Framingham Stroke Risk Score Research Articles

Serum NfL (Neurofilament Light Chain) Levels and Incident Stroke in Adults With Diabetes Mellitus.

Background and Purpose- Effective stroke prevention depends on accurate stroke risk prediction. We determined the discriminative ability of NfL (neurofilament light chain) levels for distinguishing between adults with diabetes mellitus who develop incident stroke and those who remain stroke free during a 7-year follow-up period. Methods- We performed a case-control study of participants selected from the previously completed ACCORD trial (Action to Control Cardiovascular Risk in Diabetes). Cases were all ACCORD subjects who were stroke free at enrollment and developed incident stroke during follow-up (n=113). Control subjects (n=250) were randomly selected ACCORD subjects who had no stroke events either before or after randomization. NfL was measured in baseline samples using Single Molecule Array technology (Quanterix). Results- Baseline NfL levels were higher in stroke subjects, compared to controls, after adjusting for age, race, blood pressure, weight, and the Framingham Stroke Risk Score. Relative to the subjects in the lowest quintile of NfL levels, the hazard ratios of incident stroke for subjects in the second to fifth quintiles were 3.91 (1.45-10.53), 4.05 (1.52-10.79), 5.63 (2.16-14.66), and 9.75 (3.84-27.71), respectively, after adjusting for race and Framingham Stroke Risk Score. Incorporating NfL levels into a predictive score that already included race and Framingham Stroke Risk Score increased the score's C statistic from 0.71 (95% CI, 0.66-0.77) to 0.78 (95% CI, 0.73-0.83), P<0.001. Older age, nonwhite race, higher systolic blood pressure, glomerular filtration rate <60, and higher hemoglobin A1C were independent predictors of serum NfL in this cohort but diastolic blood pressure, durations of hypertension or diabetes mellitus, and lipid levels were not. In total, cardiovascular disease risk factors explained 19.2% of the variability in baseline NfL levels. Conclusions- Serum NfL levels predict incident stroke and add considerably to the discriminatory power of the Framingham Stroke Risk Score in a cohort of middle-aged and older adults with diabetes mellitus.

Abstract WP480: Stroke Risk Among Post-menopausal Breast-cancer Survivors

Background and Purpose: Cancer is a well-known risk factor for stroke, yet whether the stroke comorbid with a cancer or the risk further increases along with a long-term survivorship is unclear. Also, whether the stage of cancer and receiving hormonal therapy affect stroke risk particularly in post-menopausal breast cancer survivors (BCS) is yet to be determined. This study aimed to (1) identify comorbid stroke risks at the time of the cancer diagnosis; (2) examine the changes of stroke risk at one, five and ten years after survival; and (3) explore relationships between demographic and cancer-related factors and stroke risks among BCS. Methods: We retrieved 4,152 deidentified BCS data from a Massey Cancer Registry. After excluding 39 pre-existing stroke and selecting who met the Framingham Stroke Risk Score (FSRS) criteria, we included 2141 (mean age of 64.22; SD=7.30 years). Among them, 616 who had all components for the FSRS equation (age, sex, systolic blood pressure, presence of cardiovascular disease, left ventricular hypertrophy, smoking, atrial fibrillation, and presence of diabetes) were included in this analysis. Results: We found that (1) comorbid stroke risk at the time of the diagnosis was 10.6 in terms of the FSRS; among individual risk factors, elevated systolic blood pressure (SBP&gt;140mmHg, 43.3 %) was prominent followed by the presence of cardiovascular disease markers (39.56%) and diabetes (23.11%). (2) The FSRS consistently increased overtime with the largest increase during the first year of survival (10.60 at baseline vs. 16.07, 17.27. and 17.76 at year 1, 5, and 10, respectively). (3) The FSRS was significantly higher in Non-Hispanic Black than Non-Hispanic White (12.55 vs. 9.25, p=0.016 ) across time. Those who received hormonal therapy showed higher FSRS than those who did not (15.88 vs. 8.17, p=0.000 ); tumor stage was not associated with the FSRS. Conclusion: Stroke risk consistently increase along with the survivorship of a breast cancer, particularly among women after their menopause. Prevention and control of high blood pressure and diabetes should be a target of intervention to reduce the stroke risk among post-menopausal breast cancer survivors.

