Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis.
Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis.
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DOI：
10.1016/s0140-6736(21)02724-0
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发表时间：
2022-02-12
期刊：
影响因子：
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通讯作者：
Antimicrobial Resistance Collaborators
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文献类型：
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作者：
Antimicrobial Resistance Collaborators
抗生素耐药性（AMR）对全球人类健康构成重大威胁。先前的出版物估计了AMR对选定地区特定病原体-药物组合的发病率、死亡率、住院时间和医疗保健成本的影响。据我们所知，本研究提供了迄今为止最全面的AMR负担估计值。我们估计了2019年204个国家和地区的23种病原体和88种病原体-药物组合的细菌AMR所致和相关的死亡和残疾调整生命年（DIMs）。我们从系统性文献综述、医院系统、监测系统和其他来源获得数据，涵盖4.71亿个个体记录或分离株和7585个研究地点年。我们使用预测性统计建模来估计所有地点的AMR负担，包括没有数据的地点。我们的方法可分为五个主要部分：感染起作用的死亡人数、归因于特定感染综合征的感染性死亡比例、归因于特定病原体的感染综合征死亡比例、特定病原体对感兴趣的抗生素耐药的百分比以及与该耐药相关的死亡或感染持续时间的过度风险。使用这些组成部分，我们基于两个反事实估计了疾病负担：归因于AMR的死亡（基于所有耐药感染被药物敏感感染替代的替代方案），以及与AMR相关的死亡（基于所有耐药感染被无感染替代的替代方案）。我们为最终估计值生成了95%的不确定性区间（UI），作为1000次后验抽取的第25和第975个有序值，并对模型进行了样本外预测有效性的交叉验证。我们提出了全球和区域层面的最终估计数。根据我们的预测统计模型，2019年估计有495万（3.62 - 6.57）例死亡与细菌AMR相关，其中127万（95%UI 0.911 - 1.71）例死亡可归因于细菌AMR。在区域水平上，我们估计撒哈拉以南非洲西部的耐药性导致的所有年龄段死亡率最高，为每10万人27.3例死亡（20.9 - 35.3），澳大拉西亚最低，为每10万人6.5例死亡（4.3 - 9.4）。2019年，下呼吸道感染导致超过150万人死亡，与耐药性有关，使其成为负担最重的传染性综合征。2019年，与耐药相关的六种主要死亡病原体（大肠埃希菌，其次是金黄色葡萄球菌、肺炎克雷伯菌、肺炎链球菌、鲍曼不动杆菌和铜绿假单胞菌）导致92.9万（66.0 - 127.0万）例AMR死亡和357万（2.62 - 4.78）例AMR相关死亡。一种病原体-药物组合，耐甲氧西林金黄色葡萄球菌，在2019年导致超过10万例AMR死亡，而另外六种分别导致5万至10万例死亡：多重耐药，不包括广泛耐药结核病、第三代头孢菌素耐药大肠埃希菌、碳青霉烯类耐药鲍曼不动杆菌、氟喹诺酮类耐药大肠埃希菌、碳青霉烯类耐药肺炎克雷伯菌，和第三代头孢菌素耐药肺炎克雷伯菌。据我们所知，这项研究首次全面评估了AMR的全球负担，并对数据的可用性进行了评估。抗生素耐药性是世界各地的主要死因，在资源匮乏的环境中负担最重。了解抗生素耐药性的负担以及导致这种负担的主要病原体-药物组合，对于做出知情和针对具体地点的政策决定至关重要，特别是关于感染预防和控制方案、获得基本抗生素以及新疫苗和抗生素的研发。在许多低收入环境中存在严重的数据缺口，强调需要扩大微生物学实验室能力和数据收集系统，以提高我们对这一重要人类健康威胁的理解。比尔和梅林达盖茨基金会，惠康信托基金会，卫生和社会保健部使用由弗莱明基金管理的英国援助资金。
Antimicrobial resistance (AMR) poses a major threat to human health around the world. Previous publications have estimated the effect of AMR on incidence, deaths, hospital length of stay, and health-care costs for specific pathogen–drug combinations in select locations. To our knowledge, this study presents the most comprehensive estimates of AMR burden to date. We estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with bacterial AMR for 23 pathogens and 88 pathogen–drug combinations in 204 countries and territories in 2019. We obtained data from systematic literature reviews, hospital systems, surveillance systems, and other sources, covering 471 million individual records or isolates and 7585 study-location-years. We used predictive statistical modelling to produce estimates of AMR burden for all locations, including for locations with no data. Our approach can be divided into five broad components: number of deaths where infection played a role, proportion of infectious deaths attributable to a given infectious syndrome, proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antibiotic of interest, and the excess risk of death or duration of an infection associated with this resistance. Using these components, we estimated disease burden based on two counterfactuals: deaths attributable to AMR (based on an alternative scenario in which all drug-resistant infections were replaced by drug-susceptible infections), and deaths associated with AMR (based on an alternative scenario in which all drug-resistant infections were replaced by no infection). We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity. We present final estimates aggregated to the global and regional level. On the basis of our predictive statistical models, there were an estimated 4·95 million (3·62–6·57) deaths associated with bacterial AMR in 2019, including 1·27 million (95% UI 0·911–1·71) deaths attributable to bacterial AMR. At the regional level, we estimated the all-age death rate attributable to resistance to be highest in western sub-Saharan Africa, at 27·3 deaths per 100 000 (20·9–35·3), and lowest in Australasia, at 6·5 deaths (4·3–9·4) per 100 000. Lower respiratory infections accounted for more than 1·5 million deaths associated with resistance in 2019, making it the most burdensome infectious syndrome. The six leading pathogens for deaths associated with resistance (Escherichia coli, followed by Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa) were responsible for 929 000 (660 000–1 270 000) deaths attributable to AMR and 3·57 million (2·62–4·78) deaths associated with AMR in 2019. One pathogen–drug combination, meticillin-resistant S aureus, caused more than 100 000 deaths attributable to AMR in 2019, while six more each caused 50 000–100 000 deaths: multidrug-resistant excluding extensively drug-resistant tuberculosis, third-generation cephalosporin-resistant E coli, carbapenem-resistant A baumannii, fluoroquinolone-resistant E coli, carbapenem-resistant K pneumoniae, and third-generation cephalosporin-resistant K pneumoniae. To our knowledge, this study provides the first comprehensive assessment of the global burden of AMR, as well as an evaluation of the availability of data. AMR is a leading cause of death around the world, with the highest burdens in low-resource settings. Understanding the burden of AMR and the leading pathogen–drug combinations contributing to it is crucial to making informed and location-specific policy decisions, particularly about infection prevention and control programmes, access to essential antibiotics, and research and development of new vaccines and antibiotics. There are serious data gaps in many low-income settings, emphasising the need to expand microbiology laboratory capacity and data collection systems to improve our understanding of this important human health threat. Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.