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一家大型教学医院重症监护病房中医护相关感染的多模式监测

Multimodal surveillance of healthcare associated infections in an intensive care unit of a large teaching hospital.

作者信息

Migliara G, Di Paolo C, Barbato D, Baccolini V, Salerno C, Nardi A, Alessandri F, Giordano A, Tufi D, Marinelli L, Cottarelli A, De Giusti M, Marzuillo C, De Vito C, Antonelli G, Venditti M, Tellan G, Ranieri M V, Villari P

机构信息

Department of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy.

Department of Anesthesiology and Critical Care, Policlinico Umberto I, Sapienza University of Rome, Rome, Italy.

出版信息

Ann Ig. 2019 Sep-Oct;31(5):399-413. doi: 10.7416/ai.2019.2302.

DOI:10.7416/ai.2019.2302
PMID:31304521
Abstract

BACKGROUND

Healthcare-associated infections (HAIs), or nosocomial infections, represent a significant burden in terms of mortality, morbidity, length of stay and costs for patients hospitalized in intensive care units (ICUs). Surveillance systems are recommended by national and international institutions to gather data on HAIs in order to develop and evaluate interventions that reduce the risk of HAIs.

STUDY DESIGN

Here we describe the methodology and the results of the surveillance system implemented in the ICU of the Policlinico Umberto I, a large teaching hospital in Rome, from April 2016 to October 2018.

METHODS

The multimodal infection surveillance system integrates four different approaches: i) active surveillance of inpatients; ii) environmental microbiological surveillance; iii) surveillance of isolated microorganisms; and iv) behavioral surveillance of healthcare personnel. Data were collected on catheter-related bloodstream infections, ventilation-associated pneumonia, catheter-associated urinary tract infections and primary bloodstream infections that developed in patients after 48 h in the ICU. For environmental surveillance 14 points were selected for sampling (i.e. bed edges, medication carts, PC keyboards, sink faucets). The system of active surveillance of HAIs also included surveillance of microorganisms, consisting of the molecular genotyping of bacterial isolates by pulsed-field gel electrophoresis (PFGE). From 1 November 2016, monitoring of compliance with guidelines for hand hygiene (HH) and proper glove or gown use by healthcare personnel was included in the surveillance system. After the first six months (baseline phase), a multimodal intervention to improve adherence to guidelines by healthcare personnel was conducted with the ICU staff.

RESULTS

Overall, 773 patients were included in the active surveillance. The overall incidence rate of device-related HAIs was 14.1 (95% CI: 12.2-16.3) per 1000 patient-days. The monthly device-related HAI incident rate showed a decreasing trend over time, with peaks of incidence becoming progressively lower. The most common bacterial isolates were Klebsiella pneumoniae (20.7%), Acinetobacter baumannii (17.2%), Pseudomonas aeruginosa (13.4%) and Staphylococcus aureus (5.4%). Acinetobacter baumannii and Klebsiella pneumoniae showed the highest proportion of isolates with a multidrug-resistant profile. A total of 819 environmental samples were collected, from which 305 bacterial isolates were retrieved. The most frequent bacterial isolates were Acinetobacter baumannii (27.2%), Staphylococcus aureus (12.1%), Enterococcus faecalis (11.1%), Klebsiella pneumoniae (5.2%) and Pseudomonas aeruginosa (4.7%). All Acinetobacter baumannii, Pseudomonas aeruginosa and Klebsiella pneumoniae environmental isolates were at least multidrug-resistant. Genotyping showed a limited number of major PFGE patterns for both clinical and environmental isolates of Klebsiella pneumoniae and Acinetobacter baumannii. Behavioral compliance rates significantly improved from baseline to post-intervention phase.

CONCLUSIONS

By integrating information gathered from active surveillance, environmental microbiological surveillance, surveillance of bacterial isolates and behavioral surveillance of healthcare personnel, the multimodal infection surveillance system returned a precise and detailed view of the infectious risk and microbial ecology of the ICU.

摘要

背景

医疗保健相关感染(HAIs),即医院感染,在重症监护病房(ICU)住院患者的死亡率、发病率、住院时间和费用方面构成了重大负担。国家和国际机构建议建立监测系统,以收集有关HAIs的数据,从而制定和评估降低HAIs风险的干预措施。

研究设计

在此,我们描述了2016年4月至2018年10月在罗马一家大型教学医院——翁贝托一世综合医院的ICU中实施的监测系统的方法和结果。

方法

多模式感染监测系统整合了四种不同方法:i)对住院患者的主动监测;ii)环境微生物监测;iii)对分离出的微生物的监测;iv)对医护人员的行为监测。收集了与导管相关的血流感染、呼吸机相关性肺炎、导管相关性尿路感染以及患者在ICU住院48小时后发生的原发性血流感染的数据。对于环境监测,选择了14个点进行采样(即床边、药车、电脑键盘、水槽水龙头)。HAIs主动监测系统还包括对微生物的监测,包括通过脉冲场凝胶电泳(PFGE)对细菌分离株进行分子基因分型。从2016年11月1日起,对医护人员手部卫生(HH)指南的遵守情况以及正确使用手套或隔离衣的监测纳入了监测系统。在前六个月(基线阶段)之后,与ICU工作人员进行了一项多模式干预,以提高医护人员对指南的遵守情况。

结果

总体而言,773例患者被纳入主动监测。与器械相关的HAIs的总体发病率为每1000患者日14.1(95%置信区间:12.2 - 16.3)。与器械相关的HAIs的月发病率随时间呈下降趋势,发病高峰逐渐降低。最常见的细菌分离株是肺炎克雷伯菌(20.7%)、鲍曼不动杆菌(17.2%)、铜绿假单胞菌(13.4%)和金黄色葡萄球菌(5.4%)。鲍曼不动杆菌和肺炎克雷伯菌显示出具有多重耐药谱的分离株比例最高。共收集了819份环境样本,从中分离出305株细菌。最常见的细菌分离株是鲍曼不动杆菌(27.2%)、金黄色葡萄球菌(12.1%)、粪肠球菌(11.1%)、肺炎克雷伯菌(5.2%)和铜绿假单胞菌(4.7%)。所有鲍曼不动杆菌、铜绿假单胞菌和肺炎克雷伯菌环境分离株至少具有多重耐药性。基因分型显示,肺炎克雷伯菌和鲍曼不动杆菌的临床和环境分离株的主要PFGE模式数量有限。行为依从率从基线阶段到干预后阶段有显著提高。

结论

通过整合从主动监测、环境微生物监测、细菌分离株监测和医护人员行为监测中收集的信息,多模式感染监测系统提供了ICU感染风险和微生物生态的精确而详细的情况。

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