New diagnostic technologies in laboratory medicine: potential benefits and challenges.

IF 3.8 4区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Michael Nagler, Henning Nilius, Grégoire Michielin, Mojgan Masoodi, Carlo R Largiadèr
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引用次数: 0

Abstract

Laboratory tests play a central role in medicine, as they help to make diagnoses, assess prognosis and risk of disease, and monitor therapies, thus contributing to 70% of all medical decisions. This cross‑sectional function offers great potential for technologic and organizational innovation to influence health care as a whole. In recent years, a variety of technologies have emerged and entered the field of medical research, or even medical care. A new generation of biosensors enables laboratory tests to be carried out at the point of care and allows for faster medical decisions. Modern devices allow for patient‑centric blood sampling, which eliminates the need for painful blood draws, patient traveling, and limits the workload of health care professionals. Analytical techniques, such as metabolomics, lipidomics, or proteomics can identify biomarkers extremely sensitively, even down to individual cells. Pharmacogenomics allows for determination of genetic polymorphisms that predict a response to chemotherapeutic agents. Machine‑learning approaches can handle large amounts of multilayered data for diagnostic applications. However, this enormous diagnostic potential is far from being utilized and only very few applications have been implemented in clinical practice. Why is this the case? In this article, we describe the key technologic fields, discuss their medical potential, and list obstacles to their implementation. In addition, we present a methodologic framework to support researchers, clinicians, and authorities in development and implementation of novel diagnostic approaches.

实验室医学的新诊断技术:潜在的益处和挑战。
实验室检测在医学中发挥着核心作用,因为它们有助于做出诊断、评估预后、疾病风险和监测疗法,从而为 70% 的医疗决策做出贡献。这种跨部门的功能为技术和组织创新提供了巨大的潜力,从而对整个医疗保健产生影响。近年来,各种技术不断涌现并进入医学研究甚至医疗领域。新一代生物传感器可在医疗点确定实验室检测结果,从而更快地做出医疗决策。最新的设备可以实现以病人为中心的血液采样,从而避免了痛苦的抽血、病人的奔波和医护人员的工作量。代谢组学、脂质组学或蛋白质组学等分析技术可以极其灵敏地识别生物标记物,甚至精确到单个细胞。药物基因组学可以确定预测对化疗药物反应的基因多态性。机器学习方法可以处理大量多层数据,用于诊断应用。然而,这一巨大的诊断潜力远未得到利用,只有极少数应用已在临床实践中实施。为什么会出现这种情况呢?在本文中,我们将描述关键技术领域,讨论其医疗潜力和实施障碍。此外,我们还提出了一个方法论框架,以支持研究人员、临床医生和权威机构开发和实施新型诊断方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.50
自引率
0.00%
发文量
176
审稿时长
6-12 weeks
期刊介绍: Polish Archives of Internal Medicine is an international, peer-reviewed periodical issued monthly in English as an official journal of the Polish Society of Internal Medicine. The journal is designed to publish articles related to all aspects of internal medicine, both clinical and basic science, provided they have practical implications. Polish Archives of Internal Medicine appears monthly in both print and online versions.
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