Lifetime risk of stroke in young-aged and middle-aged Chinese population: the Chinese Multi-Provincial Cohort Study

Long-term risk and characteristics of cerebrovascular events after upper body radiotherapy among childhood cancer survivors in the DCCSS-LATER cohort

Cerebrovascular events (CVEs) are serious late adverse events among childhood cancer survivors. We estimated the incidence and risk factors of symptomatic CVEs and described the clinical characteristics among childhood cancer survivors after upper body radiotherapy. The Dutch Childhood Cancer Survivor Study LATER cohort study includes 5-year childhood cancer survivors diagnosed 50 Gy was associated with 6-fold increased risk, compared to upper body radiotherapy not involving the cranium (hazard ratio = 6.3, 95%CI: 3.3-12.1). In a subgroup with available data on lifestyle and comorbidities, hypertension (odds ratio[OR] = 6.2, 95%CI: 1.6-23.8) and obesity (BMI≥30 vs. <30 = 2.95, 95%CI: 1.1-8.0) significantly increased CVE risk. During CVE episode, 17 (16%) had a life-threatening situation, and two (2%) others died. In 28%, a second CVE developed during follow-up. At end of follow-up, 29% were deceased, and 40% of those alive were unable to carry out normal activities/active work. Childhood cancer survivors treated with higher doses of cranial radiotherapy are at highest risk for developing CVEs. CVEs occur at a young age and cause a high morbidity. Studies to investigate risk-reducing secondary preventive interventions are warranted.

Association between biological aging and cardiovascular health: Combined evidence based on cross-sectional and prospective study

PURPOSE

To examine the relationship between biological aging metrics and cardiovascular health, as well as the mediating effect of sleep duration.

METHOD

We applied the recommended sampling weights to adjust for the complex survey design of NHANES. Using NHANES data, we first employed restricted cubic spline (RCS) and logistic regression models to explore the cross-sectional associations between biological aging metrics, defined by the Klemera-Doubal method biological age (KDM-BA), phenotypic age (PA), homeostatic dysregulation (HD), and allostatic load (AL), and the prevalence of cardiovascular diseases (CVD) and its subtypes. We then used Cox regression, Kaplan-Meier curves, and RCS models to assess the prospective associations between biological aging metrics and all-cause as well as CVD mortality. Further, ROC and DCA models were used to assess the predicting ability of 4 biological aging metrics to cardiovascular health.

RESULT

This study included 7,704 participants. We found that biological aging metrics were strongly linked to the prevalence of CVD and its subtypes, as well as to all-cause and CVD mortality. Sleep duration appeared to moderate these associations. Among the four biological aging metrics, PA was the most effective predictor of CVD prevalence and its subtypes, though none of the metrics accurately predicted mortality.

CONCLUSION

Biological aging metrics were significantly associated with cardiovascular health, while sleep duration may attenuate this relationship. Clinically, PA can be a potential predictor of cardiovascular health.

Do facilitators and barriers to community ambulation differ among stroke survivors in low resource settings? A cross-sectional study in Nigeria

PURPOSE

Stroke survivors (SSV) in many low- and middle-income countries experience frustrating participation restriction in community ambulation (CA), which impedes community life. This study assessed facilitators and barriers to CA among community-dwelling SSV in a southwest state of Nigeria.

METHODS

This cross-sectional study involved 66 community-dwelling ambulating SSV, purposively recruited from physiotherapy out-patient clinics of selected hospitals in southwest Nigeria. Semi-structured questionnaire containing physical and social environment elements of the ICF domains was administered on respondents. Mobility status at home and community, socio-demographic and clinical data of SSV were also obtained. Responses from open-ended questions were triangulated with appropriate close ended options. Data were analyzed using descriptive statistics and logistic regression at p < 0.05 Alpha value.

RESULTS

Majority of the SSV were independent in their homes (59.1%), used mobility aids (87.9%) and assisted in CA (66.7%). They identified limited physical accessibility by crowds 25 (37.9%), lack of inclined surfaces 40 (95.2%), uneven floors 36 (87.8%), public seating arrangements 33 (78.6%), rain (73.8%) and inability to use services, systems and policies (77.3%) as barriers to CA. Built physical environment was a significant predictor of home (OR = 0.754, p = 0.001) and community mobility (OR = 0.850; p = 0.018), while post-stroke depression was a significant predictor of community mobility (OR = 1.038; p = 0.014).

CONCLUSION

Mobility aids, social attitudes and general support were identified as facilitators, whereas barriers to CA included built physical environment, services and policies, products and technology. Facilitators and barriers to CA are similar to some HIC contexts, perceived difficulties and experiences differ for infrastructural and social reasons among others.

