Conventional and novel platelet parameters: Clinical and laboratory approaches.

Journal: Clinica chimica acta; international journal of clinical chemistry
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Abstract

INTRODUCTION: Platelet count and related indices obtained from the complete blood count (CBC) play an important role in the diagnosis, monitoring, and prognostic evaluation of various hematologic and systemic disorders. However, methodological variability and the lack of standardized analytical protocols may limit their diagnostic reliability in certain clinical settings. OBJECTIVES: This review aimed to summarize conventional and advanced platelet counting methodologies, evaluate their analytical strengths and limitations, and discuss the diagnostic and prognostic value of platelet indices, including mean platelet volume (MPV), platelet distribution width (PDW), platelet large cell ratio (P-LCR), immature platelet fraction (IPF), and plateletcrit (PCT). METHODS: A narrative literature review was conducted based on a structured search of PubMed, Scopus, Web of Science, and Google Scholar for studies published up to June 1, 2025. RESULTS: Modern hematology analyzers employ several technologies for platelet enumeration, including impedance (PLTI), optical light scatter (PLTO), fluorescence-based detection (PLTF), and hybrid approaches (PLTH). Each method demonstrates context-dependent advantages and limitations. Advanced fluorescence-based and hybrid methods show improved accuracy, particularly in severe thrombocytopenia. Platelet indices have been investigated as supportive markers in various clinical conditions, including immune thrombocytopenia, myelodysplastic syndromes, acute coronary syndrome, and sepsis. However, substantial variability between analyzers and the lack of harmonized analytical standards remain major challenges. CONCLUSION: Advanced platelet counting methods and indices show promising diagnostic and prognostic potential, but wider clinical implementation requires further validation and standardization. Integration of artificial intelligence-based analytics may improve accuracy, reproducibility, and clinical utility.

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