Assessing Stroke Recurrence Risk by Using a Lipoprotein-Associated Phospholipase A2 and Platelet Count-Based Nomogram

Area of Science:

• Neuroscience
• Biochemistry
• Cardiovascular Research

Background:

• Stroke recurrence is a major clinical challenge requiring better predictive markers.
• Identifying novel predictors can refine risk assessment and therapeutic strategies for ischemic stroke patients.

Purpose of the Study:

• To investigate the predictive value of the interaction between lipoprotein-associated phospholipase A2 (Lp-PLA2) and platelets for stroke recurrence.
• To develop and validate a nomogram incorporating this interaction for enhanced stroke risk prediction.

Main Methods:

• Retrospective cohort study of 580 ischemic stroke patients.
• Multivariable logistic regression analysis to identify independent predictors.
• Development of a nomogram incorporating traditional risk factors and the Lp-PLA2 * platelet interaction.

Main Results:

• Diabetes mellitus, hypertension, LDL, Lp-PLA2 levels, and platelet counts were independent predictors.
• The interaction of Lp-PLA2 and platelet count showed superior predictive power compared to individual factors.
• The developed nomogram demonstrated enhanced accuracy in predicting stroke recurrence.

Conclusions:

• The interaction between Lp-PLA2 and platelets is a significant predictor of stroke recurrence.
• The novel nomogram provides a practical tool for personalized stroke risk assessment and management.
• Multifactorial assessment, including molecular markers, is crucial for mitigating stroke recurrence.