ArticleHealth science reports2021
Functional transcranial Doppler: Selection of methods for statistical analysis and representation of changes in flow velocity.
Article in Health science reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
- Functional transcranial Doppler: Selection of methods for statistical analysis and representation of changes in flow velocity.Health science reports · 2021Article
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Authors and funding
5 authors at 3 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionTranscranial Doppler (TCD) is a method used to study cerebral hemodynamics. In the majority of TCD studies, regression analysis and analysis of variance are the most frequently applied statistical methods. However, due to the dynamic and interdependent nature of flow velocity, nonparametric tests may allow for better statistical analysis and representation of results.
methodThe sample comprised 30 healthy participants, aged 33.87 ± 7.48 years; with 33% (n = 10) females. During a visuo-motor task, the mean flow velocity (MFV) in the middle cerebral artery (MCA) was measured using TCD. The MFV was converted to values relative to the resting state. The results obtained were analyzed using the general linear model (GLM) and the general additional model (GAM). The fit indices of both analysis methods were compared with each other.
resultsBoth MCAs showed a steady increase in MFV during the visuo-motor task, smoothly returning to resting state values. During the first 20 seconds of the visuo-motor task, the MFV increased by a factor of 1.06 ± 0.07 in the right-MCA and by a factor of 1.08 ± 0.07 in the left-MCA. GLM and GAM showed a statistically significant change in MFV (GLM:F(2, 3598) = 16.76,
conclusionsBoth the GLM and GAM yielded valid statistical models of MFV in the MCA in healthy subjects. However, the model using the GAM resulted in improved fit indices. The GAM's advantage becomes even clearer when the MFV curves are visualized; yielding a more realistic approach to brain hemodynamics, thus allowing for an improvement in the interpretation of the mathematical and statistical results. Our results demonstrate the utility of the GAM for the analysis and representation of hemodynamic parameters.
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