Practical Considerations for the Use of the Rapid AcuStar ® ADAMTS13 Activity Assay in the Diagnosis of Acute Thrombotic Thrombocytopenic Purpura (TTP).
Jun YongStephen MacDonaldColin DowneyRebekah FretwellCaroline LawrencePaul MurphyThomas PitchfordTina DuttPublished in: Journal of clinical medicine (2024)
Introduction: Conventional practice in the management of acute TTP entails empirical treatment of suspected cases whilst awaiting confirmatory ADAMTS13 deficiency testing. Rapid ADAMTS13 assays offer increased accessibility and rapid diagnostics. The new automated HemosIL AcuStar ® ADAMTS13 assay has seen increasing use among UK TTP Specialist Centres alongside the traditional ELISA method to confirm severe ADAMTS13 deficiency. Methods: A multi-centre retrospective case-control study was performed to review patients demonstrating discrepant ADAMTS13 activity results measured using rapid (AcuStar ® ) and ELISA assays in parallel from September 2019 to December 2021. Cases were compared with a cohort of suspected TTP patients exhibiting no difference in assay results and in relation to their presenting characteristics and pre-test probability of a diagnosis of TTP. Results: Where the clinical index of suspicion for TTP was high at presentation, acute TTP was confirmed using the AcuStar ® assay < 0.2 IU/dL and subsequently < 10 IU/dL by ELISA with zero incidence of discrepancy. For patients with low clinical suspicion of acute TTP, a discrepancy between the AcuStar ® and ELISA assay results was observed in 2% of cases; 5-10 IU/dL in AcuStar ® , confirmed as >20 IU/dL by ELISA. A concurrent cancer diagnosis or sepsis was observed in 40% of discrepant cases. Conclusions: Where acute TTP is strongly suspected, there is a good correlation between the rapid AcuStar ® ADAMTS13 assay and the conventional ELISA assay. Where the clinical suspicion of acute TTP is low, caution should be exercised in the interpretation of the ADAMTS13 activity using the AcuStar ® assay. Accurate interpretation requires robust ADAMTS13 testing algorithms to be incorporated into diagnostic pathways.
Keyphrases
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- aortic dissection
- machine learning
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- hepatitis b virus
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- prognostic factors
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