11 research outputs found

    Regression models.

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    a.<p>ref.: reference group.</p>b.<p>LRT: likelihood ratio test, for testing the non-linear the association between age and dependent variables.</p

    The Changes of Cerebral Morphology Related to Aging in Taiwanese Population

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    <div><p>A cross-sectional study with the 3-dimensional (3D) MRI reconstruction technique was conducted to investigate cerebral complexity changes related to age differences in native Taiwanese population. In our sample of 85 participants aged between 25 and 81, age was associated with gradual ventricular expansion. A nonlinear quadratic relationship between white matter volume and age was found overall in the brain. Widespread age-related reduction in white matter was detected from late adulthood onwards. However, no significant age-related changes in the cortex and whole brain volume were determined throughout adulthood. These findings provided information in describing brain structural complexity, which might in the future serve as an objective diagnostic index or as a predictive parameter for neurological diseases. Our method then may be used for cross-cultural longitudinal studies to evaluate the effect of disease, environment and aging on the brain.</p> </div

    The relationship between age and average ventricle volume.

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    <p>The volume of ventricle β€Š=β€Š0.013Γ— age<sup>2</sup>βˆ’0.74Γ— age+7.23Γ— sex+31.4; male β€Š=β€Š1, female β€Š=β€Š0.</p

    The relationship between age and average white matter volume.

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    <p>The volume of white matter β€Š=β€Šβˆ’0.09Γ— age<sup>2</sup>+9.85Γ— age+41.76Γ— sex+152.56; male β€Š=β€Š1, female β€Š=β€Š0.</p

    The relationship between age and average whole brain volume.

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    <p>The whole brain volume β€Š=β€Š1008.13+146.08Γ— sex; male β€Š=β€Š1, female β€Š=β€Š0.</p

    Hazard ratio of overall risk associated different dosage level of ALN use.

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    <p>Adjusted for sex, age, hypertension.</p><p>N: case numbers.</p>†<p>per 1000 person-years.</p>*<p>p<0.05, ** p<0.01, *** p<0.001.</p

    Baseline characteristics between ALN group and non-ALN group in 1998–2009.

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    a<p>Government, education, and military.</p>b<p>Insured income is lower than the level required for charging premium.</p><p>Chi-square test.</p
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