Interpretable prediction of acute ischemic stroke after hip fracture in patients 65 years and older based on machine learning and SHAP

BACKGROUND

Hip fracture and acute ischemic stroke (AIS) are prevalent conditions among the older population. The prognosis for older patients who experience AIS subsequent to hip fracture is frequently unfavorable.

METHODS

Patients were categorized into the AIS group and the non-AIS group. A predictive model was developed using six different machine learning algorithms. The SHapley Additive exPlanations (SHAP) method was then utilized to provide both local and global explanations. We performed adjusted mediation analyses. Furthermore, a nomogram was created to present the outcomes obtained from the LASSO regression examination. The main objective was to ascertain influential elements that can predict the occurrence of AIS. To alleviate the influence of confounding variables, propensity score matching was utilized to compare the occurrence of additional complications. Survival was compared by Kaplan-Meier methods.

RESULTS

The AUC of 6 ML models ranged from 0.73 to 0.87. The SVM model exhibited the greatest efficacy in forecasting AIS among older individuals with hip fractures. The leading 6 variables in the support vector machines (SVM) model were identified as systemic inflammatory response index (SIRI), carotid atherosclerosis, prior stroke, C-reactive protein (CRP), fibrinogen (FIB), and hypertension. The leading 2 variables in SHAP were identified as FIB at admission and SIRI index. There wasn't potential mediating effect of admission FIB between the SIRI index and AIS. There were statistically significant differences between the two groups in survival (P=0.003).

CONCLUSIONS

The model displayed good performance for prediction of AIS after hip fracture in patients 65 years and older, which might facilitate to establishment of a better clinical assessment plan.

Impact of Aging on Cardiovascular Diseases: From Chronological Observation to Biological Insights: JACC Family Series

Cardiovascular disease (CVD) has increasing challenges for human health with an increasingly aging population worldwide, imposing a significant obstacle to the goal of healthy aging. Rapid advancements in our understanding of biological aging process have shed new light on some important insights to aging-related diseases. Although numerous reviews delved into the mechanisms through which biological aging affects CVD and age-related diseases, most of these reviews relied heavily on research related to cellular and molecular processes often observed from animal experiments. Few reviews have provided insights that connect hypotheses regarding the biological aging process with the observed patterns of chronological aging-related impacts on CVD in human populations. The purpose of this review is to highlight some of the major questions in studies of aging-related CVD and provide our perspectives in the context of real-world patterns of CVD with multidimensional information and potential biological insights.

Cost-effectiveness of treatment in adults with blood pressure of 130-139/80-89 mmHg and high cardiovascular risk in China: a modelling study

Background

The most recent updated hypertension guidelines recommend individuals with systolic blood pressure (SBP)/diastolic blood pressure (DBP) of 130-139/80-89 mmHg and high cardiovascular risk should receive antihypertensive drug treatment. This study aimed to assess the benefits and cost-effectiveness of medication for people aged ≥35 years with this blood pressure stratum and high cardiovascular risk in China.

Methods

The benefits of drug treatment in adults aged ≥35 years with SBP/DBP of 130-139/80-89 mmHg and high cardiovascular risk were evaluated in decision-analytic simulation models. Decreasing numbers of cardiovascular disease (CVD) events and premature deaths from all causes and increasing quality-adjusted life-years (QALYs) from drug treatment were estimated in 10-year and lifetime horizons. The incremental cost-effectiveness ratios (ICER) for drug treatment were calculated.

Findings

Among approximately 106.60 million Chinese adults aged ≥35 years with this blood pressure stratum and high cardiovascular risk, drug treatment was estimated to prevent 2,060,000 strokes and 660,000 myocardial infarctions over a 10-year time horizon. Adults prescribed antihypertensive drugs could gain 0.034 incremental QALYs. Over a lifetime horizon, adults who start treatment earlier could benefit more in preventing CVD and gaining incremental QALYs. The medication treatment is cost-effective either over a 10-year time horizon with an ICER of Int$13321.29 per QALY gained or over the remaining lifetime.

Interpretation

Antihypertensive treatment of adults with SBP/DBP of 130-139/80-89 mmHg and high cardiovascular risk would gain substantial benefits with cost-effectiveness. The young and middle-aged population would derive the most benefit.

Funding

National Natural Science Foundation of China, and Beijing Natural Science Foundation.

