Announcing a new article publication for Cardiovascular Innovations and Applications journal. Accurate diagnosis of transient ischemic attacks (TIAs) is challenging. This study was aimed at analyzing blood biomarkers to distinguish TIAs from mimics.
The levels of eight candidate biomarkers were measured in 234 patients with suspected TIA, 103 of whom had TIA and 131 of whom had mimics. We compared the groups, examined the effects of the biomarkers via logistic regression, compared models with likelihood ratio tests, assessed predictive accuracy with receiver operating characteristic analysis, and optimized cutoff values with the PanelomiX algorithm. ApoC-III, IL-6, and vWF were the most effective biomarkers in discriminating TIAs from mimics after adjustment for clinical variables.
The area under the curve was 0.73 for ApoC-III; 0.74 for IL-6; 0.74 for vWF; and 0.72 for the clinical model. The likelihood ratio test indicated that these biomarkers showed better fit than the clinical model: Apo-CIII (P ≤ 0.031), IL-6 (P ≤ 0.030), and vWF (P ≤ 0.040). With the PanelomiX algorithm, a model incorporating biomarker thresholds (Apo-CIII >132.29 ng/mL, IL-6 >5.45 pg/mL, vWF <280.09%, NIHSS score >4.5, and age >41.5 years) achieved a sensitivity of 100% and a specificity of 28% in distinguishing TIAs from mimics.
These findings suggest that combining blood biomarkers with clinical data might potentially enhance TIA diagnosis.
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