Статья
Основные положенияВ обзоре впервые предложена интегративная концептуальная модель высокого периоперационного кардиального риска, объединяющая три ключевых блока: риск операции, уязвимость пациента и динамический контроль, что позволяет системно подойти к стратификации пациентов перед некардиальными операциями.Продемонстрирован критический разрыв между высокой прогностической точностью современных моделей машинного обучения (AUROC > 0,90) и отсутствием их клинической валидации в реальной практике, особенно в отечественной популяции, что определяет необходимость разработки национального калькулятора риска.Впервые в отечественной литературе детально проанализирована роль MINS (повреждения миокарда после некардиальных операций) как основного драйвера послеоперационной летальности (вклад 3,9% в общую летальность) и обоснован переход от реактивного к превентивному управлению периоперационным кардиальным риском на основе рутинного мониторинга высокочувствительных тропонинов и натрийуретических пептидов. РезюмеДанный обзор посвящен современным подходам к оценке и управлению периоперационным кардиальным риском у пациентов, переносящих некардиальные хирургические вмешательства. Актуальность темы обусловлена высокой частотой серьезных неблагоприятных сердечно-сосудистых событий (MACE), являющихся ведущей причиной периоперационной летальности. В работе проанализирована эволюция парадигмы от вопроса «можно ли оперировать?» к стратегии «как улучшить исход?», что включает предоперационную оптимизацию, активный мониторинг и мультидисциплинарный подход.На основе поиска литературы рассмотрены эпидемиология и ключевые факторы риска, детализированы классификации и определения осложнений (MACE, повреждение миокарда после некардиальных операций (MINS), интраоперационные критические инциденты). Особое внимание уделено роли биомаркеров (NT-proBNP/BNP для прогнозирования, высокочувствительный тропонин для диагностики MINS) и гемодинамического контроля в стратификации риска и раннем выявлении повреждения миокарда.Проведен сравнительный анализ прогностических инструментов: от традиционных клинических шкал (индекс Lee, NSQIP) до современных моделей машинного обучения, демонстрирующих высокую точность. Отмечены проблемы валидации, клинической интерпретируемости и интеграции этих инструментов в рутинную практику. Обобщены современные рекомендации по минимизации риска, основанные на поэтапной персонализированной оценке, оптимизации состояния пациента и активном послеоперационном наблюдении.Делается вывод о необходимости разработки интегративных, прозрачных и клинически применимых алгоритмов, сочетающих данные шкал, биомаркеров и динамического мониторинга для перехода от реактивного к превентивному управлению периоперационным кардиальным риском.
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