Assessment of Lifetime Risk for Cardiovascular Disease: Time to Move Forward

Over the past decades, there has been a notable increase in the risk of Cardiovascular Disease (CVD), even among younger individuals. Policymakers and the health community have revised CVD prevention programs to include younger people in order to take these new circumstances into account. A variety of CVD risk assessment tools have been developed in the past years with the aim of identifying potential CVD candidates at the population level; however, they can hardly discriminate against younger individuals at high risk of CVD.Therefore, in addition to the traditional 10-year CVD risk assessment, lifetime CVD risk assessment has recently been recommended by the American Heart Association/American College of Cardiology and the European Society of Cardiology prevention guidelines, particularly for young individuals. Methodologically, the benefits of these lifetime prediction models are the incorporation of left truncation observed in survival curves and the risk of competing events which are not considered equivalent in the common survival analysis. Thus, lifetime risk data are easily understandable and can be utilized as a risk communication tool for Public Health surveillance. However, given the peculiarities behind these estimates, structural harmonization should be conducted in order to create a sex-, race-specific tool that is sensitive to accurately identifying individuals who are at high risk of CVD. In this review manuscript, we present the most commonly used lifetime CVD risk tools, elucidate several methodological and critical points, their limitations, and the rationale behind their integration into everyday clinical practice.

Interpretable machine learning for predicting 28-day all-cause in-hospital mortality for hypertensive ischemic or hemorrhagic stroke patients in the ICU: a multi-center retrospective cohort study with internal and external cross-validation

Background

Timely and accurate outcome prediction plays a critical role in guiding clinical decisions for hypertensive ischemic or hemorrhagic stroke patients admitted to the ICU. However, interpreting and translating the predictive models into clinical applications are as important as the prediction itself. This study aimed to develop an interpretable machine learning (IML) model that accurately predicts 28-day all-cause mortality in hypertensive ischemic or hemorrhagic stroke patients.

Methods

A total of 4,274 hypertensive ischemic or hemorrhagic stroke patients admitted to the ICU in the USA from multicenter cohorts were included in this study to develop and validate the IML model. Five machine learning (ML) models were developed, including artificial neural network (ANN), gradient boosting machine (GBM), eXtreme Gradient Boosting (XGBoost), logistic regression (LR), and support vector machine (SVM), to predict mortality using the MIMIC-IV and eICU-CRD database in the USA. Feature selection was performed using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. Model performance was evaluated based on the area under the curve (AUC), accuracy, positive predictive value (PPV), and negative predictive value (NPV). The ML model with the best predictive performance was selected for interpretability analysis. Finally, the SHapley Additive exPlanations (SHAP) method was employed to evaluate the risk of all-cause in-hospital mortality among hypertensive ischemic or hemorrhagic stroke patients admitted to the ICU.

Results

The XGBoost model demonstrated the best predictive performance, with the AUC values of 0.822, 0.739, and 0.700 in the training, test, and external cohorts, respectively. The analysis of feature importance revealed that age, ethnicity, white blood cell (WBC), hyperlipidemia, mean corpuscular volume (MCV), glucose, pulse oximeter oxygen saturation (SpO2), serum calcium, red blood cell distribution width (RDW), blood urea nitrogen (BUN), and bicarbonate were the 11 most important features. The SHAP plots were employed to interpret the XGBoost model.

Conclusions

The XGBoost model accurately predicted 28-day all-cause in-hospital mortality among hypertensive ischemic or hemorrhagic stroke patients admitted to the ICU. The SHAP method can provide explicit explanations of personalized risk prediction, which can aid physicians in understanding the model.

Hypertension in China: epidemiology and treatment initiatives

The past two to three decades have seen a steady increase in the prevalence of hypertension in China, largely owing to increased life expectancy and lifestyle changes (particularly among individuals aged 35-44 years). Data from the China hypertension survey conducted in 2012-2015 revealed a high prevalence of grade 3 hypertension (systolic blood pressure ≥180 mmHg and diastolic blood pressure ≥110 mmHg) in the general population, which increased with age to up to 5% among individuals aged ≥65 years. The risk profile of patients with hypertension in China has also been a subject of intense study in the past 30 years. Dietary sodium and potassium intake have remained largely the same in China in the past three decades, and salt substitution strategies seem to be effective in reducing blood pressure levels and the risk of cardiovascular events and death. However, the number of individuals with risk factors for hypertension and cardiovascular disease in general, such as physical inactivity and obesity, has increased dramatically in the same period. Moreover, even in patients diagnosed with hypertension, their disease is often poorly managed owing to a lack of patient education and poor treatment compliance. In this Review, we summarize the latest epidemiological data on hypertension in China, discuss the risk factors for hypertension that are specific to this population, and describe several ongoing nationwide hypertension control initiatives that target these risk factors, especially in the low-resource rural setting.

Development of a predictive risk stratification tool to identify the population over age 45 at risk for new-onset stroke within 7 years

Background and purpose

With the acceleration of the aging process of society, stroke has become a major health problem in the middle-aged and elderly population. A number of new stroke risk factors have been recently found. It is necessary to develop a predictive risk stratification tool using multidimensional risk factors to identify people at high risk for stroke.

