Концепция инфекционного периоперационного риска (аналитический обзор)

Цель. Обосновать концепцию периоперационного инфекционного риска путем анализа современных подходов к классификации осложнений, методов их прогнозирования и ключевых факторов, влияющих на исход хирургического лечения. 
Материалы и методы. Выполнили аналитический обзор, основанный на экспертной оценке и систематическом поиске публикаций за предшествующие 10 лет в PubMed и Lens.org. В анализ включили данные по эпидемиологии инфекционных осложнений, классификационные системы (CDC, Clavien-Dindo, Accordion), прогностические шкалы (ASA, SOFA, ACS-NSQIP, SORT), лабораторные маркеры (СРБ, ИЛ-6, прокальцитонин, отношение нейтрофилов к лимфоцитам) и модели машинного обучения (PERISCOPE AI, Random Forest, SVM, ансамблевые методы). 
Результаты. Показали, что риск инфекционных осложнений определяется совокупным воздействием модифицируемых и немодифицируемых факторов, связанных как с пациентом, так и с медицинским учреждением. Лабораторные показатели демонстрировали высокую прогностическую ценность: ИЛ-6 более 432 пг/мл и CRP  150 мг/л на 3-и сутки были статистически значимо ассоциированы с неблагоприятными исходами. Современные прогностические инструменты обеспечили высокую точность: AUROC для ACS-NSQIP достигло 0,80, для PERISCOPE AI — 0,82–0,91. Использование шкал и машинного обучения позволило выявлять пациентов высокого риска до появления клинической симптоматики. 
Заключение. Периоперационный инфекционный риск формируется многофакторно и требует интегрированного подхода к стратификации, включающего клинические данные, шкалы риска, лабораторные маркеры и ИИ-модели. Применение структурированных прогностических инструментов способствует ранней идентификации осложнений, оптимизации профилактики и снижению летальности. 

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