Department of Pathology and Laboratory Medicine, University of California Davis, Sacramento, CA, USA.
Patient Care Services, University of California Davis, Sacramento, CA, USA.
Crit Rev Clin Lab Sci. 2023 Jun;60(4):290-299. doi: 10.1080/10408363.2023.2170316. Epub 2023 Feb 3.
Dysglycemia is common among hospitalized patients. Accurate point-of-care (POC) glucose monitoring is necessary for the safe administration of insulin. Unfortunately, POC glucose meters are not all created equal. Interfering factors such as abnormal hematocrit, abnormal oxygen tension, and oxidizing/reducing substances can lead to inaccurate glucose measurements and result in inappropriate insulin dosing. The introduction of autocorrecting glucose meters has changed the POC testing landscape. Autocorrecting glucose meters provide more accurate measurements and have been associated with improved glycemic control in hospitalized patients. Continuous glucose monitoring has also created interest in using these platforms in at-risk inpatient populations. Future glucose monitoring technologies such as artificial intelligence/machine learning, wearable smart devices, and closed-loop insulin management systems are poised to transform glycemic management. The goal of this review is to provide an overview of glucose monitoring technology, summarize the clinical impact of glucose monitoring accuracy, and highlight emerging and future POC glucose monitoring technologies.
高血糖在住院患者中很常见。准确的即时检测(POC)血糖监测对于安全使用胰岛素至关重要。不幸的是,POC 血糖仪并非完全相同。干扰因素如异常的红细胞压积、异常的氧张力和氧化/还原物质会导致不准确的血糖测量,并导致胰岛素剂量不当。自动校正血糖仪的引入改变了 POC 检测的格局。自动校正血糖仪提供更准确的测量值,并与住院患者血糖控制的改善相关。连续血糖监测也引起了人们对在高危住院人群中使用这些平台的兴趣。未来的血糖监测技术,如人工智能/机器学习、可穿戴智能设备和闭环胰岛素管理系统,有望改变血糖管理。本综述的目的是提供血糖监测技术的概述,总结血糖监测准确性的临床影响,并强调新兴和未来的 POC 血糖监测技术。