Methods

The study included 5,844 people (age ≥ 45 years) who participated in the China Health and Retirement Longitudinal Study in 2011 and its follow-up up to 2018. The population samples were divided into training set and validation set according to 1:1. A LASSO Cox screening was performed to identify the predictors of new-onset stroke. A nomogram was developed, and the population was stratified according to the score calculated through the X-tile program. Internal and external verifications of the nomogram were performed by ROC and calibration curves, and the Kaplan-Meier method was applied to identify the performance of the risk stratification system.

Results

The LASSO Cox regression screened out 13 candidate predictors from 50 risk factors. Finally, nine predictors, including low physical performance and the triglyceride-glucose index, were included in the nomogram. The nomogram's overall performance was good in both internal and external validations (AUCs at 3-, 5-, and 7-year periods were 0.71, 0.71, and 0.71 in the training set and 0.67, 0.65, and 0.66 in the validation set, respectively). The nomogram was proven to excellently discriminate between the low-, moderate-, and high-risk groups, with a prevalence of 7-year new-onset stroke of 3.36, 8.32, and 20.13%, respectively (P < 0.001).

Conclusion

This research developed a clinical predictive risk stratification tool that can effectively identify the different risks of new-onset stroke in 7 years in the middle-aged and elderly Chinese population.

Effects of cortico-cortical paired associative stimulation based on multisensory integration to brain network connectivity in stroke patients: study protocol for a randomized doubled blind clinical trial

INTRODUCTION

Brain has a spontaneous recovery after stroke, reflecting the plasticity of the brain. Currently, TMS is used for studies of single-target brain region modulation, which lacks consideration of brain networks and functional connectivity. Cortico-cortical paired associative stimulation (ccPAS) promotes recovery of motor function. Multisensory effects in primary visual cortex(V1) directly influence behavior and perception, which facilitate motor functional recovery in stroke patients. Therefore, in this study, dual-targeted precise stimulation of V1 and primary motor cortex(M1) on the affected hemisphere of stroke patients will be used for cortical visuomotor multisensory integration to improve motor function.

METHOD

This study is a randomized, double-blind controlled clinical trial over a 14-week period. 69 stroke subjects will be enrolled and divided into sham stimulation group, ccPAS low frequency group, and ccPAS high frequency group. All groups will receive conventional rehabilitation. The intervention lasted for two weeks, five times a week. Assessments will be performed before the intervention, at the end of the intervention, and followed up at 6 and 14 weeks. The primary assessment indicator is the 'Fugl-Meyer Assessment of the Upper Extremity ', secondary outcomes were 'The line bisection test', 'Modified Taylor Complex Figure', 'NIHSS' and neuroimaging assessments. All adverse events will be recorded.

DISCUSSION

Currently, ccPAS is used for the modulation of neural circuits. Based on spike-timing dependent plasticity theory, we can precisely intervene in the connections between different cortices to promote the recovery of functional connectivity on damaged brain networks after stroke. We hope to achieve the modulation of cortical visuomotor interaction by combining ccPAS with the concept of multisensory integration. We will further analyze the correlation between analyzing visual and motor circuits and explore the alteration of neuroplasticity by the interactions between different brain networks. This study will provide us with a new clinical treatment strategy to achieve precise rehabilitation for patient with motor dysfunction after stroke.

TRIAL REGISTRATION

This trial was registered in the Chinese Clinical Trial Registry with code ChiCTR2300067422 and was approved on January 16, 2023.

The Malay version of the attitudes and beliefs about cardiovascular disease (ABCD-M) risk questionnaire: a translation, reliability and validation study

BACKGROUND

Cardiovascular disease (CVD) and stroke are global public health problems and cause high mortality, especially in low- and middle-income countries. Knowledge and awareness are critical points in managing the risk in the general population. The Attitudes and Beliefs about Cardiovascular Disease (ABCD) risk questionnaire was developed to evaluate the awareness of stroke and CVD risk. Thus, the government can set up a practical risk assessment and management programme. The initiative will encourage people to seek healthcare timely and reduce the possibilities of developing complications.

OBJECTIVE

This study aimed to translate and validate the ABCD risk questionnaire into the Malay language and evaluate the psychometric properties of the Malay version in the general population in Malaysia.

METHODS

The questionnaire was translated using a standard forward-backwards translation method. The validation was perfomed by both expert panels and a potential user group. Next, the exploratory factor analysis was conducted to examine factorial validity. The respondents were selected from the government health clinics and according to the study criteria irrespective of the CVD risk. We used Cronbach's alpha and Raykov's rho to explore the internal consistency and composite reliability of the 18 items from three domains. Finally, the confirmatory factor analysis (CFA) was conducted using a robust maximum likelihood estimator.