Abstract WP520: The Role of Neighborhood Deprivation in Stroke Risk in Two Countries: France and the United States

Background and Aims: The role of socioeconomic status in stroke has been difficult to study due to differences at both the individual and neighborhood level. We therefore sought to examine the role of neighborhood socioeconomic status on risk of stroke in two countries: the United States (US) and France. Methods: We used the REasons for Geographic and Racial Differences in Stroke (REGARDS) study in the US and the 3-City (3C) study in France. In both studies, we used a factor analysis to combine various socioeconomic indicators collected by the governments of the two countries (in France IRIS and in the US the census) into a score indicating the level of neighborhood disadvantage. We limited the analysis to those free from stroke at baseline and used combined outcome of ischemic or hemorrhagic stroke. Cox models were used to model the association between neighborhood deprivation and risk of stroke; all models were adjusted for components of the Framingham Stroke Risk Score (REGARDS also adjusted for race), dietary pattern, individual income and education. Results: There were 802 strokes in REGARDS in 17996 participants and 326 strokes in 3C in 7647 participants. In both studies neighborhood deprivation was associated with lower individual income and educational attainment as well as higher BMI and systolic blood pressure. Only in the REGARDS study was neighborhood deprivation associated with greater risk of stroke. In REGARDS, comparing the 5 th quintile to the 1 st quintile the hazard ratio (HR) and 95% CI was 1.36 (1.09, 1.72). In the 3C study comparing the 5 th quintile to the 1 st quintile, the HR (95% CI) was 1.04 (0.73, 1.47). Conclusion: In the REGARDS study neighborhood deprivation was associated with risk of stroke but these findings were not seen in the 3C study. Future work to further evaluate the role of diet and individual socio-economic status in mediating the findings observed in France could help to better explain the differences in these two studies.

Chronic kidney disease is linked to carotid calcified atherosclerotic plaque in patients with metabolic syndrome

Background The prevalence of metabolic syndrome (MetS) is rising continuously. MetS is recently proposed as a predictor for the occurrence of vascular defects causing stroke. Objective Carotid atherosclerosis is a major cause of disabling stroke and death. The presence of carotid plaques is associated with future cardiovascular (CV) events, with local plaque composition being an independent outcome predictor. We examined the association between ultrasonographically determined carotid plaque calcification and CV risk factors in MetS. Methods This was a cross-sectional study with a total of 58 patients with MetS who underwent routine carotid ultrasonography of both carotid arteries to detect presence of calcified atherosclerotic plaque. Plaques with high echogenic nodules and posterior shadowing were considered calcified. Those who had no apparent cardiovascular vascular disease (CVD). After careful clinical examinations and biochemical evaluations. We used logistic regression models to assess the relationship between CV risk factors and carotid plaque calcification in studied subjects. Results Of this study subjects, the mean age was 63.8 ± 7.8 years. Carotid calcification was detected in 19.3% of the patients. We found that presence of carotid plaque calcification had statistically significantly positive correlations with the prevalence of autonomic dysfunction (p = 0.03), CKD (p = 0.001), framingham stroke risk score (FSRS) (p = 0.005), mean arterial pressure (MAP) (p = 0.05), and log creatinine (log cre) (p = 0.02), and negative correlations with log estimated Glomerular filtration rate (log eGFR) (p = -0.01). Results of logistic regression analysis showed that prevalence of CKD (p = 0.02) was significantly associated with carotid plaque calcification after adjustment of confounding risk factors. Conclusions Our results suggest that carotid plaque calcification presence significantly related to CKD.

Abstract 107: Differential Ischemic Stroke Risk Among Women Veterans Across Age Strata

