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新发传染病电子杂志 ›› 2025, Vol. 10 ›› Issue (5): 73-78.doi: 10.19871/j.cnki.xfcrbzz.2025.05.014

• 综述 • 上一篇    下一篇

多重耐药鲍曼不动杆菌肺炎的临床与影像学研究进展

王洁1,2, 范兵2   

  1. 1.南昌大学江西医学院,江西 南昌 330031;
    2.江西省人民医院/南昌医学院第一附属医院影像科,江西 南昌 330038
  • 收稿日期:2025-02-01 发布日期:2025-11-17
  • 通讯作者: 范兵, Email:26171381@qq.com
  • 基金资助:
    国家自然科学基金地区项目(82160335)

Advances in clinical and radiological studies of multidrug-resistant Acinetobacter baumannii pneumonia

Wang Jie1,2, Fan Bing2   

  1. 1. Jiangxi Medical College, Nanchang University, Jiangxi Nanchang 330031, China;
    2. Department of Radiology, Jiangxi Provincial People's Hospital/The First Affiliated Hospital of Nanchang Medical College, Jiangxi Nanchang 330038, China
  • Received:2025-02-01 Published:2025-11-17

摘要: 鲍曼不动杆菌(Acinetobacter baumannii,Ab)是一种机会性革兰氏阴性病原体,在自然环境与医疗环境中分布广泛,具备强大的生存与适应能力,是常见的院内感染致病菌。Ab有多种固有的耐药基因,加上近年来抗生素的滥用,多重耐药鲍曼不动杆菌(multidrug-resistant Acinetobacter baumannii,MDR-Ab)及碳青霉烯类耐药鲍曼不动杆菌(carbapenem-resistant Acinetobacter baumannii,CR-Ab)在全世界广泛流行,尤其是MDR-Ab已经成为人类健康面临的严重问题。MDR-Ab肺炎因临床治疗方案有限、预后差、病死率高,长期以来是全球医学界面临的棘手难题。在此临床困境下,早期准确诊断对于实现MDR-Ab肺炎患者的有效治疗与改善预后起着较重要作用。随着影像学技术的不断发展,其作为无创性诊断工具的临床价值日益凸显,可以及时显示MDR-Ab肺炎及肺外征象,在MDR-Ab肺炎的早期识别、病情评估和治疗效果监测中发挥着积极作用。人工智能技术在影像学分析中的应用也为早期诊断和预后评估提供了新思路。本文将围绕国内外MDR-Ab肺炎病原学、临床特征和影像学研究的最新进展综述,并探讨人工智能在其中的应用价值。

关键词: 肺炎, 鲍曼不动杆菌, 多重耐药, 计算机断层扫描, 医学影像学

Abstract: Acinetobacter baumannii (Ab) is an opportunistic Gram-negative pathogen that is widely distributed in both natural and medical environments. It has strong survival and adaptability capabilities and is a common pathogen causing nosocomial infections. This bacterium possesses multiple intrinsic drug-resistance genes, and coupled with the overuse of antibiotics in recent years, carbapenem-resistant Acinetobacter baumannii (CR-Ab) and multidrug-resistant Acinetobacter baumannii (MDR-Ab) have become widespread globally, with MDR-Ab posing a serious threat to human health. Due to the limited treatment options and poor prognosis of MDR-Ab pneumonia in clinical practice, along with its high mortality rate, it has long been a challenging issue for the global medical community. In this clinical predicament, early and accurate diagnosis plays a crucial role in the effective treatment and improved prognosis of MDR-Ab pneumonia. With the continuous development of imaging technology, imaging, as a non-invasive diagnostic method, can promptly detect can promptly detect MDR-Ab pneumonia and extrapulmonary manifestations, playing an irreplaceable role in the early identification, disease assessment, and treatment monitoring of MDR-Ab pneumonia. The application of artificial intelligence technology in imaging analysis also provides new approaches for early diagnosis and prognosis assessment. This paper reviews the latest progress in etiology, clinical characteristics, and imaging findings of MDR-Ab pneumonia at home and abroad, and discusses the application value of artificial intelligence in it.

Key words: Pneumonia, Acinetobacter baumannii, Multidrug-resistant, Computed tomography, Medical image

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