Trials and Treatments for Vascular Brain Health: Risk Factor Modification and Cognitive Outcomes

Stroke ◽  
2022 ◽  
Author(s):  
Miia Kivipelto ◽  
Katie Palmer ◽  
Tina D. Hoang ◽  
Kristine Yaffe
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Cognitive Aging ◽  
Digital Health ◽  
Cognitive Stimulation ◽  
Cognitive Outcomes ◽  
Lipid Lowering ◽  
Vascular Risk ◽  
Brain Health ◽  
Cognitive Changes

There is robust evidence linking vascular health to brain health, cognition, and dementia. In this article, we present evidence from trials of vascular risk factor treatment on cognitive outcomes. We summarize findings from randomized controlled trials of antihypertensives, lipid-lowering medications, diabetes treatments (including antidiabetic drugs versus placebo, and intensive versus standard glycemic control), and multidomain interventions (that target several domains simultaneously such as control of vascular and metabolic factors, nutrition, physical activity, and cognitive stimulation etc). We report that evidence on the efficacy of vascular risk reduction interventions is promising, but not yet conclusive, and several methodological limitations hamper interpretation. Evidence mainly comes from high-income countries and, as cognition and dementia have not been the primary outcomes of many trials, evaluation of cognitive changes have often been limited. As the cognitive aging process occurs over decades, it is unclear whether treatment during the late-life window is optimal for dementia prevention, yet older individuals have been the target of most trials thus far. Further, many trials have not been powered to explore interactions with modifiers such as age, race, and apolipoprotein E, even though sub-analyses from some trials indicate that the success of interventions differs depending on patient characteristics. Due to the complex multifactorial etiology of dementia, and variations in risk factors between individuals, multidomain interventions targeting several risk factors and mechanisms are likely to be needed and the long-term sustainability of preventive interventions will require personalized approaches that could be facilitated by digital health tools. This is especially relevant during the coronavirus disease 2019 (COVID-19) pandemic, where intervention strategies will need to be adapted to the new normal, when face-to-face engagement with participants is limited and public health measures may create changes in lifestyle that affect individuals’ vascular risk profiles and subsequent risk of cognitive decline.

Abstract P676: Rates of Preventable Thrombectomy in Acute Ischemic Stroke

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Rakhee Lalla ◽  
Ryan Dunlow ◽  
Karen L Yarbrough ◽  
Prachi Mehndiratta ◽  
Michael S Phipps ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Vascular Disease ◽  
Antiplatelet Agent ◽  
Left Ventricular ◽  
Vascular Risk Factors ◽  
Large Vessel ◽  
Favorable Outcome ◽  
Vascular Risk ◽  
History Of

Introduction: The AHA notes that more than 76% of strokes are the first occurrence. There are class 1 recommendations for the management of common risk factors such as atrial fibrillation (AF), hyperlipidemia (HLD), hypertension (HTN), diabetes (DM), and vascular disease. The purpose of this study is to investigate the percentage of large vessel strokes that are potentially preventable with adequate management of vascular risk factors. Methods: A retrospective chart review was conducted on all patients undergoing endovascular therapy (EVT) from 2012-2019. Data was collected on vascular risk factors present prior to admission including HTN, DM, HLD, AF, and smoking. Preventable stroke was defined as having at least one of the following: untreated AF, untreated HLD, poorly controlled HTN (presence of left ventricular hypertrophy on transthoracic echo), history of vascular disease not on an antiplatelet agent, poorly controlled DM (A1c>10), current smoking. Groups were compared based on age, sex and 90 day functional outcomes, with favorable outcome defined as mRS ≤ 2. Results: Our sample included 396 patients who underwent EVT (mean age 65, 50% female). 42% of patients with Afib were not on anticoagulation, 31% of patients with HLD were untreated, 39% of patients with HTN were poorly controlled, 27% of patients with a history of vascular disease were not on an antiplatelet, 14% of patients with DM were poorly controlled, and 46% of all patients were smokers. In total, 78% of patients had at least 1 poorly controlled risk factor and 37% had at least 2. There was no difference in rates of preventable stroke between males and females (48% vs 52%, p=0.30) and between age groups above and below 70 (40% vs 60%, p=0.68). 64% of patients with well controlled risk factors had a favorable outcome compared to 51% with at least one poorly controlled risk factor (p=0.03). Conclusions: Our data suggests that despite guidelines on management of vascular risk factors, a large number of these are poorly controlled prior to admission for large vessel stroke, leading to a potentially preventable procedure. Not only could improved primary prevention save the wide array of resources utilized in EVT, but it could also influence long term outcomes in this cohort of patients.

