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Validation of a Metabolite Panel for a More Accurate Estimation of Glomerular Filtration Rate Using Quantitative LC-MS/MS. | LitMetric

AI Article Synopsis

  • Clinical guidelines suggest estimating kidney function using eGFR methods based on creatinine, cystatin C, or both, but only the combined method (eGFRcr-cys) meets performance standards against measured GFR (mGFR).
  • Researchers developed a novel eGFR method (eGFRmet) utilizing a panel of metabolites without relying on creatinine, cystatin C, or demographic info, tested across 2,424 participants.
  • The new eGFRmet showed a lower frequency of large errors (10.0%) compared to eGFRcr and eGFRcys, although not outperforming the combined method (eGFRcr-cys at 8.7%), indicating its potential as

Article Abstract

Background: Clinical practice guidelines recommend estimation of glomerular filtration rate (eGFR) using validated equations based on serum creatinine (eGFRcr), cystatin C (eGFRcys), or both (eGFRcr-cys). However, when compared with the measured GFR (mGFR), only eGFRcr-cys meets recommended performance standards. Our goal was to develop a more accurate eGFR method using a panel of metabolites without creatinine, cystatin C, or demographic variables.

Methods: An ultra-performance liquid chromatography-tandem mass spectrometry assay for acetylthreonine, phenylacetylglutamine, pseudouridine, and tryptophan was developed, and a 20-day, multiinstrument analytical validation was conducted. The assay was tested in 2424 participants with mGFR data from 4 independent research studies. A new GFR equation (eGFRmet) was developed in a random subset (n = 1615) and evaluated in the remaining participants (n = 809). Performance was assessed as the frequency of large errors [estimates that differed from mGFR by at least 30% (1 - P); goal <10%].

Results: The assay had a mean imprecision (≤10% intraassay, ≤6.9% interassay), linearity over the quantitative range ( > 0.98), and analyte recovery (98.5%-113%). There was no carryover, no interferences observed, and analyte stability was established. In addition, 1 - P in the validation set for eGFRmet (10.0%) was more accurate than eGFRcr (13.1%) and eGFRcys (12.0%) but not eGFRcr-cys (8.7%). Combining metabolites, creatinine, cystatin C, and demographics led to the most accurate equation (7.0%). Neither equation had substantial variation among population subgroups.

Conclusions: The new eGFRmet equation could serve as a confirmatory test for GFR estimation.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6646882PMC
http://dx.doi.org/10.1373/clinchem.2018.288092DOI Listing

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