RESULTS

The content and face validity indices were determined to be 0.94 and 0.99 respectively. Data were obtained from 179 respondents (mean age, 36.8 years; female, 68.2%; secondary level education, 51.1%). The internal consistency and composite reliability of the domains showed good results ranging from 0.643 to 0.885. The factor loadings of each item were acceptable (> 0.3), and the fit indices from the CFA resulted in a good model fit [χ² (p-value = 0.16), SRMR = 0.054, RMSEA = 0.029, CFI = 0.99, TLI = 0.99)].

CONCLUSIONS

The Malay version of the ABCD risk questionnaire is a valid and reliable tool to assess the awareness of stroke and CVD risk in the general population in Malaysia.

Prevalence of cardiovascular disease risk factors in Chinese patients with type 2 diabetes mellitus, 2013-2018

OBJECTIVE

Coronary heart disease (CHD) is the most common cause of death in patients with type 2 diabetes (T2DM). We aim to estimate the prevalence of CHD and cardiovascular risk factors in Chinese patients with T2DM.

METHODS

A total of 66,536 inpatients with diabetes treated from 2013 to 2018 were investigated, and demographic and clinical data were collected from 30,693 patients with T2DM. Age-standardized prevalence of CHD was calculated on the basis of data from the Chinese population census in 2010. Logistic regression analysis was used to analyze the risk factors.

RESULTS

The crude prevalence of CHD was estimated to be 23.5% and a standardized prevalence was 13.9% (16.0% in men and 11.9% in women). More than half of patients with CHD have four or more of the five traditional risk factors, much higher than the 38.96% of patients without CHD (p < .01). Multivariate regression analysis showed that diabetes duration, hypertension, smoking, underweight, overweight, obesity and hypoglycaemia were significantly associated with increased risk of CHD (all p < .05). The odds ratio of CHD in patients with three, four or five defined CHD risk factors (i.e. diabetes, hypertension, dyslipidaemia, overweight or obese, and smoking) were 2.35 (95% CI 1.81-3.04), 2.96 (95% CI 2.28-3.85) or 5.29 (95% CI 4.04-6.93), compared with diabetes patients without any other risk factors.

CONCLUSIONS

The prevalence of CHD was rather high in Chinese T2DM inpatients, and the aggregation of CHD risk factors was severe. Thus, hierarchical CHD prevention strategies based on risk factors are necessary.

The Effectiveness of Stroke Riskometer™ in Improving Stroke Risk Awareness in Malaysia: A Study Protocol of a Cluster-Randomized Controlled Trial

BACKGROUND

Stroke is considered the second leading cause of mortality and disability worldwide. The increasing burden of stroke is strong evidence that currently used primary prevention strategies are not sufficiently effective. The Stroke Riskometer™ application (app) represents a new stroke prevention strategy distinctly different from the conventional high-cardiovascular disease risk approach.

OBJECTIVE

This proposed study aims to evaluate the effectiveness of the Stroke Riskometer™ app in improving stroke awareness and stroke risk probability amongst the adult population in Malaysia.

METHODS

A non-blinded, parallel-group cluster-randomized controlled trial with a 1:1 allocation ratio will be implemented in Kelantan, Malaysia. Two groups with a sample size of 66 in each group will be recruited. The intervention group will be equipped with the Stroke Riskometer™ app and informational leaflets, while the control group will be provided with standard management, including information leaflets only. The Stroke Riskometer™ app was developed according to the self-management model of chronic diseases based on self-regulation and social cognitive theories. Data collection will be conducted at baseline and on the third week, sixth week, and sixth month follow-up via telephone interview or online questionnaire survey. The primary outcome measure is stroke risk awareness, including the domains of knowledge, perception, and intention to change. The secondary outcome measure is stroke risk probability within 5 and 10 years adjusted to each participant's socio-demographic and/or socio-economic status. An intention-to-treat approach will be used to evaluate these measures. Pearson's χ2 or independent t test will be used to examine differences between the intervention and control groups. The generalized estimating equation and the linear mixed-effects model will be employed to test the overall effectiveness of the intervention.

CONCLUSION

This study will evaluate the effect of Stroke Riskometer™ app on stroke awareness and stroke probability and briefly evaluate participant engagement to a pre-specified trial protocol. The findings from this will inform physicians and public health professionals of the benefit of mobile technology intervention and encourage more active mobile phone-based disease prevention apps.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier NCT04529681.

Development and internal validation of a multivariable prediction model for 6-year risk of stroke: a cohort study in middle-aged and elderly Chinese population

OBJECTIVE

To develop and internally validate a prediction model for 6-year risk of stroke and its primary subtypes in middle-aged and elderly Chinese population.

