Research Center, Almoosa Specialist Hospital, Al-Ahsa, Saudi Arabia; College of Nursing, Princess Nora University, Riyadh, Saudi Arabia; School of Nursing, University of Wollongong, Australia.
Administration of Pharmaceutical Care, Al-ahsa Health Cluster, Ministry of Health, Al-ahsa, Saudi Arabia.
J Glob Antimicrob Resist. 2021 Jun;25:142-150. doi: 10.1016/j.jgar.2021.03.009. Epub 2021 Mar 21.
Awareness of antimicrobial resistance (AMR) patterns in a given healthcare setting is important to inform the selection of appropriate antimicrobial therapy to reduce the further rise and spread of AMR as well as the rate of healthcare-associated infections (HAIs) and multidrug-resistant (MDR) organisms. We aimed to describe resistance patterns to several antimicrobial agents in pathogens causing HAIs isolated from patients using data gathered at three private tertiary-care hospitals in Saudi Arabia.
Data on trends in AMR among bacteria causing HAIs and MDR events in children and adults at three private hospitals were collected retrospectively (2015-2019) using surveillance data.
Over the 5-year period, 29 393 pathogens caused 17 539 HAIs in 15 259 patients. Approximately 57.3% of patients were female and the mean age was 38.4 ± 16.8 years (81.4% adults, 18.6% children). Gram-negative pathogens were four times more likely to cause HAIs compared with Gram-positive bacteria (79.3% vs. 20.7%). Ranking of causative pathogens in decreasing order was Escherichia coli (42.2%), Klebsiella spp. (16.8%) and Staphylococcus aureus (13.9%). Acinetobacter spp. were the only pathogens to decrease significantly (7% reduction; P = 0.033). The most common resistant pathogens were extended-spectrum cephalosporin-resistant E. coli (37.1%), extended-spectrum cephalosporin-resistant Klebsiella (27.8%), carbapenem-non-susceptible Acinetobacter spp. (19.5%), carbapenem-non-susceptible Pseudomonas aeruginosa (19.2%) and methicillin-resistant S. aureus (18.6%).
National collaboration is required by prompt feedback to local authorities to tackle regional differences in AMR. This can help plan timely containment interventions to stop and contain microbial threats and swiftly assess their impact.
了解特定医疗环境中抗菌药物耐药（AMR）模式对于选择适当的抗菌治疗方案以减少 AMR 的进一步上升和传播以及降低医疗相关感染（HAI）和多药耐药（MDR）病原体的发生率至关重要。我们旨在描述从沙特阿拉伯三家私立三级保健医院的患者中分离出的导致 HAI 的病原体对几种抗菌药物的耐药模式。
使用监测数据回顾性收集了 2015 年至 2019 年期间，三家私立医院儿童和成人中导致 HAI 和 MDR 事件的细菌中 AMR 趋势的数据。
在 5 年期间，29393 种病原体在 15259 名患者中引起了 17539 例 HAI。约 57.3%的患者为女性，平均年龄为 38.4±16.8 岁（81.4%为成年人，18.6%为儿童）。与革兰阳性菌相比，革兰氏阴性病原体引起 HAI 的可能性高四倍（79.3%比 20.7%）。按降序排列，病原体依次为大肠埃希菌（42.2%）、克雷伯菌属（16.8%）和金黄色葡萄球菌（13.9%）。鲍曼不动杆菌是唯一显著减少的病原体（减少 7%；P=0.033）。最常见的耐药病原体是产超广谱头孢菌素的大肠埃希菌（37.1%）、产超广谱头孢菌素的克雷伯菌（27.8%）、耐碳青霉烯不动杆菌（19.5%）、耐碳青霉烯铜绿假单胞菌（19.2%）和耐甲氧西林的金黄色葡萄球菌（18.6%）。
需要国家间的合作，通过向当地当局提供及时反馈来解决 AMR 方面的地区差异。这有助于计划及时采取遏制干预措施，以阻止和控制微生物威胁，并迅速评估其影响。
