Monocyte-to-Lymphocyte Ratio in Clot Analysis as a Marker of Cardioembolic Stroke Etiology

Area of Science:

• Neurology
• Hematology
• Biomarker Discovery

Background:

• Cryptogenic stroke (CS) diagnosis remains challenging, often requiring differentiation between cardioembolic and other etiologies.
• Identifying high-risk cardioembolic etiology (HRCE) is crucial for targeted prevention strategies.
• Current diagnostic methods may not always definitively determine the stroke's origin.

Purpose of the Study:

• To identify novel biomarkers within intracranial clots for predicting high-risk cardioembolic etiology (HRCE) in patients with cryptogenic strokes (CS).
• To utilize flow cytometry (FC) analysis of clot components to distinguish HRCE from other stroke types, such as large arterial atherosclerosis (LAA).

Main Methods:

• A prospective single-center study analyzed clot composition using flow cytometry (FC) in patients with large vessel occlusion strokes.
• Key cellular components analyzed included granulocytes, monocytes, and lymphocytes, focusing on the monocyte-to-lymphocyte ratio (MLr).
• Machine learning models, specifically multilevel decision trees with random forest classifiers, were employed to identify predictors of HRCE.

Main Results:

• The monocyte percentage and MLr in clots independently predicted HRCE when compared to LAA strokes.
• In cryptogenic stroke patients, the MLr emerged as the most significant predictor of HRCE in decision tree analysis.
• An MLr cutoff of 1.59 demonstrated high sensitivity (91.23%) and moderate specificity (44%) for HRCE detection in CS patients.

Conclusions:

• Clot analysis via flow cytometry reveals elevated monocyte-to-lymphocyte ratio as an independent marker for cardioembolic etiology in cryptogenic strokes.
• The MLr shows significant potential as a diagnostic tool for identifying HRCE in CS patients.
• This research contributes to a more precise etiological diagnosis of stroke, guiding therapeutic decisions.