DESIGN

This is a retrospective cohort study from a prospectively collected database.

PARTICIPANTS

We included a total 3124 adults aged 45-80 years, free of stroke or myocardial infarction at baseline in the 2009-2015 cohort of China Health and Nutrition Survey.

PRIMARY AND SECONDARY OUTCOME MEASURES

The outcome of the prediction model was stroke. Investigated predictors were: age, gender, body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), hypertension (HBP), drinking status, smoking status, diabetes and site. Stepwise multiple Cox regression was applied to identify independent predictors. A nomogram was constructed to predict 6-year risk of stroke based on the multiple analysis results. Bootstraps with 1000 resamples were applied to both C-index and calibration curve.

RESULT

The overall incidence of overall stroke was 2.98%. Age, gender, HBP and TC were found as significant risk predictors for overall stroke; age, gender, HBP and LDL-C were found as significant risk predictors for ischaemic stroke; age, gender, HBP, BMI and HDL-C were found as significant risk predictors for haemorrhagic stroke. The nomogram was constructed using significant variables included in the model, with a C-index of 0.74 (95% CI: 0.72 to 0.76), 0.74 (95% CI: 0.71 to 0.77), and 0.81 (95% CI: 0.78 to 0.84) for overall stroke, ischaemic stroke, and haemorrhagic stroke model, respectively. The calibration curves demonstrated the good agreements between predicted and observed 6-year risk probability.

CONCLUSION

Our nomogram could be convenient, easy to use and effective prognoses for predicting 6-year risk of stroke in middle-aged and elderly Chinese population.

Lifetime risk of stroke stratified by chronic kidney disease and hypertension in the general Asian population: the Ohasama study

Lifetime risk (LTR) evaluates the absolute risk of developing a disease during the remainder of one's life. It can be a useful tool, enabling the general public to easily understand their risk of stroke. No study has been performed to determine the LTR of cardiovascular disease in patients with chronic kidney disease (CKD) with or without hypertension; therefore, we performed this study in an Asian population. We followed 1525 participants (66.0% women; age 63.1 years) in the general population of Ohasama, Japan. We defined CKD as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m² and/or proteinuria. Hypertension was defined as a systolic/diastolic blood pressure ≥140/≥90 mmHg and/or the use of antihypertensive medication. We calculated the sex-specific LTR of stroke adjusted for the competing risk of death. During the mean follow-up period of 16.5 years, a first stroke occurred in 238 participants. The 10-year risk of stroke at the age of 45 years was 0.0% for men and women. The LTRs of stroke at the index age of 45 years (men/women) were 20.9%/14.5% for participants without CKD and hypertension, 34.1%/29.8% for those with CKD but not hypertension, 37.9%/27.3% for those with hypertension but not CKD, and 38.4%/36.4% for those with CKD and hypertension. The LTRs of stroke tended to be higher in younger participants than in older participants with CKD and/or hypertension. CKD contributed to the LTR of stroke, as did hypertension. The prevention of CKD and hypertension can reduce the LTR of stroke, especially in young populations.

Development and validation of a 2-year new-onset stroke risk prediction model for people over age 45 in China

Multiple factors, including increasing incidence, poor knowledge of stroke and lack of effective, noninvasive and convenient stroke risk prediction tools, make it more difficult for precautions against stroke in China. Effective prediction models for stroke may assist to establish better risk awareness and management, healthier lifestyle, and lower stroke incidence for people.The China Health and Retirement Longitudinal Survey was the development cohort. Logistic regression was applied to model's development, in which the candidate variables with statistically significant coefficient were included in the prediction model. The area under receiver operating characteristic curve (AUC) and 10-times cross-validation were used for internal validation. Cutoff point of high-risk group was measured by Youden index. The China Health and Nutrition Survey was the validation cohort.The development cohort and the validation cohort included 16557 and 5065 participants, and the incidence density was 358.207/100,000 person-year and 350.701/100,000 person-year, respectively. The model for 2-year new-onset stroke risk prediction included age, hypertension, diabetes, heart disease, and smoking. The AUC and cross-validation AUC were 0.707 (95% confidence interval[CI]: 0.664, 0.750) and the 0.710 (95% CI: 0.650, 0.736). The sensitivity, specificity and accuracy of the cutoff point were 0.774, 0.545, and 0.319. The AUC and cross-validation AUC were 0.800 (95% CI: 0.744, 0.856) and 0.811(95% CI:0.714, 0.847), and the sensitivity, specificity and accuracy of cutoff point being 0.857,0.569, and 0.426 in external validation.A simple prediction tool using 5 noninvasive and easily accessible factors can assist in 2-year new-onset stroke risk prediction in Chinese people over 45 years old, which is believed to be applicable in identifying high-risk individuals and health management in China.

