федерации</institution><country>Россия</country></aff><aff xml:lang="en"><institution>A.N. Bakulev National Medical Research Center for Cardiovascular Surgery of the Ministry of Health of the Russian Federation</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>04</day><month>03</month><year>2026</year></pub-date><volume>70</volume><issue>11-12</issue><fpage>5</fpage><lpage>13</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Попов Д.А., Осокина Р.А., Вострикова Т.Ю., 2026</copyright-statement><copyright-year>2026</copyright-year><copyright-holder xml:lang="ru">Попов Д.А., Осокина Р.А., Вострикова Т.Ю.</copyright-holder><copyright-holder xml:lang="en">Popov D.A., Osokina R.A., Vostrikova T.Y.</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.antibiotics-chemotherapy.ru/jour/article/view/1303">https://www.antibiotics-chemotherapy.ru/jour/article/view/1303</self-uri><abstract><p>Цель исследования. Сравнить аналитическую чувствительность и время детекции роста микроорганизмов при использовании анализаторов гемокультур BACT/ALERT 3D 120 (bioMérieux, Франция), ЮНОНА LABSTAR 100 (SCENKER Biological Technology Co., Ltd., Китай) и Autobio BC 120 (Autobio Diagnostics Co., Ltd, Китай). Материал и методы. Исследование проведено в два этапа: 1. In vitro: суспензии 10 клинических штаммов в концентрации, имитирующей бактериемию (30 КОЕ/мл, конечное разведение 1–2 КОЕ/флакон). 2). Клинический этап: 197 гемокультур от 89 кардиохирургических пациентов с параллельным использованием только систем BACT/ALERT 3D 120 и ЮНОНА LAB- STAR 100. На обоих этапах образцы инокулировали в пары аэробных и анаэробных флаконов, оценивая наличие роста и время его детекции. Результаты. На этапе in vitro суммарная чувствительность составила 80,5, 77,5 и 74,5% для систем ЮНОНА LABSTAR 100, BACT/ALERT 3D 120 и Autobio BC 120 соответственно. При аэробном культивировании грамотрицательных бактерий выявляемость была высокой во всех системах (90–100%). В анаэробных условиях максимальную чувствительность для этой группы показала система ЮНОНА LABSTAR 100 (72,5%), минимальную — Autobio BC 120 (45%). Профили эффективности систем различались: преимущество Autobio BC 120 в скорости детекции энтеробактерий в аэробных условиях (медиана 11,5 ч против 13–13,9 ч у других) сочеталось с более низкой чувствительностью анаэробных флаконов к грамположительным бактериям (77,5 против 100% у систем BACT/ALERT 3D 120 и ЮНОНА LABSTAR 100). Примечательным результатом стал рост P. aeruginosa во всех анаэробных флаконах системы ЮНОНА LABSTAR 100. Для грибов рода Candida все системы показали более низкую чувствительность и большее время детекции (медианы 30,1–33,6 ч в аэробных условиях) по сравнению с бактериями. На клиническом этапе рост был подтверждён в 19 случаях (9,6%). В аэробных условиях обе системы выявили рост в 73,7% флаконов. В анаэробных флаконах (исключая облигатные аэробы) рост детектировался системой BACT/ALERT 3D 120 в 75% случаев, что чаще, чем системой ЮНОНА LABSTAR 100 (56,3%). Суммарная чувствительность при выявлении эпизода бактериемии составила 89,5% (17/19) для BACT/ALERT 3D 120 против 73,7% (14/19) для ЮНОНА LABSTAR 100, что соответствует выявлению системой BACT/ALERT 3D 120 на 3 случая бактериемии больше. Анализ по группам возбудителей показал, что для энтеробактерий и грамположительных кокков чувствительность системы BACT/ALERT 3D 120 была выше. Полное совпадение идентификации в обеих системах отмечено лишь в 47,4% проб, а общий уровень расхождений достиг 52,6%. Вывод. Диагностическая эффективность сравниваемых систем вариабельна и зависит от вида микроорганизма и условий культивирования. Превосходство по отдельным параметрам in vitro (например, скорость) не гарантирует аналогичного результата в клинической практике, где ключевым является стабильная чувствительность при выявлении эпизода бактериемии. Высокий процент расхождений между современными системами подтверждает обоснованность рекомендаций по взятию нескольких проб для повышения выявляемости гемокультур.