A mathematical model of measurement uncertainty of single substrate enzyme assays. (30th July 2014)

• Record Type: Journal Article
• Authors: Ramamohan, Varun; Abbott, James T.; Yih, Yuehwern
• Is Part Of: Journal of chemometrics. Volume 29:Number 1(2015:Jan.)
• Page Start: 49
• Page End: 58
• Publication Date: 2014-07-30
• Subjects: Chemistry -- Mathematics -- Periodicals; Chemistry -- Statistical methods -- Periodicals; 542.85
• DOI: 10.1002/cem.2661
• Languages: English
• ISSNs: 0886-9383

Abstract

<abstract abstract-type="main" id="cem2661-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p id="cem2661-para-0001">Clinical laboratory tests provide critical information at every stage of the medical decision‐making process, and measurement of the activity levels of enzymes such as alkaline phosphatase, lactate dehydrogenase, etc. provide information regarding various body functions such as the liver and gastrointestinal tract. The uncertainty associated with these enzyme measurement processes describes the quality of the measurement process, and therefore methods to improve the quality of the measurement process require minimizing the measurement uncertainty of the enzyme assay. In this study, we develop a mathematical model of the lactate dehydrogenase measurement process, with uncertainty introduced into its parameters that represent the sources of variation in the different components and stages of the measurement process. The Monte Carlo method is then utilized to estimate the uncertainty associated with the model, and therefore the measurement process. An empirical function used to generate estimates of uncertainty for patient samples with unknown activity levels is constructed using the model. The model is then used to quantify the contributions of the individual sources of uncertainty to the net measurement uncertainty and also quantify the effect of uncertainty within the calibration process on the distribution of the measurement result. Copyright © 2014 John Wiley & Sons, Ltd.</p> </abstract>