Lifetime risks and health impacts of hemorrhagic and ischemic stroke in South Korea

This study is aimed toward estimating the lifetime risks, life expectancy, expected years of life lost (EYLL), and lifetime costs related to different subtypes of stroke in South Korea. We included 13,994 patients diagnosed with stroke (ICD-10, I60-I63) in the National Health Insurance Service-National Sample Cohort of Korea between 2006 and 2015. Lifetime risks were calculated using the cumulative incidence rate for patients aged 18–84. Lifetime survival data were obtained through the Kaplan–Meier method and extrapolated with a rolling-over extrapolation algorithm. The lifetime costs were estimated by multiplying the average monthly expenditures with the survival probabilities and adding the values over lifetime. The lifetime risks of stroke in Korea have been decreasing consistently over the last decade with the exception of subarachnoid hemorrhage in females, which appears to have slightly increased. The EYLL is higher in hemorrhagic stroke than in ischemic stroke (6–9.7 vs. 4.7). Expected lifetime costs reimbursed by the NHIS would amount to about $71,406 accompanied with $14,921 copayment from the patients for hemorrhagic stroke, and $50,551 and $11,666, respectively, for ischemic stroke. Further studies are warranted to combine survival with quality of life and functional disability to obtain a more detailed outcome assessment of the potential impact of the prevention of stroke.

Stroke Prediction with Machine Learning Methods among Older Chinese

Timely stroke diagnosis and intervention are necessary considering its high prevalence. Previous studies have mainly focused on stroke prediction with balanced data. Thus, this study aimed to develop machine learning models for predicting stroke with imbalanced data in an elderly population in China. Data were obtained from a prospective cohort that included 1131 participants (56 stroke patients and 1075 non-stroke participants) in 2012 and 2014, respectively. Data balancing techniques including random over-sampling (ROS), random under-sampling (RUS), and synthetic minority over-sampling technique (SMOTE) were used to process the imbalanced data in this study. Machine learning methods such as regularized logistic regression (RLR), support vector machine (SVM), and random forest (RF) were used to predict stroke with demographic, lifestyle, and clinical variables. Accuracy, sensitivity, specificity, and areas under the receiver operating characteristic curves (AUCs) were used for performance comparison. The top five variables for stroke prediction were selected for each machine learning method based on the SMOTE-balanced data set. The total prevalence of stroke was high in 2014 (4.95%), with men experiencing much higher prevalence than women (6.76% vs. 3.25%). The three machine learning methods performed poorly in the imbalanced data set with extremely low sensitivity (approximately 0.00) and AUC (approximately 0.50). After using data balancing techniques, the sensitivity and AUC considerably improved with moderate accuracy and specificity, and the maximum values for sensitivity and AUC reached 0.78 (95% CI, 0.73–0.83) for RF and 0.72 (95% CI, 0.71–0.73) for RLR. Using AUCs for RLR, SVM, and RF in the imbalanced data set as references, a significant improvement was observed in the AUCs of all three machine learning methods (p < 0.05) in the balanced data sets. Considering RLR in each data set as a reference, only RF in the imbalanced data set and SVM in the ROS-balanced data set were superior to RLR in terms of AUC. Sex, hypertension, and uric acid were common predictors in all three machine learning methods. Blood glucose level was included in both RLR and RF. Drinking, age and high-sensitivity C-reactive protein level, and low-density lipoprotein cholesterol level were also included in RLR, SVM, and RF, respectively. Our study suggests that machine learning methods with data balancing techniques are effective tools for stroke prediction with imbalanced data.

Predicting 10-Year and Lifetime Stroke Risk in Chinese Population

Background and Purpose—

Risk assessment is essential for the primary prevention of stroke. However, the current available tools derived from Chinese populations are insufficient for individualized 10-year and lifetime stroke risk prediction. Our study aims to develop and validate personalized 10-year and lifetime stroke risk equations incorporating 4 large Chinese cohorts.

Methods—

We used 2 prospective cohorts of 21 320 participants with similar survey protocols as the derivation cohort to develop sex-specific 10-year and lifetime stroke risk equations. Two other independent cohorts with 14 123 and 70 838 participants were used for external validation. In addition, the performance of the 10-year stroke risk equations among participants aged ≥55 years was compared with the new Framingham Stroke Risk Profile.

Results—

The sex-specific equations for predicting 10-year stroke risk had C statistics being 0.810 for men and 0.810 for women, with calibration χ 2 being 15.0 ( P =0.092) and 7.8 ( P =0.550), respectively. The lifetime stroke risk equations also showed C statistics around 0.800 and calibration χ 2 below 20 for both sexes. In the validation cohorts, we found good agreement between the observed and predicted stroke probabilities for both the 10-year and lifetime stroke risk equations. Further compared with the new Framingham Stroke Risk Profile, our 10-year stroke risk equations displayed better prediction capability. In addition, based on lifetime stroke risk assessment, 5.7% of study participants aged 35 to 49 years old were further reclassified as high risk, who were initially categorized as low 10-year risk.

