“PRECISION IN THE THROMBOCYTE FUNCTIONAL ARRAY: AUTOMATED AGGREGOMETRY FOR DECODING CONGENITAL AND ACQUIRED DYSFUNCTION”

Abstract

Qualitative platelet disorders, whether intrinsic or extrinsic, present significant diagnostic challenges due to their diverse manifestations and complex underlying mechanisms. Conventional aggregation testing methods are labor-intensive, require skilled personnel, and are time-consuming, thereby, delaying diagnosis and limiting timely intervention. To address these challenges, automated hemostasis analyzers have emerged as a valuable solution, enabling faster diagnostics and promoting quicker recovery through early ascertainment and holistic management.

Objective: This investigation aims to evaluate the diagnostic precision and clinical utility of an automated platelet aggregation platform in identifying intrinsic and extrinsic thrombocyte abnormalities.

Methods: Using Hospital Based Diagnostic Study, Cases with suspected bleeding disorders and Cases who were already on Anti-Platelet Treatment (APT) (n-50) were analyzed using an automated aggregometer, Automated  LTA  method  has been  developed  by  Sysmex  (Kobe,  Japan)  on  a  routine  coagulation  analyzer (CS-2400). Comparative assessment was performed against manual light transmission aggregometry and clinical history to establish concordance and sensitivity.

Results: Individuals with suspected bleeding disorders (n=25) were younger (mean age 42.3 ± 11.2) and more likely female (52%) compared to those on antiplatelet therapy (n=25; mean age 64.7 ± 8.9, 72% male). Group A showed more mucocutaneous (68% vs. 12%) and surgical bleeding (36% vs. 8%). Both groups had normal platelet counts (210 ± 35 vs. 198 ± 29 ×10⁹/L).Diagnostic agreement between Lumi-LTA and CS-2400 was high (overall 90%), with perfect concordance for aspirin effect and normal function (100%), and slightly lower for PSD (83.3%) and δ-SPD (87.5%). On the CS-2400, aggregation amplitudes and detection rates were highest for ristocetin (70 ± 9%, 98%) and collagen (67 ± 10%, 96%), and lower for ADP (55 ± 12%, 94%), epinephrine (43 ± 15%, 88%), and arachidonic acid (32 ± 18%, 76%). APAL and CPAL scores in healthy controls (n=19) were 9.7 (8.8–10.0) and 10.0 (10.0–10.0). Patients on antiplatelet drugs (n=28) had lower scores: APAL 6.4 (5.9–8.0), CPAL 7.1 (5.7–8.5), both p<0.001. ASA-only users had APAL 8.9 (8.0–9.7, p=0.362), CPAL 6.7 (6.2–7.2, p<0.001); combined ASA+Plavix showed the largest drop (APAL 6.2, CPAL 4.7, both p<0.001). Congenital PFD (n=18) had lower aggregation with collagen (38% vs. 72%), U46619 (0.5 μM: 12% vs. 58%), TRAP (22% vs. 45%), and arachidonic acid (28% vs. 66%), all p<0.05 relative to acquired PFD (n=32). ATP release and granule content (serotonin 0.18 vs. 0.36; ADP 0.62 vs. 2.12) were significantly lower, and ATP/ADP higher (7.06 vs. 1.98, p=0.002)

Conclusion: Automated platelet aggregation analysis provides a robust, standardized alternative. Its adoption can enhance diagnostic consistency and support timely clinical decision-making, especially in high-throughput laboratory environments.