Introduction Transcranial Doppler (TCD) is method used to study cerebral
hemodynamics. The analysis majority of TCD studies are conducted at
group level, pooling change in flow velocity over several subjects.
Analysis of variance are the most frequently applied statistical methods
However, due to the dynamic nature of flow velocity, non- parametric
tests, may allow for a better representation of results. Methods During
a visuo-motor task, the mean flow velocity (MFV) in the middle cerebral
artery (MCA) in healthy-subjects was measured using TCD. All MFV values
were converted to relative values, i.e. compared with resting values.
The results obtained were analyzed using the general linear model (GLM)
and the general additional models (GAM). Both methods of analysis were
compared against with each other. Results The sample comprised 30
healthy participants, aged 33.87±7.48 years; 33% females. The MFV for
the first 20 seconds was 1.06±0.07 in the right-MCA and 1.08±0.07 in the
left-MCA. Both MCAs showed a steady increase in MFV, returning to
resting state. GL- and GA-Models showed a statistically significant
change in MFC (GLM: F (2, 3598) = 16.76, p<0.001; GAM: F (2,
3598) = 21.63, p<0.001); as well as differences in hemispheric
side and gender. Comparing the models using a Chi-square test for
goodness of fit yields a significant difference X2 (9.9556) = 0.6836, p=
<0.000. With a superiority of the models using GAM. Discussion
GLM and GAM of the MFV yielded similar results; the model using the GAM
resulted in a better measurement of fit. The GAM’s advantage becomes
clearer when the mean flow velocity curves are visualised; yielding a
more realistic approach to brain hemodynamics, thus allowing for an
improvement in interpretation of the mathematical and statistical
results. Conclusion Our results demonstrate the utility of the GAM for
the analysis of hemodynamic measurements.