Overhydration as a modifiable cardio-vascular risk factor in patients undergoing hemodialysis

Introduction: While retrospective studies have shown that poor control of vascular risk factors is associated with progression of white matter hyperintensity (WMH), it has not been studied prospectively. Hypothesis: We hypothesize that higher systolic blood pressure (SBP) mean, LDL cholesterol, and Hgb A1c will be correlated with WMH progression in diabetics. Methods: This is a secondary analysis of the Memory in Diabetes (MIND) substudy of the Action to Control Cardiovascular Risk in Diabetes Follow-on Study (ACCORDION). The primary outcome was WMH progression, evaluated by fitting linear regression models to the WMH volume on the month 80 MRI and adjusting for the WMH volume on the baseline MRI. The primary predictors were the mean values of SBP, LDL, and A1c from baseline to month 80. We defined a good vascular risk factor profile as mean SBP <120 mm Hg and mean LDL <120 mg/dL. Results: We included 292 patients, with a mean (SD) age of 62.6 (5.3) years and 55.8% male. The mean number of SBP, LDL, and A1c measurements per patient was 17, 5, and 12. We identified 86 (29.4%) patients with good vascular risk factor profile. In the linear regression models, mean SBP and LDL were associated with WMH progression and in a second fully adjusted model they both remained associated with WMH progression (Table). Those with a good vascular risk factor profile had less WMH progression (β Coefficient -0.80, 95% CI -1.42, -0.18, p=0.012). Conclusions: Our data reinforce prior research showing that higher SBP and LDL is associated with progression of WMH in diabetics, likely secondary to chronic microvascular ischemia, and suggest that control of these factors may have protective effects. This study has unique strengths, including prospective serial measurement of the exposures, validated algorithmic measurement methodology for WMH, and rigorous adjudication of study data. Clinical trials are needed to investigate the effect of vascular risk factor reduction on WMH progression.

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Abstract 121: Vascular Risk Factor Control in the Year After Ischemic Stroke Versus Myocardial Infarction

Stroke ◽

10.1161/str.46.suppl_1.121 ◽

2015 ◽

Vol 46 (suppl_1) ◽

Author(s):

Dawn M Bravata ◽

Jared Brosch ◽

Jason Sico ◽

Fitsum Baye ◽

Laura Myers ◽

...

Keyword(s):

Myocardial Infarction ◽

Risk Factor ◽

Ischemic Stroke ◽

Standard Deviation ◽

Vascular Risk Factor ◽

Vascular Risk ◽

Hypertension Control ◽

Stroke Patients ◽

Risk Factor Control ◽

Facility Level

Background: The Veterans Health Administration has multiple quality improvement activities directed at improving vascular risk factor control. We sought to examine facility quality of blood pressure (BP) control (<140/90 mm Hg), lipid control (LDL-cholesterol <100 mg/dL) and glycemic control (HbA1c <9%) in the one-year after hospitalization for ischemic stroke or acute myocardial infarction (AMI). Methods: We assembled a retrospective cohort of patients hospitalized with stroke or AMI (fiscal year 2011). Facilities were included if they admitted ≥25 stroke patients and ≥25 AMI patients. A facility-level consolidated measure of vascular risk factor control was calculated for the 3 processes of care (number of passes divided by number of opportunities). Results: A total of 2432 patients had a new stroke and 4873 had a new primary AMI (at 75 facilities). Stroke patients had worse vascular risk factor control than AMI patients (mean facility rate on consolidated measure: stroke, 70% [95%CI 0.68-0.72] vs AMI, 77% [0.75-0.78]). The greatest disparity between stroke and AMI patients was in hypertension control: at 87% of hospitals, fewer stroke patients achieved BP control than AMI patients (mean facility pass rate: stroke, 41% vs AMI, 52%; p<0.0001). Overall there were no statistical differences for stroke versus AMI patients in facility-level hyperlipidemia control (71% vs 73%, p=0.33) and glycemic control (79% versus 82%, p=0.24). AMI patients had more outpatient visits than stroke patients in the year after discharge [AMI: mean 7.9 visits (standard deviation 6.1)]; stroke: mean 6.0 visits (standard deviation 4.5; p<0.0001].); the primary difference in outpatient utilization was additional cardiology visits for AMI patients (2.5 visits with cardiology per AMI patient vs 0.4 visits per stroke patient; p<0.001). Conclusions: These results demonstrated clinically substantial disparities in hypertension control among patients with stroke vs patients with AMI. It may be that cardiologists provided risk factor management to AMI patients that stroke patients did not receive. The etiology of these observed differences merits additional investigation.

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

Neurology ◽

10.1212/wnl.0000000000006360 ◽

2018 ◽

Vol 91 (16) ◽

pp. e1479-e1486 ◽

Cited By ~ 14

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.

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

Stroke ◽

10.1161/str.48.suppl_1.tmp98 ◽

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.

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