Background: Ischemic stroke disproportionately affects women. Women have a higher lifetime risk of stroke, experience worse functional recovery post-stroke, and are more likely to be institutionalized after stroke than men. Despite the pronounced differences in which stroke may affect women compared to men, stroke research specifically focusing on women has not been published until recently. For instance, stroke specific guidelines for women were not published until 2014. This study sought to determine whether differences in stroke risk exist between women and men across age strata using the Framingham Stroke Risk (FRS) score in a large cohort of Veterans. Methods: Study participants were Veterans receiving care within Veterans Health Administration facilities between April 2011 and May 2012 (N=57,072). In this secondary analysis, patients were excluded (n=39,978) based on age less than 55 years and prior history of stroke. FRS was calculated for each patient based on race- and sex-specific pooled cohort equations that accounted for age, atrial fibrillation, systolic blood pressure, diabetes mellitus, cigarette smoking, prior cardiovascular disease, and antihypertensive medication use. FRS scores ≥15% were classified as high risk for stroke. SAS Version 9.1 statistical software was used to calculate FRS, perform chi-square analysis, and perform logistic regression analysis. Results: Among 39,978 eligible patients, the mean age (standard deviation [SD]) was 71.6 ± 10.1 years with 1,842 (4.6%) patients within the cohort being women. The mean FRS score for women was 11.29 (± 4.29 SD) and was 14.52 (± 4.37 SD) for men. Risk factors for stroke including age, atrial fibrillation, systolic blood pressure, diabetes mellitus, and antihypertensive use were significant predictors of women’s high 10-year risk of stroke in unadjusted OR unadjusted analyses? ( P =&lt;.0001). When stratified into groups of high 10-year risk of stroke, this study found that nearly half (47.9%) of all Veterans were high-risk for stroke. Women 55-73 years old had a lower risk of future stroke than men of the same age; however, women Veterans 71 years and older had a higher risk of future stroke than similarly aged men ( P &lt;0.001). Conclusions: Nearly half of all women Veterans were found to be at high risk of ischemic stroke within the next 10-years. Furthermore, sex differences were noted across age strata, with women having a lower risk of stroke then men at younger ages and a higher risk at older ages. Given that women tend to have more severe strokes, higher mortality, and delayed diagnosis compared to men, further work is required to understand reasons for the differential stroke risk across sexes. Based on these study findings, implementing primary prevention programs for women Veterans would help to mitigate future ischemic stroke risk.

Abstract WMP88: Comparing Behavioral Principles in Mailed Messages to Activate Patients at High Risk for Stroke

Objectives: To compare the effect of behaviorally-tailored mailed messages on patient activation to reduce stroke risk. Methods: We used EHR data to construct Framingham Stroke Risk Scores (FSRS) in primary care patients in one VA and one non-VA urban healthcare system. Patients in the highest risk quintile were eligible. We recruited 15 subjects to develop four stroke risk messages: standard, incentive ($5 gift card), salience, and incentive plus salience. Patients were randomly assigned to receive one of the messages. All letters asked the patient to call a stroke prevention coordinator. Response to the messages (calling the prevention coordinator) was modeled separately in the two healthcare system cohorts using logistic regression. Results: From 6,695 eligibles, 1,759 Veterans (mean age 75.6, 99% male, 61% White, mean FSRS 18.6) and 2,084 non-Veterans (mean age 65.6, 36% male, 68% Black, mean FSRS 13.1) received a letter. Overall call response rate was 23% among Veterans and 13% among non-Veterans. Both cohorts were significantly more likely to respond to the incentive and to the incentive plus salience message compared to the standard message (Table). Older age (for Veterans) and Black race (for non-Veterans) were also significantly associated with response, but FSRS and medical comorbidity were not. Among 631 subjects calling the stroke prevention coordinator, 26% (100/390) of Veterans and 30% (73/241) of non-Veterans were unaware of their risk factors. Conclusions: A mailed letter including a small monetary incentive may be more effective than standard or salience-related messages in engaging high-risk patients with their health care system. Many patients are unaware of their stroke risk. Future analyses will examine the relationship between messages and primary care follow-up.

Abstract TMP56: Comparison of Incident Stroke in Veterans and Non-Veterans in a National Cohort

Introduction: Veterans represent a unique population who may be at higher risk of stroke. However, the association between veteran status and stroke remains poorly defined. Methods: Veteran status was determined among 12,932 participants in the REasons for Geographic and Racial Differences in Stroke Study, a national population-based cohort. Demographics, socioeconomic (SE) factors, and vascular risk factors including Framingham Stroke Risk Score (FSRS) were compared between veterans and non-veterans. Veterans were further characterized as enlisted or commissioned officers. Hazard ratios for incident stroke were calculated for male and female veterans. Results: In this cohort, 3,405 veterans were identified. After adjusting for age, race, geographic region, income, and education, there were no substantial differences in vascular risk factors and FSRS between veterans and non-veterans other than a higher proportion of current smokers in male veterans (particularly enlisted) than non-veterans. Among those free of stroke at baseline, male veterans were at similar risk for incident stroke compared to non-veterans (Figure 1a), even with adjustment for age, race, SE factors, and vascular risk factors (HR 1.10, 95% CI 0.82-1.47). Female veterans were at an increased risk for incident stroke (Figure 1b, HR 2.30, 95% CI 1.21-4.34), although this difference was not significant when adjusted for SE and vascular risk factors. Risk for incident stroke was similar between enlisted and commissioned officers (Figure 1c,d). Conclusions: This is the one of the first studies to examine incident stroke among veterans and is not limited to those seeking care within the Veterans Health Administration. From this national cohort, military exposure did not increase the risk of incident stroke among males. Female veterans seem to be at a higher risk for incident stroke; however, this association was primarily driven by differences in vascular risk factors compared to non-veterans.

