医学
社区获得性肺炎
队列
肺炎
重症监护医学
队列研究
舒巴坦钠
内科学
慢性阻塞性肺病
抗生素
抗生素耐药性
微生物学
亚胺培南
生物
作者
Natsuki Nakagawa,Masahiro Katsurada,Y Fukuda,Shingo Noguchi,Nobuyuki Horita,Makoto Miki,Hiroki Tsukada,Kazuyoshi Senda,Yuichiro Shindo,Hiroshi Mukae
标识
DOI:10.1183/16000617.0183-2024
摘要
Introduction Community-acquired pneumonia (CAP) is a leading cause of death worldwide. Reducing inappropriate and excessive use of extended-spectrum antibiotics is essential for treating CAP effectively. Evaluating the risk of drug-resistant pathogens (DRPs) is crucial for determining initial antibiotic therapy in clinical settings. Methods This systematic review and meta-analysis assessed the risk factors for DRPs in patients with CAP. CAP-DRPs were defined as pathogens resistant to commonly used antibiotics for CAP, including nonpseudomonal β-lactams such as ceftriaxone or sulbactam-ampicillin, macrolides and respiratory fluoroquinolones. The studies included were divided into two cohorts, namely an all-patient cohort, comprising both culture-positive and culture-negative patients, and a culture-positive pneumonia cohort, comprising patients with identified causative pathogens. The primary objective of this study was to evaluate the risk factors for CAP-DRPs in the all-patient cohort. Results 24 articles were included with 11 categorised into the all-patient cohort. The meta-analysis identified 11 significant risk factors for CAP-DRPs, namely prior DRP infection/colonisation, tracheostomy, severe respiratory failure requiring early induction of mechanical ventilation, prior use of antibiotics, chronic lung disease, COPD, wound care, neurological disorders, prior hospitalisation, nursing home residence and low activities of daily living. Conclusion To our knowledge, this is the first systematic review focused on CAP-DRP. Unlike previous reviews, the all-patient and culture-positive pneumonia cohorts were analysed separately. Findings from the all-patient cohort are particularly relevant for guiding initial antimicrobial selection in clinical practice. Furthermore, the abovementioned factors should be considered when developing prediction models for CAP-DRPs.
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