ArticleJIMD reports2024
Calculation of continuous reference intervals for biological parameters exhibiting strong age-dependent level changes: Its application to glycosaminoglycans and sialic acid in urine.
Article in JIMD reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Integrated glycoproteomics reveals site-specific N-glycosylation defects in phosphomannomutase two congenital disorder of glycosylation.The Journal of biological chemistry · 2026Article
- Article
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Authors and funding
6 authors.
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Abstract
Glycosaminoglycan (GAG) and sialic acid (total and free) assays are used as first-line screening tests for the diagnosis of mucopolysaccharidoses and glycoproteinoses, respectively. There is a pronounced age-dependent variation in the urinary concentrations of these metabolites in the normal population, and the stratification of the reference values into discrete age ranges may lead to an undesirably high number of false-positive or false-negative results. The aim of this study was to design a method for calculating continuous reference intervals as a function of age and its application to the analysis of GAGs and sialic acid (total, free, and conjugated) in urine. In the postpubertal period, concentrations of urinary GAGs and sialic acid have reached a plateau, so a traditional calculation of the reference range in this specific age group was considered appropriate. In the prepubertal period, a nonlinear regression performed with the Excel add-in Solver was used to fit the logarithmized concentrations of the controls to a curve that represents the mean values as a function of age. A uniform distribution of the residuals was obtained, which allowed the calculation of the reference intervals by adding the values of their 2.5 and 97.5 percentiles to the independent variable of the regression curve to calculate the upper and lower reference curves. The main advantages of the developed method are (1) a reduction in the number of control samples needed to obtain adequate reference intervals and (2) an improvement in the reliability of diagnostic screening by reducing the uncertainty generated by the gaps in the traditional age-stratified method.
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