scholarly journals Fusidic Acid: A Neglected Risk Factor for Statin-Associated Myopathy

2018 ◽  
Vol 12 ◽  
pp. 117954681881516 ◽  
Author(s):  
Josefine Rönnqvist ◽  
Pär Hallberg ◽  
Qun-Ying Yue ◽  
Mia Wadelius
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Risk Factor ◽  
Fusidic Acid ◽  
Case Reports ◽  
Statistical Significance ◽  
Lipid Lowering ◽  
Concomitant Treatment ◽  
Swedish Medical ◽  
Statin Dose

Background: Statins are widely used lipid-lowering drugs used for the prevention of cardiovascular disease. Statins are known to cause myopathy, an adverse drug reaction with various clinical features rhabdomyolysis. Objective: To describe clinical characteristics of statin-treated individuals who experienced myopathy and identify risk factors of statin-associated myopathy. Methods: A retrospective study was conducted on cases of statin-associated myopathy reported to the Swedish Medical Products Agency. Clinical factors were compared between cases and statin-treated controls not diagnosed with myopathy. Statistical methods were univariate and multivariate logistic regression and results were presented as odds ratio (OR) with 95% confidence interval (CI). To correct for multiple comparisons, the cutoff for statistical significance was set to P < .0017. Results: In total, 47 cases of statin-associated myopathy were compared with 3871 treated controls. Rhabdomyolysis was diagnosed in 51% of the cases. Markers for cardiovascular disease were more common in cases than controls. Statistical analysis revealed the following independent risk factors for myopathy: high statin dose (OR = 1.54, calculated using the standard deviation 19.82, 95% CI = 1.32-1.80, P < .0001), and concomitant treatment with fusidic acid (OR = 1002, 95% CI = 54.55-18 410, P < .0001), cyclosporine (OR = 34.10, 95% CI = 4.43-262.45, P = .0007), and gemfibrozil (OR = 12.35, 95% CI = 2.38-64.10, P = .0028). Conclusions: The risk of myopathy increases with statin dose and cotreatment with cyclosporine and gemfibrozil. Concomitant fusidic acid has previously only been noted in a few case reports. Considering that use of fusidic acid may become more frequent, it is important to remind of this risk factor for statin-associated myopathy.

Vascular risk factors and cognitive aging: The Maastricht aging study

2000 ◽  
Vol 21 ◽  
pp. 230
Author(s):  
Jellemer Jolles ◽  
Martin P.J. Van Boxtel ◽  
Hans Bosma
Keyword(s):  
Risk Factors ◽  
Cognitive Aging ◽  
Vascular Risk Factors ◽  
Vascular Risk ◽  
Aging Study

scholarly journals Vascular risk at younger ages most strongly associates with current and future brain volume

Neurology ◽  
2018 ◽  
Vol 91 (16) ◽  
pp. e1479-e1486 ◽  
Author(s):  
Matthew P. Pase ◽  
Kendra Davis-Plourde ◽  
Jayandra J. Himali ◽  
Claudia L. Satizabal ◽  
Hugo Aparicio ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Stroke Risk ◽  
Brain Volume ◽  
Vascular Risk Factor ◽  
Vascular Risk Factors ◽  
Vascular Risk ◽  
Cross Sectional ◽  
Strength Of Association ◽  
Risk Factor Burden

ObjectiveGiven the potential therapeutic effect of vascular disease control timing to reduce dementia risk, we investigated the age-related influences of vascular risk factor burden on brain structure throughout the lifespan.MethodsWe studied participants from the community-based prospective Framingham Heart Study. Overall vascular risk factor burden was calculated according to the Framingham Stroke Risk Profile, a validated algorithm that predicts stroke risk. Brain volume was estimated by MRI. We used cross-sectional data to examine how the strength of association between vascular risk factor burden and brain volume changed across each age decade from age 45–54 years through to 85–94 years (N = 2,887). Second, we leveraged up to 40 years of longitudinal data to determine how the strength of association between vascular risk factor burden and brain volume changed when vascular risk factors were examined at progressively earlier ages (N = 7,868).ResultsIn both cross-sectional and longitudinal analyses, higher vascular risk factor burden was associated with lower brain volume across each age decade. In the cross-sectional analysis, the strength of this association decreased with each decade of advancing age (p for trend < 0.0001). In longitudinal analysis, the strength of association between vascular risk factor burden and brain volume was stronger when vascular risk factors were measured at younger ages. For example, vascular risk factor burden was most strongly associated with lower brain volume in later life when vascular risk factors were measured at age 45 years.ConclusionVascular risk factors at younger ages appear to have detrimental effects on current and future brain volume.

