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Published on: June 4, 2020
New Methods for Activated Partial Thromboplastin Time -Based Clot Waveform Analysis: Normalization and
Hongmei Dong1, Qi Hu1, Huan Wang1
1Department of Laboratory Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China.
Background:
The evaluation of a prolonged activated partial thromboplastin time (APTT) traditionally relies on a diagnostic cascade, including mixing studies to screen for inhibitors, specific factor activity assays, and specialized tests like lupus anticoagulant detection. Activated partial thromboplastin time-based clot waveform analysis (CWA-APTT) has emerged as an optical technique that captures the entire kinetic profile of clot formation, offering potential for enhanced diagnostic triage and monitoring. However, conventional analysis of CWA-APTT parameters, particularly peak-related metrics, is confounded by variables like fibrinogen concentration, limiting their specificity for accurately quantifying coagulation factor activity. Furthermore, the diagnostic utility of time-distribution parameters remains underexplored, especially for distinguishing between factor deficiencies and phospholipid-dependent inhibitors. This study aims to improve the correlation between peak-related parameters in APTT-based clotting curves and coagulation factor activity through novel data analysis methods and to investigate the potential clinical utility of time-distribution parameters in distinguishing sample types.
Methods:
A total of 263 blood samples collected from patients with hemophilia A, hemophilia B, or lupus anticoagulant positivity were used to perform CWA-APTT. Normalization methods were applied to process the characteristic parameters in CWA-APTT. Then, the correlation between the processed peak-related parameters and coagulation factor activity was analyzed, and the ability of time-distribution parameters to distinguish different sample types was investigated.
Results:
Following normalization, peak-related parameters more accurately reflect coagulation factor activity. Time-distribution parameters can also monitor coagulation factor activity and exhibit a certain degree of sample specificity. Combined analysis of time-distribution parameters enhances the ability to distinguish sample types, achieving a higher concordance rate in curve feature recognition compared to APTT correction tests.
Conclusion:
This study innovatively explored new applications of CWA-APTT characteristic parameters. It was found that normalization enables peak-related parameters to more accurately reflect coagulation factor activity, and multi-parameter combined analysis can significantly enhance the ability of CWA-APTT to distinguish clinical samples.
