Transformation of Sequential Hospital and Outpatient Laboratory Data into Between-Day Reference Change Values.

Area of Science:

• Clinical Chemistry
• Laboratory Medicine
• Biostatistics

Background:

• Intrapatient consecutive measurements can be analyzed using Taylor series to determine total variation (y0).
• With minimal preanalytical variation, y0 approximates the variable component of Reference Change Value (RCV) calculations.
• RCVs are crucial for interpreting the significance of changes in serial laboratory test results.

Purpose of the Study:

• To determine the between-day RCV for 17 analytes using patient data.
• To compare patient-derived RCVs (RCVAlternate) with RCVs calculated from healthy participants (RCVhealthy).
• To assess the clinical relevance of RCVAlternate by integrating all sources of variation.

Main Methods:

• Analyzed 4.2 million general chemistry results from 653 consecutive days of patient data.
• Transformed serial patient values into 95% 2-sided RCV (RCVAlternate).
• Calculated RCVhealthy from quality control data and biological variation (BV) studies.

Main Results:

• RCVAlternate values were found to be similar to RCVhealthy values for most analytes.
• Equivalence was observed for sodium, chloride, bicarbonate, calcium, magnesium, phosphate, albumin, and total protein.
• Increased variation was noted for glucose, AST, creatinine, and potassium, while direct bilirubin and urea showed lower variation.

Conclusions:

• RCVAlternate integrates analytic, biologic, and preanalytical variation, reflecting real-world clinical observations.
• The similarity between RCVAlternate and RCVhealthy suggests the validity of the RCVAlternate approach.
• Further research is recommended to fully understand patient test result variations in routine laboratory settings.