ArticleInternational journal of general medicine2026
New Methods for Activated Partial Thromboplastin Time -Based Clot Waveform Analysis: Normalization and Multi-Parameter Combination.
Article in International journal of general medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
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.
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