Beschreibung:
<jats:title>Abstract</jats:title><jats:p>Sieving coefficients reported in dialyzer data sheets and instructions for use (IFUs) indicate the potential of different solutes to pass across a particular membrane. Despite being measured in vitro, sieving coefficient data are often used as a predictor of the clinical performance of dialyzers. Although standards for the measurement of sieving coefficients exist, the stated methodologies do not offer sufficient guidance to ensure comparability of test results between different dialyzers. The aim of this work was to investigate the relationship between sieving coefficients and published clinical performance indicators for two solutes, albumin loss and beta‐2 microglobulin (β<jats:sub>2</jats:sub>M) reduction ratio (RR), and to assess the impact of different in vitro test parameters on sieving coefficient values for albumin, β<jats:sub>2</jats:sub>M, and myoglobin. Clinical albumin loss and β<jats:sub>2</jats:sub>M RR for commercially available dialyzers used in hemodialysis (HD) and post‐dilution hemodiafiltration (HDF) were extracted from the literature and plotted against sieving coefficients reported in data sheets and IFUs. Albumin, β<jats:sub>2</jats:sub>M, and myoglobin sieving coefficients of a selection of dialyzers were measured per the ISO 8637 standard. The impact of in vitro testing conditions was assessed by changing blood flow rate, ultrafiltration (UF) rate, sampling time, and origin of test plasma. Results showed variation in albumin loss and β<jats:sub>2</jats:sub>M RR for the same sieving coefficient across different dialyzers in HD and HDF. Changes in blood flow rates, UF rates, sampling time, and test plasma (bovine vs. human) caused marked differences in sieving coefficient values for all investigated solutes. When identical testing conditions were used, sieving coefficient values for the same dialyzer were reproducible. Testing conditions have a marked impact on the measurement of sieving coefficients, and values should not be compared unless identical conditions are used. Further, variability in observed clinical data in part reflects the lack of definition of test conditions.</jats:p>