Revised Framingham Stroke Risk Score, Nontraditional Risk Markers, and Incident Stroke in a Multiethnic Cohort.

Limited data exist on the performance of the revised Framingham Stroke Risk Score (R-FSRS) and the R-FSRS in conjunction with nontraditional risk markers. We compared the R-FSRS, original FSRS, and the Pooled Cohort Equation for stroke prediction and assessed the improvement in discrimination by nontraditional risk markers. Six thousand seven hundred twelve of 6814 participants of the MESA (Multi-Ethnic Study of Atherosclerosis) were included. Cox proportional hazard, area under the curve, net reclassification improvement, and integrated discrimination increment analysis were used to assess and compare each stroke prediction risk score. Stroke was defined as fatal/nonfatal strokes (hemorrhagic or ischemic). After mean follow-up of 10.7 years, 231 of 6712 (3.4%) strokes were adjudicated (2.7% ischemic strokes). Mean stroke risks using the R-FSRS, original FSRS, and Pooled Cohort Equation were 4.7%, 5.9%, and 13.5%. The R-FSRS had the best calibration (Hosmer-Lemeshow goodness-of-fit, χ2=6.55; P=0.59). All risk scores were predictive of incident stroke. C statistics of R-FSRS (0.716) was similar to Pooled Cohort Equation (0.716), but significantly higher than the original FSRS (0.653; P=0.01 for comparison with R-FSRS). Adding nontraditional risk markers individually to the R-FSRS did not improve discrimination of the R-FSRS in the area under the curve analysis, but did improve category-less net reclassification improvement and integrated discrimination increment for incident stroke. The addition of coronary artery calcium to R-FSRS produced the highest category-less net reclassification improvement (0.36) and integrated discrimination increment (0.0027). Similar results were obtained when ischemic strokes were used as the outcome. The R-FSRS downgraded stroke risk but had better calibration and discriminative ability for incident stroke compared with the original FSRS. Nontraditional risk markers modestly improved the discriminative ability of the R-FSRS, with coronary artery calcium performing the best.

KORELASI RASIO LINGKAR PINGGANG-PANGGUL TERHADAP PROBABILITAS STROKE ISKEMIK

Background. Stroke is the third cause of death worldwide. Ischemic stroke is the most common type of stroke with high prevalence. Obesity is one of ischemic stroke risk factor, but its correlation with higher ischemic stroke risk remains unclear. Studies about correlation of waist hip ratio (WHR) and ischemic stroke risk is still contradictive. Objective. This study was aimed to explore the correlation between WHR and ischemic stroke probability. Methods. This was a descriptive analytic study using cross sectional design. The population of this study was resident in Sekarbela Mataram aged 55-84 years old. This study was conducted 63 participants. They were interviewed and received a measurement of WHR and ischemic stroke probability. The ischemic stroke probability was assessed by using assessment of Framingham stroke risk score. Data were analyzed by using Pearson correlation. Results. Among 63 participants, 51 (81%) were abdominal obesity and 12 (19%) were normal based on WHR measurement. Pearson correlation analysis showed that there was no correlation between WHR and ischemic stroke probability (p = 0,11). Conclusion. There was no correlation between WHR and ischemic stroke probability of population in Sekarbela Mataram

Statistical evaluation of adding multiple risk factors improves Framingham stroke risk score

BackgroundFramingham Stroke Risk Score (FSRS) is the most well-regarded risk appraisal tools for evaluating an individual’s absolute risk on stroke onset. However, several widely accepted risk factors for stroke were not included in the original Framingham model. This study proposed a new model which combines an existing risk models with new risk factors using synthesis analysis, and applied it to the longitudinal Atherosclerosis Risk in Communities (ARIC) data set.MethodsRisk factors in original prediction models and new risk factors in proposed model had been discussed. Three measures, like discrimination, calibration and reclassification, were used to evaluate the performance of the original Framingham model and new risk prediction model.ResultsModified C-statistics, Hosmer-Lemeshow Test and classless NRI, class NRI were the statistical indices which, respectively, denoted the performance of discrimination, calibration and reclassification for evaluating the newly developed risk prediction model on stroke onset. It showed that the NEW-STROKE (new stroke risk score prediction model) model had higher modified C-statistics, smaller Hosmer-Lemeshow chi-square values after recalibration than original FSRS model, and the classless NRI and class NRI of the NEW-STROKE model over the original FSRS model were all significantly positive in overall group.ConclusionThe NEW-STROKE integrated with seven literature-derived risk factors outperformed the original FSRS model in predicting the risk score of stroke. It illustrated that seven literature-derived risk factors contributed significantly to stroke risk prediction.

