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Related Concept Videos

Data Validation01:15

Data Validation

448
Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
448

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Dried blood spot collection, sample quality, and fieldwork conditions: Structural validations for conversion into

Axel Börsch-Supan1,2,3, Luzia M Weiss1, Martina Börsch-Supan4

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|October 16, 2020
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Summary

This study developed conversion formulas to accurately measure analyte values from dried blood spot (DBS) samples, even under challenging fieldwork conditions. These findings improve the reliability of large-scale health surveys using DBS collection.

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Area of Science:

  • Biomedical Science
  • Public Health Research
  • Analytical Chemistry

Background:

  • The SHARE study collected approximately 27,000 dried blood spot (DBS) samples from 13 European countries.
  • Accurate conversion of DBS analyte values to venous blood samples (VBS) is crucial for large-scale health research.
  • Fieldwork conditions can significantly impact DBS sample quality and analyte measurements.

Purpose of the Study:

  • To develop conversion factors for analyte values between DBS and VBS.
  • To account for adverse fieldwork conditions affecting DBS sample integrity.
  • To ensure accurate data in large-scale epidemiological studies like SHARE.

Main Methods:

  • Simulated adverse fieldwork conditions (e.g., spot size, temperature, humidity, drying time) in a laboratory setting.
  • Collected VBS and DBS from 20 donors under controlled conditions.
  • Used 3420 outcomes to estimate DBS analyte values and develop conversion formulas.

Main Results:

  • Field conditions and sample quality significantly influence DBS analyte values, varying by assay.
  • Smaller spot sizes and lack of desiccant negatively impact most markers.
  • Temperature and drying time affect specific analytes like HDL, CysC, CRP, and tHb.

Conclusions:

  • Lab-based adjustment formulas alone are insufficient for DBS samples collected under field conditions.
  • Simulating adverse conditions allowed for the validation of DBS samples.
  • Established conversion formulas demonstrate high prediction accuracy for DBS analyte values obtained under challenging fieldwork.