Ducharme James, Self Wesley H, Osborn Tiffany M, Ledeboer Nathan A, Romanowsky Jonathan, Sweeney Timothy E, Liesenfeld Oliver, Rothman Richard E
Department of Medicine, McMaster University, Hamilton, ON L8S 4L8, Canada.
Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, TN 37220, USA.
J Pers Med. 2020 Dec 7;10(4):266. doi: 10.3390/jpm10040266.
Current diagnostics are insufficient for diagnosis and prognosis of acute infections and sepsis. Clinical decisions including prescription and timing of antibiotics, ordering of additional diagnostics and level-of-care decisions rely on understanding etiology and implications of a clinical presentation. Host mRNA signatures can differentiate infectious from noninfectious etiologies, bacterial from viral infections, and predict 30-day mortality. The 29-host-mRNA blood-based InSep test (Inflammatix, Burlingame, CA, formerly known as HostDx Sepsis) combines machine learning algorithms with a rapid point-of-care platform with less than 30 min turnaround time to enable rapid diagnosis of acute infections and sepsis, as well as prediction of disease severity. A scientific advisory panel including emergency medicine, infectious disease, intensive care and clinical pathology physicians discussed technical and clinical requirements in preparation of successful introduction of InSep into the market. Topics included intended use; patient populations of greatest need; patient journey and sample flow in the emergency department (ED) and beyond; clinical and biomarker-based decision algorithms; performance characteristics for clinical utility; assay and instrument requirements; and result readouts. The panel identified clear demand for a solution like InSep, requirements regarding test performance and interpretability, and a need for focused medical education due to the innovative but complex nature of the result readout. Innovative diagnostic solutions such as the InSep test could improve management of patients with suspected acute infections and sepsis in the ED, thereby lessening the overall burden of these conditions on patients and the healthcare system.
目前的诊断方法对于急性感染和脓毒症的诊断及预后评估并不充分。临床决策,包括抗生素的处方和使用时机、额外诊断检查的安排以及护理级别决策,都依赖于对临床表现的病因及影响的理解。宿主mRNA特征可区分感染性与非感染性病因、细菌感染与病毒感染,并预测30天死亡率。基于29种宿主mRNA的血液InSep检测(Inflammatix公司,加利福尼亚州伯林盖姆市,前身为HostDx脓毒症检测)将机器学习算法与快速即时护理平台相结合,周转时间不到30分钟,能够快速诊断急性感染和脓毒症,并预测疾病严重程度。一个由急诊医学、传染病学、重症监护和临床病理学医生组成的科学咨询小组讨论了将InSep成功推向市场所需的技术和临床要求。主题包括预期用途;最有需求的患者群体;急诊科及其他场所的患者就医流程和样本流转;基于临床和生物标志物的决策算法;临床效用的性能特征;检测和仪器要求;以及结果解读。该小组确定了对InSep这类解决方案的明确需求、对检测性能和可解释性的要求,以及由于结果解读具有创新性但复杂的性质而需要进行针对性医学教育。像InSep检测这样的创新诊断解决方案可以改善急诊科疑似急性感染和脓毒症患者的管理,从而减轻这些病症对患者和医疗系统的总体负担。