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Analysis of a Point-of-Care HbA1c Assay: Is It Time for an HbA1c Error Grid?

Jan S Krouwer
Published in: Journal of diabetes science and technology (2019)
In an article in Journal of Diabetes Science and Technology, Arnold et al have presented a thorough study of imprecision components for a point-of-care hemoglobin A1c (HbA1c) assay. An interesting and innovative approach is the combination of data from different studies to arrive at a total error estimate. But total error has the oxymoron feature of estimating performance for most (95%) but not all of the results. An HbA1c error grid would provide the severity for results that exceed the 6% requirement. Since this device is intended for Clinical Laboratory Improvement Amendments waived labs and allows for finger-stick samples, monitoring the Food and Drug Administration adverse event database (MAUDE, Manufacturer and User Facility Device Experience) is recommended.
Keyphrases
  • drug administration
  • high throughput
  • type diabetes
  • cardiovascular disease
  • public health
  • machine learning
  • adverse drug
  • artificial intelligence
  • case control
  • human health
  • neural network