Garvey Mary
Department of Life Science, Atlantic Technological University, F91 YW50 Sligo, Ireland.
Centre for Precision Engineering, Materials and Manufacturing Research (PEM), Atlantic Technological University, F91 YW50 Sligo, Ireland.
Antibiotics (Basel). 2024 Sep 13;13(9):877. doi: 10.3390/antibiotics13090877.
Neonatal infectious disease continues to result in high rates of infant morbidity and mortality. Early- and late-onset disease represent difficult to detect and difficult to treat illnesses, particularly when antimicrobial resistant pathogens are present. Newborns are immunodeficient and are at increased risk of vertical and horizontal infection, with preterm infants increasingly susceptible. Additional risk factors associated with infection include prolonged use of a central catheter and/or ventilation, congenital abnormalities, admittance to intensive care units, and the use of broad-spectrum antibiotics. There is increasing recognition of the importance of the host microbiome and dysbiosis on neonatal infectious disease, including necrotising enterocolitis and sepsis in patients. Current diagnostic methods rely on blood culture, which is unreliable, time consuming, and can result in false negatives. There is a lack of accurate and reliable diagnostic tools available for the early detection of infectious disease in infants; therefore, efficient triage and treatment remains challenging. The application of biomarkers, machine learning, artificial intelligence, biosensors, and microfluidics technology, may offer improved diagnostic methodologies. Point-of-care devices, such diagnostic methodologies, may provide fast, reliable, and accurate diagnostic aids for neonatal patients. This review will discuss neonatal infectious disease as impacted by antimicrobial resistance and will highlight novel point-of-care diagnostic options.
新生儿感染性疾病仍然导致婴儿发病率和死亡率居高不下。早发型和晚发型疾病代表着难以检测和治疗的病症,尤其是当存在抗菌药物耐药病原体时。新生儿免疫功能低下,垂直和水平感染风险增加,早产儿尤其易感。与感染相关的其他风险因素包括长期使用中心导管和/或通气、先天性异常、入住重症监护病房以及使用广谱抗生素。人们越来越认识到宿主微生物群和生态失调对新生儿感染性疾病的重要性,包括坏死性小肠结肠炎和患者败血症。目前的诊断方法依赖于血培养,而血培养不可靠、耗时且可能导致假阴性。缺乏用于早期检测婴儿感染性疾病的准确可靠的诊断工具;因此,有效的分诊和治疗仍然具有挑战性。生物标志物、机器学习、人工智能、生物传感器和微流控技术的应用可能会提供改进的诊断方法。即时检测设备,如这种诊断方法,可能为新生儿患者提供快速、可靠和准确的诊断辅助工具。本综述将讨论受抗菌药物耐药性影响的新生儿感染性疾病,并将重点介绍新型即时检测诊断选项。