Abstract P127: Racial Disparities in Risk Factor Control in Older Adults with Diabetes: The Atherosclerosis Risk in Communities (ARIC) Study

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Christina Parrinello ◽  
Ina Rastegar ◽  
Job G Godino ◽  
Michael D Miedema ◽  
Kunihiro Matsushita ◽  
...  
Keyword(s):  
Risk Factors ◽  
Older Adults ◽  
Risk Factor ◽  
Racial Disparities ◽  
Low Density Lipoprotein ◽  
Density Lipoprotein ◽  
Lipid Lowering ◽  
Tight Control ◽  
Risk Factor Control ◽  
Atherosclerosis Risk In Communities

Background: Racial disparities in risk factor control have been documented in middle-aged adults, but much less is known about older adults with diabetes. Our findings will inform clinical guidelines on appropriate risk factor control in older adults with diabetes. Methods: In 2011-13, 6,538 ARIC participants attended visit 5, and 4,988 provided data on all key covariates used in these analyses. Of these, 31% had diagnosed diabetes (N=1,561, 72% white, mean age=75 years) and were included in this study. Tight control of risk factors was defined according to American Diabetes Association guidelines: hemoglobin A1c <7%; low-density lipoprotein cholesterol <100 mg/dL; systolic blood pressure (BP) <140 mmHg and diastolic BP <80 mmHg. We evaluated risk factor control overall and by race. We used logistic regression and predictive margins to assess independent associations of race with tight risk factor control. Results: Among older adults with diabetes, 64% used glucose-lowering medication, 70% lipid-lowering medication and 82% BP-lowering medication. Only 5% of participants did not take medication for any of these risk factors. Tight control was observed in 72% for glucose, 64% for lipids and 70% for BP. Only 34% had tight control of all three. A higher proportion of whites than blacks consistently achieved tight control ( Figure ). In multivariable analyses of persons with diabetes who were treated for risk factors, racial disparities in tight control of lipids and BP remained significant: adjusted prevalence ratios and 95% CIs (white vs black) were 1.04 (0.91, 1.17) for glucose, 1.21 (1.08-1.34) for lipids, 1.15 (1.03-1.26) for BP, and 1.33 (0.95, 1.70) for tight control of all three risk factors. Conclusions: Our results highlight racial disparities in risk factor control in older adults with diabetes that were not explained by demographic or clinical characteristics. Further studies are needed to elucidate the determinants of disparities in risk factor control and strategies to address these.

Abstract TMP98: Could Mobile Health be an Effective Strategy for Enhancing Stroke Prevention?

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Shimeng Liu ◽  
Wuwei Feng ◽  
Pratik Y Chhatbar ◽  
Bruce I Ovbiagele
Keyword(s):  
Risk Factors ◽  
Smoking Cessation ◽  
Risk Factor ◽  
Glycemic Control ◽  
Mobile Health ◽  
Meta Analysis ◽  
Vascular Risk Factor ◽  
Smoking Abstinence ◽  
Vascular Risk ◽  
Risk Factor Control

Background: The overwhelming majority of strokes can be prevented via optimal vascular risk factor control. However, there remains an evidence practice gap with regard to treatment of vascular risk factors. With the rapid growth worldwide in cell-phone use, Internet connectivity, and digital health technology, mobile health (mHealth) technology may offer a promising approach to bridge these treatment gaps and reduce the global burden of stroke. Objective: To evaluate the effectiveness of mHealth in vascular risk factor control through a systemic review and meta-analysis. Methods: We searched PubMed from January 1, 2000 to May 17, 2016 using keywords: mobile health, mhealth, short message, cellular phone, mobile phone, stroke prevention and control, diabetes mellitus, hypertension, hyperlipidemia and smoking cessation. We performed a meta-analysis of all eligible randomized control clinical trials that assessed the long-term (at 6 months) effect of mHealth. Results: Of 79 articles identified, 13 of them met eligibility criteria (6 for glycemic control and 7 for smoking cessation) and were included for the final meta-analysis. There were no eligible studies for dyslipidemia or hypertension. mHealth resulted in greater HbA1c reduction at 6 months (6 studies; 663 subjects; SMD: -0.44; 95% CI: [-0.82, -0.06], P =0.02; Mean difference of decrease in HbA1c: -0.39%; 95% CI: [-0.74,-0.04], P =0.03). mHealth also led to relatively higher smoking abstinence rates at 6 months (7 studies; 9,514 subjects; OR: 1.54; 95% CI: [1.24, 1.90], P <0.0001). Conclusion: Use of mHealth improves glycemic control and smoking abstinence rates, two factors that may lead to better stroke outcomes. Future mHealth studies should focus on modifying premier vascular risk factors like hypertension, specifically in people with or at risk of stroke.

