Hypertension in midlife is an independent risk factor of late life cognitive dysfunction or dementia. Chronic hypertension cause vascular damage and cerebral ischemia, which ultimately gives rise to the cognitive dysfunction or dementia. A recent study showed that high visit-to-visit variability in clinic systolic blood pressure (BP) was a strong independent predictor of stroke. This finding suggests that high clinic systolic BP variability itself as well as chronic hypertension may cause vascular damage and cerebral ischemia. Therefore, high clinic SBP variability may be also an independent risk factor of cognitive dysfunction or dementia. Vascular damage leads to the diminished autoregulatory capacities of cerebral arteries. The brain with the reduced autoregulatory capacity may be more vulnerable to BP fluctuation. Therefore, high BP variability may be more harmful in patients with damaged vessels (for example, in patients with cerebral small vessel disease). Previous data about BP variability and cognition revealed very controversial. Some studies showed poor cognition in patients with high BP variability, but others did not. The previous studies were mostly based on cross-sectional designs, and performed in small-sized heterogeneous population for primary prevention. The harmful effect of high BP variability may be clearer in the population with damaged vascular bed, such as cerebral small vessel disease. The previous studies usually used ambulatory BP monitoring (ABPM). However, recent data suggested that variability in BP on ABPM may be a weaker predictor of vascular events than be visit-to-visit variability in clinic BP. The investigators sought to find whether high visit-to-visit variability in clinic BP is related with poor cognitive function in patients with cerebral small vessel disease.
This is a retrospective cohort study. We include patients with cerebral small vessel disease, documented on MRI from Jan 2006 to Dec 2010, who have been regularly followed up. We evaluate the patients' cognitive function after written informed consent. We independently review patients' medical record and analyze MRI data. BP variability parameters include standard deviation(SD, primary measuring parameter), coefficient of variation, successive variation, average real variability (ARV), SD independent of mean(SDIM), SV independent of mean(SVIM), and ARV independent of mean (ARVIM). We will adjust following confounding variables: age, sex, level of education, vascular risk factors, mean SBP and DBP, NIHSS score, and white matter lesion burden on T2-weighted MRI.
Study Type
OBSERVATIONAL
Enrollment
140
Chuncheon Sacred Heart Hospital, Hallym University, College of Medicine
Chuncheon, Gangwon-do, South Korea
RECRUITINGHallym University Sacred Heart Hospital, Hallym University, College of Medicine
Anyang-si, Gyeonggi-do, South Korea
RECRUITINGGangdong Sacred Heart Hospital, Hallym University, College of Medicine
Seoul, South Korea
RECRUITINGHangang Sacred Heart Hospital, Hallym University, College of Medicine
Seoul, South Korea
RECRUITINGGangnam Sacred Heart Hospital, Hallym University, College of Medicine
Seoul, South Korea
RECRUITINGAssociation between raw score of K-MMSE and visit-to-visit systolic BP variability
Difference of mean K-MMSE raw scores between the highest and the lowest tertile group stratified by visit-to-visit systolic BP variability: Wilcoxon\_Mann\_Whitney test Binary logistic regression analysis for independent association between visit-to-visit systolic BP variability and low cognition, including confounding variables with p\<0.2 in univariate analysis (Low cognition, defined as the lowest tertile of K-MMSE raw score)
Time frame: Time from previous MRI documentation as small vessel disease to cognitive function evaluation; 1.5 to 7 years
Association between raw score of K-MMSE and visit-to-visit diastolic BP variability
Difference of mean K-MMSE raw scores between the highest and the lowest tertile group stratified by visit-to-visit diastolic BP variability: Wilcoxon\_Mann\_Whitney test Binary logistic regression analysis for independent association between visit-to-visit diastolic BP variability and low cognition, including confounding variables with p\<0.2 in univariate analysis (Low cognition, defined as the lowest tertile of K-MMSE raw score)
Time frame: Time from previous MRI documentation as small vessel disease to cognitive function evaluation; 1.5 to 7 years
Association between raw scores of "K-VCI NP 30-minute protocol" sub-tests and visit-to-visit systolic BP variability
Difference of mean "K-VCI NP 30-minute protocol" sub-tests' raw scores between the highest and the lowest tertile group stratified by visit-to-visit systolic BP variability: Wilcoxon\_Mann\_Whitney test Binary logistic regression analysis for independent association between visit-to-visit systolic BP variability and low cognition, including confounding variables with p\<0.2 in univariate analysis (Low cognition, defined as the lowest tertile of each "K-VCI NP 30-minute protocol" sub-test) "K-VCIHS NP 30-minute protocol" include Seoul Verbal Learning Test (SVLT), Semantic Fluency Test, Animal Phonemic Fluency Test, Digit Symbol-Coding (DSC), Geriatric Depression Scale (GDS), and Trail Making Test A \& B.
Time frame: Time from previous MRI documentation as small vessel disease to cognitive function evaluation; 1.5 to 7 years
Association between raw scores of "K-VCI NP 30-minute protocol" sub-tests and visit-to-visit diastolic BP variability
Difference of mean "K-VCI NP 30-minute protocol" sub-tests' raw scores between the highest and the lowest tertile group stratified by visit-to-visit diastolic BP variability: Wilcoxon\_Mann\_Whitney test Binary logistic regression analysis for independent association between visit-to-visit diastolic BP variability and low cognition, including confounding variables with p\<0.2 in univariate analysis (Low cognition, defined as the lowest tertile of each "K-VCI NP 30-minute protocol" sub-test)
Time frame: Time from previous MRI documentation as small vessel disease to cognitive function evaluation; 1.5 to 7 years
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