Can Study of Variations in Platelet Indices in Adult Thrombocytopenias Help to Differentiate the Underlying Mechanism? A Prospective Study

Introduction: Thrombocytopenia (TCP) is defined as a platelet count below 1,50,000 per microliter. This fall can be attributed to increased destruction, decreased production in bone marrow and pooling of platelets. A good knowledge of the cause and clinical course of the underlying pathology as reflected by the platelet indices contributes to the better management of TCP. With the advent of automation in haematology, these indices are now available from the routinely used blood cell counters in the laboratory. Aim: To determine if studying the variation in platelet indices helps to identify the aetiology of TCP. Materials and Methods: The prospective study was conducted in the haematology wing of central diagnostics attached to a medical college in Bangalore, Karnataka, India over a period of three months from June 2019 to August 2019. A total of 598 cases of adult TCPs were encountered, out of which 505 cases met the inclusion criteria and were categorised into three groups, namely- Hyperdestructive (Group 1), Hypoproductive (Group 2) and Abnormal pooling (Group 3). Variation of platelet indices {Platelet count, Plateletcrit (PCT), Mean Platelet Volume (MPV), Platelet Distribution Width (PDW)} were studied not only between the groups but also with the severity of TCPs. Data was analysed using the software Statistical Package for Social Sciences (SPSS) program version 20 and tested for statistical significance using one-way Analysis of Variance (ANOVA) test. A p-value of <0.05 was considered as statistically significant. Results: Of the 505 cases a majority fell under Group 1- 420 cases (83%). A higher value of MPV (11.870±1.3) and PDW (15.63±3.4) were seen in Group 1 compared to Groups 2 and 3. There was also significant variation among the platelet indices (PCT, MPV, PDW) with the severity of TCPs. Conclusion: Platelet counts along with a good knowledge on interpretation of platelet parameters obtained by automated analysers play a pivotal role in determining the aetiology of TCPs, thereby, providing better initial patient management.