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This is a Literature Review study.

August 16, 2025

From metabolic profiles to clinical interpretation: multivariate approaches to population-based and personalized reference intervals and reference change values.

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A multivariate approach improves the interpretation of laboratory test results by capturing relationships among multiple analytes, enhancing clinical relevance.
Using data from related analytes, current methods struggle with univariate applications for test panels, highlighting the need for updated reference intervals and change values.
The proposed method combines single tests into meaningful groups, aiming to interpret the group holistically rather than independently, which could lead to better clinical outcomes.
This approach supports the idea that metabolism involves networks of biomolecules, which requires a comprehensive interpretation model across test panels.

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Implication

Opinion paper presents a multivariate framework to improve interpretation of test panels, suggesting better clinical decisions through correlated analytes.

Cite This Study

Coşkun et al. (2025) studied this question.

synapsesocial.com/papers/68a26d256226934df6fbfcfe https://doi.org/10.1515/cclm-2025-0786

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Implication

Opinion paper presents a multivariate framework to improve interpretation of test panels, suggesting better clinical decisions through correlated analytes.

From metabolic profiles to clinical interpretation: multivariate approaches to population-based and personalized reference intervals and reference change values.

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Discussion

Implication

Cite This Study

From metabolic profiles to clinical interpretation: multivariate approaches to population-based and personalized reference intervals and reference change values.

Key Points

Discussion

Implication

Cite This Study

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