Laboratório de Genética Molecular de Microrganismos, Instituto Oswaldo Cruz - Fundação Oswaldo Cruz, Avenida Brasil, 4365, Pavilhão Leônidas Deane, 6º andar, sala 607, Rio de Janeiro, RJ, 21040-900, Brazil.
Department of Engineering, Hospital Federal Dos Servidores Do Estado (HFSE), Rio de Janeiro, RJ, Brazil.
Antimicrob Resist Infect Control. 2021 Jun 16;10(1):92. doi: 10.1186/s13756-021-00944-5.
The emergence and spread of antimicrobial resistance and infectious agents have challenged hospitals in recent decades. Our aim was to investigate the circulation of target infectious agents using Geographic Information System (GIS) and spatial-temporal statistics to improve surveillance and control of healthcare-associated infection and of antimicrobial resistance (AMR), using Klebsiella pneumoniae complex as a model.
A retrospective study carried out in a 450-bed federal, tertiary hospital, located in Rio de Janeiro. All isolates of K. pneumoniae complex from clinical and surveillance cultures of hospitalized patients between 2014 and 2016, identified by the use of Vitek-2 system (BioMérieux), were extracted from the hospital's microbiology laboratory database. A basic scaled map of the hospital's physical structure was created in AutoCAD and converted to QGis software (version 2.18). Thereafter, bacteria according to resistance profiles and patients with carbapenem-resistant K. pneumoniae (CRKp) complex were georeferenced by intensive and nonintensive care wards. Space-time permutation probability scan tests were used for cluster signals detection.
Of the total 759 studied isolates, a significant increase in the resistance profile of K. pneumoniae complex was detected during the studied years. We also identified two space-time clusters affecting adult and paediatric patients harbouring CRKp complex on different floors, unnoticed by regular antimicrobial resistance surveillance.
In-hospital GIS with space-time statistical analysis can be applied in hospitals. This spatial methodology has the potential to expand and facilitate early detection of hospital outbreaks and may become a new tool in combating AMR or hospital-acquired infection.
近几十年来,抗菌药物耐药性和感染病原体的出现和传播给医院带来了挑战。我们的目的是使用地理信息系统(GIS)和时空统计学来研究目标感染病原体的循环情况,以改善对医院获得性感染和抗菌药物耐药性(AMR)的监测和控制,以肺炎克雷伯菌复合体为例。
这是一项在位于里约热内卢的一家 450 床位联邦三级医院进行的回顾性研究。从 2014 年至 2016 年,从住院患者的临床和监测培养物中使用 Vitek-2 系统(生物梅里埃)鉴定的所有肺炎克雷伯菌复合体分离株,均从医院微生物实验室数据库中提取出来。使用 AutoCAD 创建医院物理结构的基本缩放地图,并将其转换为 QGis 软件(版本 2.18)。然后,根据耐药谱和耐碳青霉烯类肺炎克雷伯菌(CRKp)复合体的患者对细菌进行密集和非密集护理病房的地理定位。使用时空置换概率扫描检验来检测集群信号。
在所研究的 759 株分离株中,肺炎克雷伯菌复合体的耐药谱在研究期间显著增加。我们还发现了两个时空集群,分别影响不同楼层携带 CRKp 复合体的成年和儿科患者,这两个集群未被常规抗菌药物耐药性监测发现。
医院内的 GIS 与时空统计分析相结合,可以在医院中应用。这种空间方法具有扩展和促进医院爆发早期检测的潜力,并可能成为对抗 AMR 或医院获得性感染的新工具。