Introduction: Light transmission aggregometry (LTA) is well-established in platelet function analysis
(Gresele 2015; AWMF 2018) and can be used for monitoring of platelet inhibitor therapy
(Nakahara et al. 2022). The laborious manual sample preparation process however is
susceptible to handling errors, which has led to the development of automated aggregometers
with high potential for increased standardization. The Thrombomate XRA (Behnk Elektronik,
Germany) is a recently introduced aggregometer with a relatively high degree of automation.
In this study, we compared the Thrombomate XRA to the Platelet aggregation Profiler-8E
(PAP-8, mölab, Germany), a well-established manual aggregometer.
Method: We included 63 patients from clinical routine, which were either screened for platelet
function disorders or underwent monitoring of platelet inhibitor therapy. LTA was
performed on PAP-8 and Thrombomate for each patient, using citrated platelet-rich
plasma. Inductors used for the PAP-8 were arachidonic acid (ARA, 1mM), ADP low (5
µM), ADP high (20 µM), epinephrine (EPI, 5µM), collagen (COL, 1.9 µg/mL, calf) and
ristocetin (RIS, 1.2 mg/mL). Manufacturer: mölab. Inductors used on the Thrombomate
were ARA (1mM), ADP low (5 µM), ADP high (10 µM), EPI (5µM), COL (2 µg/mL, horse)
and RIS (1.2 mg/mL). Manufacturer: probe&go. Results are reported as maximal aggregation
(MA).
Results: Quantitative comparison revealed absolute differences>20% MA in 19 patients for ARA,
23 patients for ADP low, 23 patients for ADP high, 11 patients for COL, 14 patients
for EPI, and 7 patient for RIS. Qualitative expert-based interpretation of aggregation
curves, based on reference intervals provided by the respective manufacturers, led
to differing results in 14 patients for ARA, 20 patients for ADP low, 12 patients
for ADP high, 4 patients for COL, 6 patients for EPI, and 1 patient for RIS.
Conclusion: Lacking comparability between LTA platforms is a well-described issue in platelet
function analysis (Althaus et al. 2019). Using patient samples from clinical routine,
we showed that this issue applies to the comparison of manual and automated aggregometers
as well, even though previous reports showed a much more agreeable method comparability
in healthy individuals. Discrepant results may be a result of differences in the inductors
or variations in the automated or manual workflows, including potential handling errors
or pre-analytic influences. The present study represents the first independent method
comparison of the Thrombomate aggregometer to date.
