PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 3, 2026Cureus0 citationsOpen Access

Platelet Mass Signatures and Thrombin-Activatable Fibrinolysis Inhibitor as Discriminators of Primary Thrombocytosis: Development of a Screening Algorithm in an Eastern Sudanese Cohort

BBBashir A Bashir

Key Points

  • This study evaluates the effectiveness of platelet indices and TAFI in distinguishing between primary and reactive thrombocytosis.
  • Cross-sectional analytical study with 74 Sudanese patients with thrombocytosis.
  • Measurement of platelet indices and TAFI levels.
  • Assessment of diagnostic performance using ROC curve analysis and multivariable logistic regression.
  • Primary thrombocytosis showed significantly elevated platelet count, plateletcrit, platelet large cell count, and TAFI levels (all p < 0.001).
  • TAFI showed the highest discrimination according to ROC analysis (AUC: 0.925).
  • A multi-marker model using PLT, PCT, PLCC, and TAFI achieved an AUC of 0.975.

Abstract

Background: Clinically differentiating primary from reactive thrombocytosis is crucial, but it often requires expensive molecular and bone marrow examinations. Platelet indices and thrombosis-associated biomarkers may offer valuable diagnostic assistance. Objective: This study aims to evaluate platelet indices and thrombin-activatable fibrinolysis inhibitor (TAFI) for discrimination between primary and reactive thrombocytosis and to develop a combined diagnostic model. Methods: A cross-sectional analytical study included 74 Sudanese patients with thrombocytosis (29 primary and 45 reactive). Platelet indices and TAFI were measured. Diagnostic performance was assessed using the receiver operating characteristic (ROC) curve analysis and multivariable logistic regression. Results: Primary thrombocytosis exhibited markedly elevated platelet count (PLT), plateletcrit (PCT), platelet large cell count (PLCC), and TAFI levels (all p < 0.001). ROC analysis indicated the highest discrimination for TAFI (area under the curve (AUC): 0.925), plateletcrit (AUC: 0.916), and platelet count (AUC: 0.890). The optimal TAFI threshold of 24.6 resulted in a sensitivity of 82.8% and a specificity of 97.8%. A composite multi-marker model (PLT + PCT + PLCC + TAFI) attained an AUC of 0.975. Conclusion: Plateletcrit and TAFI are powerful discriminators of primary thrombocytosis. A combined marker model offers superior diagnostic accuracy and may function as a cost-effective screening technique in settings with limited resources.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Bashir A Bashir (2026) studied this question.

synapsesocial.com/papers/69cf58cb5a333a8214609a42https://doi.org/10.7759/cureus.106174
Ask AI
Helpful
Bookmark
Share
View Full Paper