Key result
Monte Carlo simulation yielded measurement uncertainties for factor assays that were interchangeable with the top-down approach, except for FVIII from STA Compact.
Why the study?
The authors aimed to quantify the measurement uncertainty for coagulation factor activities using Monte Carlo simulation.
Monte Carlo simulation is a suitable computational method for quantifying measurement uncertainty in coagulation factor assays.
Answers are grounded in this paper and cite their sources.
Monte Carlo simulation may offer labs a computational alternative for factor assay uncertainty; leaves open multi-instrument validation before routine use.
OBJECTIVES: We aimed to quantify the measurement uncertainty (MU) for factor activities using the Monte Carlo simulation (MCS), which is a computational algorithm that simulates statistical sampling to obtain numerical results through complex mathematical calculations. METHODS: The uncertainties of factor V (FV), factor VIII (FVIII), and factor X (FX) were simulated with two coagulation testing systems: ACL TOP 750 CTS (Instrumentation Laboratory) and STA Compact (Diagnostica Stago). RESULTS: When the factor activities were 74% (FV), 68% (FVIII), and 89% (FX), the MUs were 3.5% (FV), 9.3% (VIII), and 2.8% (FX) for ACL TOP and 8.5% (FV), 18.2% (FVII), and 6.5% (FX) for STA Compact. MCS MUs were compared with MUs obtained from running actual samples (not simulated) using a method called the top-down approach. The MCS MU results were interchangeable with MUs from the top-down approach, except for FVIII from STA Compact. CONCLUSIONS: The MCS procedure is well suited for the quantification of MUs for factor assays over the entire measurement range.
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Lim et al. (2021) studied Factor assays. Monte Carlo simulation vs. Top-down approach was evaluated on Measurement uncertainty for factor activities. Monte Carlo simulation yielded measurement uncertainties for factor assays that were interchangeable with the top-down approach, except for FVIII from STA Compact.
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