DOI 10.1080/23279095.2025.2469261
Alterations in cerebral artery flow velocity acceleration pattern correlate with cognitive impairment in diabetes mellitus.
Аннотация
INTRODUCTION
Flow velocity acceleration pattern is related to shear stress, pressure changes, cardiovascular risk factors, diabetes mellitus, hypertension, endothelial dysfunction and arterial stiffness. Considering the hemodynamic alterations in cognitive impairment, perturbations in cerebral artery flow acceleration pattern may correlate with cognitive impairment, which could enhance our understanding of how cardiovascular risk factors drive cognitive decline from a mechanistic point of view.
METHOD: The first derivative of middle cerebral artery flow velocity waveforms obtained via transcranial Doppler were computed to visualize acceleration/deceleration waves (a,b,c,d,e) in ensemble-averaged signals. Vascular Aging Index was calculated per its definition (VAI:(b-c-d-e)/a). Relationship between multiple cognitive domains and VAI was evaluated with standard statistical tests.
RESULTS
VAI was significantly correlated with HVLT total recall (Hopkins Verbal Learning Test-revised) (r: -0.310 p: 0.046, n: 42), delayed recall (r: -0.396 p: 0.009), % Retention (r: -0.305 p: 0.050) and components of RCFT(Rey-Osterrieth Complex Figure Test), namely raw copy score (r: -0.524 p < 0.001), immediate recall (r: -0.323 p: 0.037). Controlling for age, body mass index, gray matter volume and diabetes duration yielded stronger correlations but lower group numbers due to missing data. Correlation coefficients for VAI with HVLT delayed recall and % Retention were -0.439 (p: 0.012) and -0.444(p: 0.011 n: 36) respectively. Likewise the adjusted correlations of VAI with RCFT components were improved (Raw Copy r: -0.557 p < 0.001, Immediate Recall r: -0.440 p: 0.012, Delayed Recall (r: -0.358 p: 0.044).
CONCLUSION
In patients with diabetes, cerebral artery flow velocity acceleration pattern correlates with cognitive performance in visuo-constructional and verbal cognitive domains. Computational fluid dynamics may aid developing a better mechanistic understanding of arterial hemodynamics-cortical function coupling.
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