Evaluation of a rapid turn-over, fully-automated ADAMTS13 activity assay: a method comparison study.
Jan A StratmannJosephine-Nana WardWolfgang MiesbachPublished in: Journal of thrombosis and thrombolysis (2021)
Thrombotic thrombocytopenic purpura (TTP) is a life-threatening thrombotic microangiopathy caused by severely reduced activity of the von-Willebrand factor-cleaving protease ADAMTS13, mainly caused by anti-ADAMTS-13 antibodies. Although several test systems for ADAMTS13 measurement exist, long turn-around times hamper the usability in daily practice. We performed a method comparison study for two commercially available ADAMTS13 assays and evaluated the agreement between the fully-automated rapid turn-over HemosIL AcuStar ADAMTS13 Activity assay and the manually performed TECHNOZYM ADAMTS-13 Activity assay. Twenty-four paired test samples derived from 10 consecutively recruited patients (n = 8, acquired TTP; n = 1, atypical hemolytic uremic syndrome; n = 1, control), of which nine test samples were collected in case of clinically apparent TTP and 13 samples were collected from TTP patients in clinical remission were included. Overall correlation between the TECHNOZYM and AcuStar assay was good with a Pearson R of 0.93 (p < 0.001). Agreement between the assays assessed with the Passing-Bablok analysis showed high agreement with an Intercept of - 2.56 (95% confidence interval [CI], - 5.07 to - 0.86) and Slope of 1.04 (95% CI 0.84-1.17). The absolute mean bias was 2.54% (standard difference [SD], 6.38%; 95% CI to 10.0-15.05%). Intra-method reliability was high with an absolute mean bias of - 0.13% (SD 3.21%; 95% CI to 6.42-6.16%). The observer agreement for categorial thresholds (> or < 10% ADAMTS3 activity) was kappa = 0.82 (95% CI 0.59-1.0). Conclusively, overall agreement between the testing methods was sufficient and we support previously published data suggesting the AcuStar assay being a valuable and accurate tool for ADAMTS13 activity testing and TTP diagnostics.
Keyphrases
- high throughput
- end stage renal disease
- newly diagnosed
- ejection fraction
- chronic kidney disease
- prognostic factors
- fluorescent probe
- sensitive detection
- peritoneal dialysis
- rheumatoid arthritis
- deep learning
- immune response
- physical activity
- systematic review
- magnetic resonance
- computed tomography
- artificial intelligence
- nuclear factor
- living cells
- social media
- quantum dots
- inflammatory response
- mass spectrometry
- case report
- big data