Abstract TP205: Framingham Stroke Risk Score Predicts Severity of Leukoaraiosis in Patients with Acute Ischemic Stroke

Introduction: Severity of leukoaraiosis, or white matter hyperintensity (WMH) detected on T2 MRI, is associated with cognitive and functional decline and is a known risk factor for stroke and poor post-stroke outcomes. Fazekas score is a validated ordinal scale that accounts for WMH severity in the individual categories of periventricular (PVWM), deep WMH extent (DWMH) and deep WMH number of lesions (DWMNUM). Vascular risk factors (VRFs) are hypothesized to have differential effect on WMH lesion pathophysiology. We tested whether the Framingham Stroke Risk Score (FSRS), a collective score of several VRFs, is associated with WMH severity across individual Fazekas categories in a hospital-based cohort of patients with acute ischemic stroke (AIS). Methods: In 294 AIS patients, WMH was categorized into PVWM, DWMH, DWMNUM, and an average of all three categories per subject (“the condensed score”). Fazekas scores ranging 0-3 in each category were dichotomized (mild WMH≤1 vs. severe WMH ≥2). FSRS was calculated for each patient using a standardized formula awarding points for each FSRS variable (age, gender, systolic blood pressure, diabetes mellitus, cigarette smoking, coronary heart disease, left ventricular hypertrophy, atrial fibrillation) and added to obtain a total FSRS, which was then categorized into multiples of ten (FSRS ≥10, FSRS ≥20). Logistic regression models included binary FSRS category and Fazekas score for each WMH category using Stata 12. Results: As compared to AIS subjects with FSRS&lt;20, those with FSRS≥20 had greater odds of severe leukoaraiosis across all four WMH categories (Figure). Conclusions: In our cohort, FSRS predicts severity of leukoaraiosis across different Fazekas categories, suggesting compounded effect on WMH development from various VRFs comprising the FSRS. Future studies powered to discern the effect of individual elements of FSRS on WMH categories are warranted to further understand the pathophysiology of leukoaraiosis.

Abstract 134: A Telephone Approach for Sceening for Stroke RIsk: The REGARDS Telephone Stroke Risk Score

Introduction: The ability to identify a stroke/TIA-free population at high risk for stroke is important for risk assessment in the general population, and also a critical step to make a primary stroke prevention trial feasible. The standard for risk stratification is the Framingham Stroke Risk Score (FSRS); however, its use requires a clinic visit for blood pressure and ECG assessment, and laboratory measurement of glucose levels. The feasibility of a primary prevention trial would be greatly enhanced by a brief interview, potentially conducted over the telephone or web, to identify a high-risk population. Methods: A general population sample consisting of 23,983 REGARDS participants aged 45+ who reported being stroke and TIA free at baseline was characterized on 11 self-reported characteristics: age, race, sex, self-reported diagnosis of medical conditions (hypertension, diabetes, atrial fibrillation, and myocardial infarction), smoking, previous stroke symptoms, self-reported general health, and education. Participants were followed for incident stroke, with associations assessed by proportional hazards. Results: Over an average follow-up of 8.2 years, 564 incident strokes occurred. The self-reported characteristics were strongly related to stroke risk (see table), and proved marginally more predictive of stroke risk (c-statistic = 0.7268; 95% CI: 0.7078 - 0.7459) than the FSRS (c-statistic = 0.7222; 95% CI: 0.7025 - 0.7419). The annual stroke risk was 1.4% (95% CI: 1.2 - 1.7) for those in the highest decile of the telephone risk score. The Spearman correlation between the FSRS and the REGARDS telephone risk score was 0.848 (95% CI: 0.844 - 0.851). Discussion: The REGARDS Telephone Stroke Risk Score can be calculated using data collected over the telephone, at a web site, or in person. It can identify a population at high risk for stroke as well as the FSRS clinic-based assessment can, making it an efficient stroke risk assessment tool.