scholarly journals The comparison of traditional vascular risk factor between hemorrhagic and non-hemorrhagic stroke

2017 ◽  
Vol 8 (6) ◽  
pp. 5-8
Author(s):  
Rizaldy Taslim Pinzon ◽  
Rosa De Lima Renita Sanyasi ◽  
Andre Dharmawan Wijono
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Protective Factor ◽  
Hemorrhagic Stroke ◽  
Sample Size Calculation ◽  
Vascular Risk Factor ◽  
Vascular Risk Factors ◽  
Vascular Risk ◽  
Significance Level ◽  
Stroke Registry

Background: Understanding about risk factors of stroke based on its pathology is very important. Previous study about the vascular risk factors in patients with stroke in Indonesia is very limited.Aims and Objective: Measure the comparison between traditional vascular risk factors in patients with hemorrhagic stroke and non-hemorrhagic (ischemic) stroke.Materials and Methods: This was a nested case-control study using secondary data from electronic medical record and electronic stroke registry of Bethesda Hospital Yogyakarta Indonesia. The stroke was diagnosed with standard way by well-trained neurologist and confirmed with CT Scan. The traditional risk factors were defined systematically. We used Dupont Power and Sample Size calculation software and StatCal EpiInfo software with significance level 0,05.Result: The data of 200 subjects consisted of 100 patients with hemorrhagic stroke and 100 patients with non-hemorrhagic stroke. Hypertension was main vascular risk factor in both Group but it was more common in hemorrhagic stroke (OR: 2,528, 95% CI: 0,069 ; 0,316, p < 0,002). Dyslipidemia was a protective factor against hemorrhagic stroke (OR: 0,147, 95% CI: 1,415 ; 4,516, p < 0,001). Diabetes was more common in ischemic stroke compared with hemorrhagic stroke (68% and 32%) respectively.Conclusion: Hypertension, dyslipidemia, and diabetes were modifiable traditional vascular risk factors which significantly had effect on stroke. Asian Journal of Medical Sciences Vol.8(6) 2017 5-8

scholarly journals Predictors for carotid and femoral artery intima-media thickness in a non-diabetic sleep clinic cohort

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252569
Author(s):  
Christopher Lambeth ◽  
Rita Perri ◽  
Sharon Lee ◽  
Manisha Verma ◽  
Nicole Campbell-Rogers ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Intervention Study ◽  
Intima Media Thickness ◽  
Vascular Risk Factor ◽  
Vascular Risk Factors ◽  
Vascular Risk ◽  
Link Type ◽  
Media Thickness ◽  
Continuous Positive Pressure

Introduction The impact of sleep disordered breathing (SDB) on arterial intima-media thickness (IMT), a surrogate measure for cardiovascular disease, remains uncertain, in part because of the potential for non-SDB vascular risk factor interactions. In the present study, we determined predictors for common carotid (CCA) and femoral (CFA) artery IMT in an adult, sleep clinic cohort where non-SDB vascular risk factors (particularly diabetes) were eliminated or controlled. Methods We recruited 296 participants for polysomnography (standard SDB severity metrics) and CCA/CFA ultrasound examinations, followed by a 12 month vascular risk factor minimisation (RFM) and continuous positive pressure (CPAP) intervention for participants with a range of SDB severity (RFM Sub-Group, n = 157; apnea hyponea index [AHI]: 14.7 (7.2–33.2), median [IQR]). Univariable and multivariable linear regression models determined independent predictors for IMT. Linear mixed effects modelling determined independent predictors for IMT change across the intervention study. P<0.05 was considered significant. Results Age, systolic blood pressure and waist:hip ratio were identified as non-SDB predictive factors for CCA IMT and age, weight and total cholesterol:HDL ratio for CFA IMT. No SDB severity metric emerged as an independent predictor for either CCA or CFA IMT, except in the RFM Sub-Group, where a 2-fold increase in AHI predicted a 2.4% increase in CFA IMT. Across the intervention study, CCA IMT decreased in those who lost weight, but there was no CPAP use interaction. CFA IMT, however, decreased by 12.9% (95%CI 6.8, 18.7%, p = 0.001) in those participants who both lost weight and used CPAP > = 4hours/night. Conclusion We conclude that SDB severity has little impact on CCA IMT values when non-SDB vascular risk factors are minimised or not present. This is the first study, however, to suggest a potential linkage between SDB severity and CFA IMT values. Trial registration Australian New Zealand Clinical Trials Registry, ACTRN12611000250932 and ACTRN12620000694910.

