In-house chromogenic anti-factor Xa assay: development, validation, and identification of factors predicting APTT discordance

Figures

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  Figure 1. Reaction time optimization. Incubation time optimization showing Δ(OD) decreased rapidly within 60 s and reached equilibrium after 90 s.

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  Figure 2. Reaction time optimization. Reaction time optimization. Detection time kinetics showing Δ(OD) declined sharply in the first 25 s and stabilized after 55 s.

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  Figure 3. Standard curve for anti-Xa activity of heparin. Seven-point calibration curves using standard plasma (0–1.50 IU/ml). In-house system (Y = −0.01181 + 1.00678X, R2 = 0.99883).

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  Figure 4. Standard curve for anti-Xa activity of heparin. Seven-point calibration curves using standard plasma (0–1.50 IU/ml). STA-Liquid system (Y = 7.1312 – 3.7510X, R2 = 0.99854). Each point represents duplicate measurements.

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  Figure 5. Analytical sensitivity evaluation. LoB determination showing distribution of 60 blank measurements (mean 0.042 IU/ml, LoB 0.073 IU/ml at 95th percentile).

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  Figure 6. Analytical sensitivity evaluation. LoQ established at 0.10 IU/ml based on convergence of MAD ( ≤ 30%), POD (≥95%), and TE ( ≤ 40%) criteria. MAD, median absolute deviation; POD, probability of detection; TE, total error.

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  Figure 7. Linear range of the in-house anti-factor Xa detection system. Linear regression analysis (Y = 1.00596X – 0.00387, R2 = 0.99923) with duplicate measurements on three separate days (n = 6 per dilution level).

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  Figure 8. Method comparison between in-house and STA-Liquid anti-factor Xa systems. Correlation analysis showing strong linear relationship (Y = −0.01018 + 1.03984X, R2 = 0.972, Pearson r = 0.986, ρ < 0.001, n = 120).

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  Figure 9. Method comparison between in-house and STA-Liquid anti-factor Xa systems. Bland-Altman analysis showing mean bias of 0.005 IU/ml with 95% limits of agreement at ±1.96 SD (−0.1 to 0.11 IU/ml); five points (6.25%) fell outside limits.

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  Figure 10. Correlation between APTT and anti-factor Xa activity. Linear regression analysis showing moderate correlation (Y = 132.7X + 44.1, R2 = 0.46, n = 110).

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  Figure 11. ROC curve analysis for APTT therapeutic threshold determination. ROC curves comparing therapeutic vs. sub-therapeutic (AUC = 0.870, optimal cutoff = 71.34 s) and therapeutic vs. supra-therapeutic (AUC = 0.855, optimal cutoff = 125.80 s).

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  Figure 12. Concordance analysis between APTT and anti-factor Xa classifications. Heatmap showing distribution of 110 patients across APTT and anti-Xa categories with concordance and discordance patterns.