Abstract 12511: Left Ventricular Hypertrophy by Electrocardiogram versus Cardiac Magnetic Resonance Imaging as a Predictor for Stroke: The MESA Study

Background: Left ventricular hypertrophy (LVH) is an established risk factor for stroke and is a component of the Framingham Stroke Risk Score (FSRS). It is unknown, however, if LVH detected by the electrocardiogram (ECG-LVH) is equally predictive of stroke as LVH detected by cardiac magnetic resonance imaging (MRI-LVH). Methods: We analyzed 4716 participants (mean age 61±10 years, 53.4% women, 38.2% whites) from the Multi-Ethnic Study of Atherosclerosis (MESA) who were free of cardiovascular disease at baseline (2000-2002). ECG-LVH was defined as values &gt; 95 th percentile of left ventricular mass (LVM) derived from an established race- and sex-specific ECG model for estimating LVM indexed to weight. MRI-LVH was obtained from LVM by cardiac MRI using the 95th percentile cut-off value of observed LVM/predicted LVM calculated as 1.31. Multivariable Cox regression was used to examine the association between 1-standard deviation (SD) increase in estimated ECG-LVM and MRI-LVM as well as ECG-LVH and MRI-LVH, separately, with incident ischemic stroke. Harrell’s C-index was used to estimate the predictive ability of the FSRS model when either ECG-LVH or MRI-LVH was included. Results: Over a median follow-up of 11.2 years, 119 participants developed stroke. In a model adjusted for demographics and components of the FSRS, ECG-LVM and MRI-LVM as well as ECG-LVH and MRI-LVH were all predictive of stroke with ECG-LVM and MRI-LVH showing stronger associations with stroke in terms of hazard ratios but with wider confidence intervals (Table). However, the ability of FSRS model to predict stroke was slightly better when MRI-LVH (C-index 0.748, 95% CI: 0.514-0.829) was used as one of the FSRS components instead of ECG-LVH (C-index 0.739, 95% CI: 0.503-0.823), likelihood ratio test p 0.008. Conclusion: In asymptomatic cardiovascular disease-free individuals, both ECG-LVH and MRI-LVH are predictive of stroke. Using MRI-LVH slightly improves the predictive ability of the FSRS model.

Abstract MP102: Family Caregiving is Associated with Increased Stroke Risk Among Strained Spouse Caregivers

Background: As the American population ages, the number of family caregivers is expected to increase. Consequently, understanding the effects family caregiving has on the cardiovascular health of caregivers presents an important public health concern. Previous studies have observed associations between family caregiving and adverse cardiovascular health outcomes such as hypertension, coronary heart disease, and an increased Framingham Stroke Risk Score. However, the association between family caregiving and stroke risk is poorly understood. Hypothesis: We examined the association between family caregiving and risk of incident stroke in the REasons for Geographic and Racial Differences in Stroke (REGARDS) study to test the hypotheses that 1) family caregivers have higher risk of stroke compared to noncaregivers and 2) strained caregivers have higher risk of stroke compared to noncaregivers. Methods: The REGARDS study enrolled black and white participants, aged 45 and older, from 2003-2007. Participants were categorized as caregivers if they answered affirmatively to the baseline interview question, “Are you currently providing care on an on-going basis to a family member with a chronic illness or disability?” Caregivers were asked their relationship to the care recipient and the amount of perceived physical and mental strain they associated with care (none, some, a lot). Using a propensity score matching procedure based on 16 demographic, lifestyle, and stroke risk factors, caregivers (n=3,055) were individually matched with noncaregivers (n=3,055). Hazard ratios (HRs) and 95% confidence intervals (95% CIs) for incident stroke risk were calculated using Cox proportional hazards models. Results: During an average 8.5-year follow up period, 114 (3.73%) caregivers and 112 (3.67%) matched noncaregivers had an incident stroke. Caregivers did not have a higher risk of stroke compared to non-caregivers (HR=1.006, 95% CI=0.775, 1.306). The HRs (95% CIs) for incident stroke risk were 1.427 (0.938, 2.171) for caregivers reporting no caregiving strain, 0.918 (0.628, 1.341) for moderate strain, and 1.963 (0.977, 3.946) for high strain. Strained spouse caregivers who reported high or moderate strain had a 95% higher risk of stroke than matched noncaregivers (HR=1.958, 95% CI=1.002, 3.828). Conclusion: We observed that perceived caregiving strain, particularly among spouse caregiviers, is associated with increased risk of stroke. This group of caregivers may need targeted support. Further studies examining the nuanced effects of caregiver burden on cardiovascular health are required.

Relationship Between Cerebrovascular Risk, Cognition, and Treatment Outcome in Late-Life Psychotic Depression.

