Optimization of hemolysis index thresholds for biochemical and immunoassays

BACKGROUND: Our study aimed at establishing analyte-specific hemolysis-index thresholds on 18 chemistry assays to avoid re-sampling on Atellica© Solution (Siemens Healthcare Diagnostics, Los Angeles, CA, USA). METHODS: We focused on the analytes which showed the highest degree of hemolysis interference at one or two baseline concentrations for the following 18 analytes: ALT (alanine aminotransferase), ammonium, AST (aspartate aminotransferase), CK (creatine kinase), creatinine, folates, FSH (follicle stimulating hormone), GGT (γ-glutamyltransferase), Hp (haptoglobin), iron, insulin, LD (lactate dehydrogenase), lipase, potassium, urea, uric acid, vitamins B12, and D. Interference was quantified as a percentage difference from the Hb-free baseline sample. Each calculated bias was compared to the four cutoffs: 10%Δ, analytical change limit, total change limit, or reference change limit. RESULTS: Analytes that did not exceed the predefined allowable-bias criterion for hemolysis included creatinine, FSH, GGT, iron, urea, uric acid, and vitamin B12. Among the affected analytes, the largest positive and negative biases were observed for AST, folates, LD, and potassium. The principal quantitative optimized thresholds for the hemolysis-sensitive analytes were AST, folates, iron, potassium, and LD tests. CONCLUSION: Our study allowed us to supplement the data provided by the manufacturer and to optimize the thresholds for interference with hemolysis management of hemolyzed samples.

Authors

Institutions

Publication Details

Journal
Bioanalysis
Published
2026-10-16
DOI
https://doi.org/10.1080/17576180.2026.2744031
Primary Topic
Clinical Laboratory Practices and Quality Control
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimization of hemolysis index thresholds for biochemical and immunoassays

Jean‐Paul Cristol, Caroline Coulon, Anne‐Marie Dupuy, Marion Morena et al.
Bioanalysis
Clinical Laboratory Practices and Quality Control
article

Optimization of hemolysis index thresholds for biochemical and immunoassays

Jean‐Paul Cristol, Caroline Coulon, Anne‐Marie Dupuy, Marion Morena, Delphine Tabone
article en

Abstract

BACKGROUND: Our study aimed at establishing analyte-specific hemolysis-index thresholds on 18 chemistry assays to avoid re-sampling on Atellica© Solution (Siemens Healthcare Diagnostics, Los Angeles, CA, USA). METHODS: We focused on the analytes which showed the highest degree of hemolysis interference at one or two baseline concentrations for the following 18 analytes: ALT (alanine aminotransferase), ammonium, AST (aspartate aminotransferase), CK (creatine kinase), creatinine, folates, FSH (follicle stimulating hormone), GGT (γ-glutamyltransferase), Hp (haptoglobin), iron, insulin, LD (lactate dehydrogenase), lipase, potassium, urea, uric acid, vitamins B12, and D. Interference was quantified as a percentage difference from the Hb-free baseline sample. Each calculated bias was compared to the four cutoffs: 10%Δ, analytical change limit, total change limit, or reference change limit. RESULTS: Analytes that did not exceed the predefined allowable-bias criterion for hemolysis included creatinine, FSH, GGT, iron, urea, uric acid, and vitamin B12. Among the affected analytes, the largest positive and negative biases were observed for AST, folates, LD, and potassium. The principal quantitative optimized thresholds for the hemolysis-sensitive analytes were AST, folates, iron, potassium, and LD tests. CONCLUSION: Our study allowed us to supplement the data provided by the manufacturer and to optimize the thresholds for interference with hemolysis management of hemolyzed samples.

Bioanalysis
Université de Montpellier (FR)
Good health and well-being
Openalex Percentile: Top 13%
Clinical Laboratory Practices and Quality Control
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.