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The Need for Standardization of Continuous Glucose Monitoring Performance Evaluation: An Opinion by the International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Continuous Glucose Monitoring.
J Diabetes Sci Technol
November 2024
Working Group on Continuous Glucose Monitoring, Scientific Division, The International Federation of Clinical Chemistry and Laboratory Medicine, Milano, Italy.
Metrics derived from continuous glucose monitoring (CGM) systems are often discordant between systems. A major cause is that CGM systems are not standardized; they use various algorithms and calibration methods, leading to discordant CGM readings across systems. This discordance can be addressed by standardizing CGM performance assessments: If manufacturers aim their CGM systems at the same target, then CGM readings will align across systems.
View Article and Find Full Text PDFThe Pharmacogenomics Global Research Network Implementation Working Group: global collaboration to advance pharmacogenetic implementation.
Pharmacogenet Genomics
January 2025
Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Pharmacogenetics promises to optimize treatment-related outcomes by informing optimal drug selection and dosing based on an individual's genotype in conjunction with other important clinical factors. Despite significant evidence of genetic associations with drug response, pharmacogenetic testing has not been widely implemented into clinical practice. Among the barriers to broad implementation are limited guidance for how to successfully integrate testing into clinical workflows and limited data on outcomes with pharmacogenetic implementation in clinical practice.
View Article and Find Full Text PDFThe Diabetes Technology Society Error Grid and Trend Accuracy Matrix for Glucose Monitors.
J Diabetes Sci Technol
November 2024
University of California San Francisco, San Francisco, CA, USA.
Article Synopsis
- An error grid is a tool that helps compare glucose levels measured by devices to see if they are correct and to identify any risks.
- Experts created a new error grid called the DTS Error Grid that works for both blood glucose monitors (BGMs) and continuous glucose monitors (CGMs), organizing accuracy into five risk zones.
- The results showed that the DTS Error Grid provides a clearer picture of how accurate these devices are and includes a separate matrix to evaluate how well CGMs track glucose trends over time.
ADLM Guidance Document on the Measurement and Reporting of Lipids and Lipoproteins.
J Appl Lab Med
September 2024
Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States.
Article Synopsis
- Accurate measurement of blood lipids is essential for managing atherosclerotic disease risk, but variations in testing methods and reporting still exist.
- The guidance document aims to standardize lipid testing by providing recommendations on fasting requirements, lipid panel components, and specific lipid measurements like non-HDL-C and LDL-C.
- It emphasizes that non-HDL-C and LDL-C should be reported whenever possible, fasting is usually not necessary, and modern equations should be used for LDL-C calculations, making direct measurements less common.
Substantial Underestimation of Fine-Mode Aerosol Loading from Wildfires and Its Radiative Effects in Current Satellite-Based Retrievals over the United States.
Environ Sci Technol
September 2024
State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
Wildfires generate abundant smoke primarily composed of fine-mode aerosols. However, accurately measuring the fine-mode aerosol optical depth (fAOD) is highly uncertain in most existing satellite-based aerosol products. Deep learning offers promise for inferring fAOD, but little has been done using multiangle satellite data.
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