To examine whether cerebrovascular risk, executive function, and processing speed are associated with acute treatment outcome of psychotic depression in older adults. The authors analyzed data from 142 persons aged 60 years or older with major depression with psychotic features who participated in a 12-week randomized controlled trial (RCT) comparing olanzapine plus sertraline with olanzapine plus placebo. The independent variables were baseline cerebrovascular risk (Framingham Stroke Risk Score), baseline executive function (Stroop interference score and the initiation/perseveration subscale of the Mattis Dementia Rating Scale), and baseline processing speed (color and word reading components of the Stroop). The outcome variable was change in severity of depression, measured by the 17-item Hamilton Depression Rating Scale total score, during the course of the RCT. Greater baseline cerebrovascular risk was significantly associated with less improvement in depression severity over time, after controlling for pertinent covariates. Neither executive function nor processing speed predicted outcome. This study suggests an association of cerebrovascular risk, but not executive function or processing speed, with treatment outcome of major depression with psychotic features in older adults.

Electrocardiographic and Echocardiographic Left Ventricular Hypertrophy in the Prediction of Stroke in the Elderly

It is unclear whether left ventricular hypertrophy (LVH) detected by electrocardiography (ECG-LVH) is equally predictive of heart failure as LVH detected by echocardiography (echo-LVH). This analysis included 4,008 white participants (41% men) aged 65 years or older from the Cardiovascular Health Study who were free of stroke and major intraventricular conduction defects. ECG-LVH was defined by the Cornell criteria from baseline ECG data and echo-LVH was calculated from baseline echocardiography measurements. Cox regression was used to compute hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between ECG-LVH and echo-LVH and adjudicated incident stroke events, separately. Harrell's concordance indices (C-index) were calculated for the Framingham Stroke Risk Score with inclusion of ECG-LVH and echo-LVH, separately. ECG-LVH was detected in 136 (3.4%) participants and echo-LVH was present in 208 (5.2%) participants. Over a median follow-up of 13 years, a total of 769 (19%; incidence rate = 15.4 per 1000 person-years) strokes occurred. In a multivariable Cox regression analysis adjusted for stroke risk factors and potential confounders, ECG-LVH (HR = 1.68; 95% CI = 1.23, 2.28) and echo-LVH (HR = 1.58; 95% CI = 1.17, 2.14) were associated with an increased risk of stroke. Similar values were obtained for the C-index when either ECG-LVH (C-index = .786) or echo-LVH (C-index = .786) were included in the Framingham Stroke Risk Score. ECG-LVH and echo-LVH are able to be used interchangeably in stroke risk scores.

Abstract 149: Can Prevention of Risk Factors Pre-Stroke Reduce 30-Day Post-Stroke Mortality?

Introduction: Studies of short-term survival after stroke generally identify patients in the hospital, providing limited insights about the association between pre-stroke risk factors and outcomes. We hypothesized that pre-stroke risk factors will be related to 30-day case fatality. Methods: We prospectively studied the association of Framingham Stroke Risk Score (FSRS) factors on 30-day mortality following incident ischemic stroke (IS) among 28,253 stroke-free participants, aged 45+ in REGARDS, a national population based cohort enrolled 2003-2007. Suspect IS events were physician-reviewed. Logistic regression evaluated the association of pre-stroke risk factors with 30-day case-fatality after adjustment for age, race, sex and region of country. The six FSRS factors (hypertension, diabetes, cigarette smoking, atrial fibrillation, left ventricular hypertrophy, heart disease) were considered as predictors of case-fatality (individually, as a composite FSRS, and cumulative number present). Results: Of 792 incident IS events, 67 (8.5%) people died within 30-days. Age was strongly associated with case-fatality (p &lt; 0.0001), with a strong association for oldest age groups relative to those &lt;65 years (see table). Race, sex and region were not associated with case fatality. After adjustment for demographic factors, individual risk factors were positively but nonsignificantly associated with higher case fatality. Higher FSRS was associated with higher case fatality (test for trend p = 0.014), with increased fatality for the top two vs. the lowest tertile. Likewise, higher fatality was seen for those with more risk factors (test for trend p = 0.025), with a notable increase for those with 3+ cumulative risk factors. Conclusions: Individuals with higher pre-stroke risk factor burden were more likely to have a higher 30-day mortality following infarction. Prevention of risk factors could reduce the incidence of stroke and improve mortality following stroke.

The Stroke Riskometer(TM) App: validation of a data collection tool and stroke risk predictor.

