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[Normal ranges and accuracy of laboratory analyses]
Insights
Establishing definitive laboratory normal ranges is challenging due to inherent analytical uncertainty. A three-zone model (health, disease, intermediate) and statistical shift scattering improve diagnostic accuracy for biomarkers.
Area of Science:
- Clinical chemistry
- Laboratory medicine
- Biomarker analysis
Context:
- Establishing definitive laboratory normal ranges for health and disease is inherently uncertain.
- Analytical and preanalytical errors contribute to the variability of laboratory test results.
- Existing population-based reference intervals may not fully capture individual health status.
Purpose:
- To address the challenge of establishing precise normal ranges for laboratory indices.
- To propose a model for interpreting laboratory results that accounts for uncertainty.
- To enhance the accuracy of diagnostic conclusions based on laboratory analyses.
Summary:
- Laboratory results possess an inherent uncertainty, making a strict distinction between health and disease difficult.
- A three-zone interpretation model (health, disease, intermediate) is proposed, similar to blood glucose and cholesterol guidelines.
- The statistical shift scattering method is recommended for assessing analytical and preanalytical errors, improving the assessment of uncertainty.
Impact:
- This approach can lead to more nuanced and accurate interpretations of laboratory diagnostics.
- It provides a framework for understanding the probabilistic nature of diagnostic conclusions.
- The proposed methods aim to refine the definition and application of reference intervals in clinical practice.
Abstract:
For many reasons, it is impossible to make a distinction between the laboratory indices of health and disease (to establish the normal ranges); there is always an uncertainty portion wherein the result of an analysis allows the conclusion to be made only with a definitive probability. The real uncertainty (i.e. inaccuracy) of an analysis extends this portion. The generally recognized recommendations on blood glucose and cholesterol should be taken as a model, which identifies three zones: 1) health; 2) disease; and 3) intermediate one when well-being cannot be stated, but a significant disease is absent. The uncertainty of the result of analysis is best assessed by the statistical shift scattering method that characterizes the wide spectrum of not only analytical, but also some preanalytical errors. The ranges of normal values (a reference interval) established by a traditional population-based study may be taken only as interim ones, by introducing the half-width intermediate zone of one shift scatter.
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