</p></abstract><trans-abstract xml:lang="en"><p>The aim of the study was to compare the analytical sensitivity and microbial growth detection time using the BACT/ALERT 3D 120 (bioMérieux, France), YUNONА LABSTAR 100 (SCENKER, China), and Autobio BC 120 (Autobio, China) blood culture analyzers. Material and methods. The study was conducted in two stages. 1) In vitro: suspensions of 10 clinical strains at concentrations simulating bacteremia (30 CFU/ml, final dilution 1–2 CFU/vial). 2) Clinical phase: 197 blood cultures from 89 cardiothoracic surgery patients, tested in parallel using only the BACT/ALERT 3D 120 and YUNONA LABSTAR 100 systems. At both stages, samples were inoculated into pairs of aerobic and anaerobic vials, and the presence of growth and its detection time were assessed. Results. In the in vitro phase, the total sensitivity was 80.5%, 77.5%, and 74.5% for the YUNONA LABSTAR 100, BACT/ALERT 3D 120, and Autobio BC 120 systems, respectively. During aerobic cultivation of gram-negative bacteria, detection rates were high in all systems (90–100%). Under anaerobic conditions, the YUNONA LABSTAR 100 system showed the maximum sensitivity for this group (72.5%), while the Autobio BC 120 system showed the minimum sensitivity (45%). The eﬃcacy profiles differed: the advantage of the Autobio BC 120 system in the detection speed of enterobacteria under aerobic conditions (median 11.5 h vs. 13–13.9 h for others) was combined with its lower sensitivity of anaerobic vials for gram-positive bacteria (77.5% vs. 100% for the BACT/ALERT 3D 120 and YUNONA LABSTAR 100 systems). A notable finding was the growth of P. aeruginosa in all anaerobic vials of the YUNONA LABSTAR 100 system. For Candida spp., all systems showed lower sensitivity and longer detection times compared to bacteria. In the clinical phase, growth was confirmed in 19 cases (9.6%). Under aerobic conditions, both systems detected growth in 73.7% of vials. In anaerobic vials (excluding obligate aerobes), growth was detected by the BACT/ALERT 3D 120 system in 75% of cases, which was more frequent than with the YUNONA LABSTAR 100 system (56.3%). The overall sensitivity for detecting a bacteremia episode was 89.5% (17/19) for the BACT/ALERT 3D 120 system versus 73.7% (14/19) for the YUNONA LABSTAR 100 system, meaning the BACT/ALERT 3D 120 system detected 3 more bacteremia cases. The analysis by pathogen groups showed that for enterobacteria and gram-positive cocci, the sensitivity of the BACT/ALERT 3D 120 system was higher. Complete agreement in identification between both systems was observed in only 47.4% of samples, with the overall discrepancy rate reaching 52.6%. Conclusion. The diagnostic eﬃcacy of the compared systems is variable and depends on the type of microorganism and cultivation conditions. Superiority in individual in vitro parameters (e.g., speed) does not guarantee a similar result in clinical practice, where stable sensitivity in detecting a bacteremia episode is key. The high percentage of discrepancies between modern systems confirms the validity of recommendations for collecting multiple samples to improve bacteremia detection.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>гемокультивирование</kwd><kwd>бактериемия</kwd><kwd>фунгемия</kwd><kwd>автоматизированные системы гемокультивирования</kwd><kwd>время детекции роста микроорганизмов</kwd></kwd-group><kwd-group xml:lang="en"><kwd>blood culture</kwd><kwd>bacteremia</kwd><kwd>fungemia</kwd><kwd>automated blood culture systems</kwd><kwd>microbial growth detection time</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">Bhavani S. V., Lonjers Z., Carey K. A., Afshar M., Gilbert E. R., Shah N. S., Huang E. S., Churpek M. M. The development and validation of a machine learning model to predict bacteremia and fungemia in hospitalized patients using electronic health record data. 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