scholarly journals Multimodal Brain Age Gap as a Mediating Indicator in the Relation between Modifiable Dementia Risk Factors and Cognitive Functioning

2020 ◽  
Author(s):  
Chang-Le Chen ◽  
Pin-Yu Chen ◽  
Yu-Hung Tung ◽  
Yung-Chin Hsu ◽  
Wen-Yih Isaac Tseng
Keyword(s):  
Risk Factors ◽  
Cognitive Decline ◽  
Cognitive Aging ◽  
Prediction Models ◽  
Equation Modeling ◽  
Pathophysiological Mechanism ◽  
Cognitive Changes ◽  
Age Gap ◽  
Dementia Risk ◽  
Brain Age

AbstractIntroductionAs a structural proxy for evaluating brain health, neuroimaging-based brain age gap (BAG) is presumed to link the dementia risks to cognitive changes in the premorbid phase, but this remains unclear.MethodsBrain age prediction models were constructed and applied to a population-based cohort (N=371) to estimate their BAG. Further, structural equation modeling was employed to investigate the mediation effect of BAG between risk levels (assessed by 2 dementia-related risk scores) and cognitive changes (examined by 4 cognitive assessments).ResultsA higher burden of modifiable dementia risk factors was causally associated with a greater cognitive decline, and this was significantly mediated (P=0.017) by a larger multimodal BAG, which indicated an older brain. Moreover, a steeper slope (P=0.020) of association between cognitive decline and multimodal BAG was observed when individuals had higher dementia risks.DiscussionMultimodal BAG is a potential mediating indicator to reflect the changes in the pathophysiological mechanism of cognitive aging.

scholarly journals Risk factor profile of different clinical manifestations of cerebral small vessel disease - data from SHEF-CSVD Study

2017 ◽  
Author(s):  
J. Staszewski ◽  
E. Skrobowska ◽  
R. Piusińska-Macoch ◽  
B. Brodacki ◽  
A. Stępień
Keyword(s):  
Risk Factors ◽  
Uric Acid ◽  
Risk Factor ◽  
Cerebrovascular Disease ◽  
Fasting Glucose ◽  
Small Vessel Disease ◽  
Clinical Manifestations ◽  
Cerebral Small Vessel Disease ◽  
Vascular Risk ◽  
Vessel Disease

AbstractBACKGROUNDLittle is known of the mechanisms of cerebral small vessel disease (CSVD). Both atherosclerosis or non-atherosclerotic diffuse arteriopathy are involved.METHODSA single-center, prospective, case-control study was performed in consecutive patients with different CSVD manifestations. The study group consisted of 205 patients: 52 with lacunar stroke (LS), 20 with subcortical hemorrhagic stroke (HS), 50 with vascular dementia (VaD), 28 with vascular parkinsonism (VaP) and 55 controls (CG) free of cerebrovascular disease but with high vascular risk.RESULTSPatients with CSVD had significantly higher prevalence of vascular risk factors including hypertension, diabetes mellitus, polymetabolic syndrome and chronic kidney disease. Patients with CSVD had also significantly higher fasting blood glucose, homocysteine, fibrinogen, systolic blood pressure, IMT values and lower eGFR, albumin and HDL levels. After adjustment for age and sex, low eGFR, albumin and high levels of uric acid and fibrinogen were associated with all CSVD groups, elevated fasting glucose was related to LS and HS. In the multivariate analysiss, the independent predictors for CSVD were female sex, low albumin, high fibrinogen, fasting glucose and uric acid. Patients with LS had significantly higher IMT values comparing to other CSVD groups, patients with VaP had a trend towards higher homocysteine levels.CONCLUSIONRisk factor profile for CSVD as a whole differs from subjects with proatherogenic profile without history of cerebrovascular disease. Our results support the concept that CSVD is not homogeneous, and that unique risk factors profiles exist for different clinical manifestations of the disease.

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