Comparison of classical and modified aPTT mixing tests improves accuracy in identifying coagulopathies, implying enhanced diagnostics.
Background The activated partial thromboplastin time (aPTT) mixing test is widely used to investigate prolonged aPTT from factor deficiencies, inhibitors, or lupus anticoagulant (LA), but its interpretation remains challenging. Refining protocols and indices may improve accuracy. Objectives To compare classical and modified aPTT mixing tests using conventional and novel indices for distinguishing FVIII deficiency, FVIII inhibitors, LA, and heparin, and to develop a structured interpretation algorithm. Methods A total of 215 plasma samples (50 factor deficiencies, 51 FVIII inhibitors, 64 LA‐positive, 50 heparinized) underwent classical and modified 1:1 mixing tests. ICA and %Correction were calculated for immediate and 2‐h incubated mixes, while ΔICA and Δ%Correction were derived from their differences. Diagnostic performance was assessed by ROC analysis, and a proposed algorithm was designed. Results Both protocols demonstrated excellent reliability (ICC > 0.90) and substantial agreement in interpretation ( κ = 0.65–0.75). The modified protocol consistently outperformed the classical approach, with index of circulating anticoagulant (ICA)‐based indices showing the greatest improvement. Novel indices ΔICA and Δ%Correction further enhanced diagnostic specificity compared with single indices. ΔICA achieved the highest performance, with near‐perfect accuracy in distinguishing factor deficiency from FVIII inhibitors and FVIII inhibitors from LA (AUC = 0.99 for both). The algorithm applying ΔICA after ICA of the immediate mix effectively separated factor deficiencies, FVIII inhibitors, and LA with high sensitivity and specificity, minimizing diagnostic overlap. Conclusions The modified aPTT mixing test provides a reliable and practical approach for interpreting prolonged aPTT. The structured algorithm, combining the modified protocol with ΔICA, offers a systematic and clinically applicable framework for laboratory evaluation.
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Police et al. (2026) studied this question.
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