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Dried blood spot collection, sample quality, and fieldwork conditions: Structural validations for conversion into standard values
Author(s) -
BörschSupan Axel,
Weiss Luzia M.,
BörschSupan Martina,
Potter Alan J.,
Cofferen Jake,
Kerschner Elizabeth
Publication year - 2020
Publication title -
american journal of human biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.559
H-Index - 81
eISSN - 1520-6300
pISSN - 1042-0533
DOI - 10.1002/ajhb.23517
Subject(s) - analyte , dried blood spot , sample (material) , venous blood , medicine , blood collection , environmental science , humidity , chromatography , chemistry , emergency medicine , geography , meteorology
Objectives SHARE, a pan‐European panel study in 27 European countries and Israel, has collected dried blood spot (DBS) samples from approximately 27 000 respondents in 13 countries. We aim to obtain factors to convert analyte values between DBS and venous blood samples (VBS) taking account of adverse fieldwork conditions such as small spot size, high temperature and humidity, short drying time and long shipment times. Methods We obtained VBS and DBS from a set of 20 donors in a laboratory setting, and treated the DBS in a systematic and controlled fashion simulating SHARE fieldwork conditions. We used the 3420 outcomes to estimate from DBS analyte values the values that we would have obtained had it been feasible to collect and analyze the donors' venous blood samples. Results The influence of field conditions and sample quality on DBS analyte values is significant and differs among assays. Varying spot size is the main challenge and affects all markers except HbA1c. Smaller spots lead to overly high measured levels. A missing desiccant is detrimental for all markers except CRP and tHb. The temperature to which the samples are exposed plays a significant role for HDL and CysC, while too brief a drying time affects CRP and CysC. Lab‐based adjustment formulae only accounting for the differences between re‐liquefied DBS and venous blood do not address these fieldwork conditions. Conclusions By simulating adverse fieldwork conditions in the lab, we were able to validate DBS collected under such conditions and established conversion formulae with high prediction accuracy.