BackgroundThe greatest potential to reduce the burden of stroke is by primary prevention of first-ever stroke, which constitutes three quarters of all stroke. In addition to population-wide prevention strategies (the ‘mass’ approach), the ‘high risk’ approach aims to identify individuals at risk of stroke and to modify their risk factors, and risk, accordingly. Current methods of assessing and modifying stroke risk are difficult to access and implement by the general population, amongst whom most future strokes will arise. To help reduce the burden of stroke on individuals and the population a new app, the Stroke Riskometer™, has been developed. We aim to explore the validity of the app for predicting the risk of stroke compared with current best methods.Methods752 stroke outcomes from a sample of 9501 individuals across three countries (New Zealand, Russia and the Netherlands) were utilized to investigate the performance of a novel stroke risk prediction tool algorithm (Stroke Riskometer™) compared with two established stroke risk score prediction algorithms (Framingham Stroke Risk Score [FSRS] and QStroke). We calculated the receiver operating characteristics (ROC) curves and area under the ROC curve (AUROC) with 95% confidence intervals, Harrels C-statistic and D-statistics for measure of discrimination, R2 statistics to indicate level of variability accounted for by each prediction algorithm, the Hosmer-Lemeshow statistic for calibration, and the sensitivity and specificity of each algorithm.ResultsThe Stroke Riskometer™ performed well against the FSRS five-year AUROC for both males (FSRS = 75·0% (95% CI 72·3%–77·6%), Stroke Riskometer™ = 74·0(95% CI 71·3%–76·7%) and females [FSRS = 70·3% (95% CI 67·9%–72·8%, Stroke Riskometer™ = 71·5% (95% CI 69·0%–73·9%)], and better than QStroke [males – 59·7% (95% CI 57·3%–62·0%) and comparable to females = 71·1% (95% CI 69·0%–73·1%)]. Discriminative ability of all algorithms was low (C-statistic ranging from 0·51–0·56, D-statistic ranging from 0·01–0·12). Hosmer-Lemeshow illustrated that all of the predicted risk scores were not well calibrated with the observed event data (P < 0·006).ConclusionsThe Stroke Riskometer™ is comparable in performance for stroke prediction with FSRS and QStroke. All three algorithms performed equally poorly in predicting stroke events. The Stroke Riskometer™ will be continually developed and validated to address the need to improve the current stroke risk scoring systems to more accurately predict stroke, particularly by identifying robust ethnic/race ethnicity group and country specific risk factors.

Coronary Artery Calcium and Incident Cerebrovascular Events in an Asymptomatic Cohort: The MESA Study

ObjectivesThis study assessed the predictive value of coronary artery calcium (CAC) score for cerebrovascular events (CVE) in an asymptomatic multiethnic cohort. BackgroundThe CAC score, a measure of atherosclerotic burden, has been shown to improve prediction of coronary heart disease events. However, the predictive value of CAC for CVE is unclear. MethodsCAC was measured at baseline examination of participants (N = 6,779) of MESA (Multi-Ethnic Study of Atherosclerosis) and then followed for an average of 9.5 ± 2.4 years for the diagnosis of incident CVE, defined as all strokes or transient ischemic attacks. ResultsDuring the follow-up, 234 (3.5%) adjudicated CVE occurred. In Kaplan-Meier analysis, the presence of CAC was associated with a lower CVE event-free survival versus the absence of CAC (log-rank chi-square: 59.8, p < 0.0001). Log-transformed CAC was associated with increased risk for CVE after adjusting for age, sex, race/ethnicity, body mass index, systolic and diastolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, cigarette smoking status, blood pressure medication use, statin use, and interim atrial fibrillation (hazard ratio [HR]: 1.13 [95% confidence interval (CI): 1.07 to 1.20], p < 0.0001). The American College of Cardiology/American Heart Association–recommended CAC cutoff was also an independent predictor of CVE and strokes (HR: 1.70 [95% CI: 1.24 to 2.35], p = 0.001, and HR: 1.59 [95% CI: 1.11 to 2.27], p = 0.01, respectively). CAC was an independent predictor of CVE when analysis was stratified by sex or race/ethnicity and improved discrimination for CVE when added to the full model (c-statistic: 0.744 vs. 0.755). CAC also improved the discriminative ability of the Framingham stroke risk score for CVE. ConclusionsCAC is an independent predictor of CVE and improves the discrimination afforded by current stroke risk factors or the Framingham stroke risk score for incident CVE in an initially asymptomatic multiethnic adult cohort.

In 85-year-old adults, MMSE predicted 5-year risk for first stroke better than Framingham score

Source Citation Sabayan B, Gussekloo J, de Ruijter W, Westendorp RG, de Craen AJ. Framingham stroke risk score and cognitive impairment for predicting first-time stroke in the oldest old. Stroke. 2013;44:1866-71. 23686982