Rapid, Breath Volatile Metabolite-Based Diagnostic for In Vivo Identification and Antibiotic Resistance Profiling of Bacterial Pathogens in Ventilator-Associated Pneumonia

基于呼吸挥发性代谢物的快速诊断，用于呼吸机相关肺炎细菌病原体的体内鉴定和抗生素耐药性分析

• 批准号: 9922858
• 负责人: Sophia Koo
• 金额: $ 108.92万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-20 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9922858
• 关键词: Acinetobacter baumannii; Address; Advanced Development; Algorithms; Antibiotic Resistance; Antibiotic Therapy; Antibiotic susceptibility; Antibiotics; Antimicrobial Resistance; Bacteria; Bacterial Antibiotic Resistance; Bacterial Infections; Bacterial Model; Breath Tests; Cephalosporin Resistance; Cessation of life; Clinical; Collaborations; Combined Antibiotics; Communities; Data; Detection; Deterioration; Development; Devices; Diagnosis; Diagnostic; Diagnostic Procedure; Diagnostic tests; Enterobacter cloacae; Enterobacteriaceae; Escherichia coli; Etiology; Gas Chromatography; High Prevalence; Hour; Industrialization; Infection; Intensive Care Units; Klebsiella pneumoniae; Laboratories; Lung; Mechanics; Metabolic; Methicillin Resistance; Microbe; Microbiology; Mus; Mycoses; Nosocomial Infections; Onset of illness; Organism; Outcome; Patient Care; Patients; Phenotype; Pneumonia; Predisposition; Preparation; Pseudomonas aeruginosa; Resistance; Resistance profile; Respiratory System; Risk; Spectrometry; Staphylococcus aureus; Statistical Methods; Symptoms; Testing; Time; Ventilator; Work; base; carbapenem resistance; combat; disability; improved; improved outcome; in vivo; industry partner; microbial; miniaturize; noninvasive diagnosis; pathogen; pathogenic bacteria; pneumonia model; pressure; prototype; resistance mechanism; response; tandem mass spectrometry; tool; ventilator-associated pneumonia

Project Summary/Abstract: The lack of diagnostics that rapidly and accurately identify bacterial infections drives empiric antibiotic prescribing in patients with pneumonia – ultimately, 37-50% of these antibiotics are unnecessary. These issues are amplified in the intensive care unit (ICU), where antimicrobial resistance is common, the risk of imminent clinical deterioration and death is high, and clinicians are under pressure to make rapid treatment decisions. Ventilator-associated pneumonia (VAP) is the most common ICU hospital-acquired infection, responsible for approximately half of all ICU antibiotic prescribing. Time to effective antibiotic treatment is a critical determinant of outcome, but many patients with VAP receive inadequate empiric treatment due to the high prevalence of resistant organisms in VAP. Clinical findings in VAP are highly nonspecific, and 30-60% of antibiotics prescribed for suspected VAP are ultimately unnecessary. Despite a high pulmonary bacterial load in patients with VAP, the lung has traditionally been a particularly inaccessible space without the use of invasive diagnostic procedures. We have established proof of concept in murine VAP models that there are bacterial species-specific breath volatile metabolite signatures in VAP caused by Staphylococcus aureus, Pseudomonas aeruginosa, Escherichia coli and Klebsiella pneumoniae, and that microbial breath volatile metabolites have markedly different responses to antibiotic exposure within a few hours in phenotypically susceptible (S) vs. non-susceptible (NS) organisms. In close collaboration with industry partners and a team of experts in antimicrobial resistance, microbiology, VAP, advanced statistical methods, and regulatory matters, we propose further development of an advanced, miniaturized gas chromatography-differential mobility spectrometry (GC-DMS) diagnostic platform for the rapid, noninvasive, breath-based diagnosis of VAP and its most common causative pathogens, S. aureus, P. aeruginosa, K. pneumoniae, E. coli, Enterobacter cloacae, and Acinetobacter baumannii, exploiting differential volatile metabolite responses to effective and ineffective antibiotic therapy to obtain in vivo phenotypic information about antibiotic susceptibility. Using thermal desorption-GC-tandem mass spectrometry and in parallel, a rapid GC-DMS diagnostic device, we will systematically characterize these species-specific breath signatures and early responses to antibiotic therapy in S vs. NS organisms in murine VAP models and in patients with suspected VAP, defining and validating breath signatures that (a) identify VAP, distinguishing it from other ventilator-associated conditions and respiratory tract colonization, (b) identify its underlying microbial etiology, and (c) determine whether the microbe is S or NS by examining its early response to antibiotics, and create GC-DMS algorithms that identify these signatures in breath data automatically, in preparation for a 510(k) clearance study. This diagnostic device will transform the care of patients with VAP and sharply reduce diagnostic delays, both facilitating early administration of appropriate antibiotics and reducing unnecessary antibiotic use.

项目摘要/摘要： 缺乏快速准确地识别细菌感染的诊断方法推动了经验性抗生素的发展 给肺炎患者开处方--最终，这些抗生素中有37%-50%是不必要的。这些问题 在重症监护病房(ICU)中被放大，在那里抗菌素耐药性很常见，危险迫在眉睫 临床恶化和死亡率很高，临床医生面临着迅速做出治疗决定的压力。 呼吸机相关性肺炎(VAP)是ICU最常见的医院获得性感染，是 约占ICU抗生素处方总数的一半。有效的抗生素治疗的时间至关重要 预后的决定因素，但许多VAP患者由于高死亡率而未得到充分的经验性治疗 VAP中耐药微生物的流行情况。VAP的临床表现高度非特异性，30%-60%的 为疑似VAP开的抗生素最终是不必要的。尽管肺部细菌载量很高 在VAP患者中，传统上肺是一个特别难以接近的空间，如果不使用 侵入性诊断程序。我们已经在小鼠VAP模型中建立了概念证明 金黄色葡萄球菌引起的呼吸性肺炎的细菌种类特异性呼吸挥发性代谢物特征， 铜绿假单胞菌、大肠埃希菌和肺炎克雷伯菌，以及微生物呼吸的挥发性 在表型上，代谢产物在几小时内对抗生素暴露的反应明显不同 敏感(S)与不敏感(NS)生物。与行业合作伙伴和 抗菌素耐药性、微生物学、VAP、先进统计方法和监管事项方面的专家， 我们建议进一步开发一种先进的、小型化的气相色谱--微分迁移率 光谱(GC-DMS)诊断平台用于VAP及其ITS的快速、无创、基于呼吸的诊断 最常见的致病菌是金黄色葡萄球菌、铜绿假单胞菌、肺炎克雷伯菌、大肠杆菌、阴沟肠杆菌、 和鲍曼不动杆菌，利用挥发性代谢物的差异反应有效和无效 抗生素治疗，以获得有关抗生素敏感性的体内表型信息。使用热能 解吸-GC-串联质谱仪和一个并行的快速GC-DMS诊断装置，我们将 系统地描述这些物种特有的呼吸特征和对抗生素治疗的早期反应 S与NS在小鼠呼吸机相关性肺炎模型和疑似呼吸机相关性肺炎患者中的对比：定义和验证呼吸 (A)识别VAP的签名，将其与其他呼吸机相关疾病和呼吸系统疾病区分开来 肠道定植，(B)确定其潜在的微生物病原学，以及(C)确定微生物是S还是 NS通过检查其对抗生素的早期反应，并创建GC-DMS算法来识别这些签名 在自动呼吸数据中，为510(K)清除研究做准备。这个诊断设备将会改变 对VAP患者的护理和极大地减少诊断延误，都有利于早期给予 适当的抗生素和减少不必要的抗生素使用。