Conclusions—

We developed a well-performed tool for predicting personalized 10-year and lifetime stroke risk among the Chinese adults, which will facilitate the further identification of high-risk individuals and community-based stroke prevention in China.

Anthology of stroke epidemiology in the 20th and 21st centuries: Assessing the past, the present, and envisioning the future

This narrative overview of stroke epidemiology shows dramatic changes in stroke incidence, prevalence, mortality, disability, and the understanding of risk factors and primary stroke prevention strategies over the last few decades. Likely future directions of stroke epidemiology and prevention are outlined.

Lifetime Risk of Stroke and Coronary Heart Disease Deaths According to Blood Pressure Level

Lifetime risk (LTR) provides an absolute risk assessment during the remainder of one’s life. Few studies have focused on the LTRs of stroke and coronary heart disease (CHD), categorized by fine blood pressure in Asian populations. We aimed to assess it using a large database of a meta-analysis with the individual participant data. The present meta-analysis included 107 737 Japanese (42.4% men; mean age, 55.1 years) from 13 cohorts. During the mean follow-up of 15.2±5.3 years (1 559 136 person-years), 1922 died from stroke and 913 from CHD. We estimated risks after adjusting for competing risk of death other than the outcome of interest. The 10-year risk of stroke and CHD deaths at index age of 35 years was ≤1.9% and ≤0.3%, respectively. The LTRs of stroke death at the index age of 35 years (men/women) were 6.1%/4.8% for optimal, 5.7%/6.3% for normal, and 6.6%/6.0% for high-normal blood pressure groups, and 9.1%/7.9% for grade 1, 14.5%/10.3% for grade 2, and 14.6%/14.3% for grade 3 hypertension groups. The LTRs of CHD death similarly elevated with an increase in blood pressure but were lower (≤7.2%) than those of stroke death. In conclusion, blood pressure was clearly associated with an elevated LTR of stroke or CHD death, although the LTR of CHD death was one-half of that of stroke death in an Asian population. These results would help young people with hypertension to adopt a healthy lifestyle or start antihypertensive therapy early.

Global, Regional, and Country-Specific Lifetime Risks of Stroke, 1990 and 2016

BACKGROUND

The lifetime risk of stroke has been calculated in a limited number of selected populations. We sought to estimate the lifetime risk of stroke at the regional, country, and global level using data from a comprehensive study of the prevalence of major diseases.

METHODS

We used the Global Burden of Disease (GBD) Study 2016 estimates of stroke incidence and the competing risks of death from any cause other than stroke to calculate the cumulative lifetime risks of first stroke, ischemic stroke, or hemorrhagic stroke among adults 25 years of age or older. Estimates of the lifetime risks in the years 1990 and 2016 were compared. Countries were categorized into quintiles of the sociodemographic index (SDI) used in the GBD Study, and the risks were compared across quintiles. Comparisons were made with the use of point estimates and uncertainty intervals representing the 2.5th and 97.5th percentiles around the estimate.

RESULTS

The estimated global lifetime risk of stroke from the age of 25 years onward was 24.9% (95% uncertainty interval, 23.5 to 26.2); the risk among men was 24.7% (95% uncertainty interval, 23.3 to 26.0), and the risk among women was 25.1% (95% uncertainty interval, 23.7 to 26.5). The risk of ischemic stroke was 18.3%, and the risk of hemorrhagic stroke was 8.2%. In high-SDI, high-middle-SDI, and low-SDI countries, the estimated lifetime risk of stroke was 23.5%, 31.1% (highest risk), and 13.2% (lowest risk), respectively; the 95% uncertainty intervals did not overlap between these categories. The highest estimated lifetime risks of stroke according to GBD region were in East Asia (38.8%), Central Europe (31.7%), and Eastern Europe (31.6%), and the lowest risk was in eastern sub-Saharan Africa (11.8%). The mean global lifetime risk of stroke increased from 22.8% in 1990 to 24.9% in 2016, a relative increase of 8.9% (95% uncertainty interval, 6.2 to 11.5); the competing risk of death from any cause other than stroke was considered in this calculation.

CONCLUSIONS

In 2016, the global lifetime risk of stroke from the age of 25 years onward was approximately 25% among both men and women. There was geographic variation in the lifetime risk of stroke, with the highest risks in East Asia, Central Europe, and Eastern Europe. (Funded by the Bill and Melinda Gates Foundation.).

Predicting lifetime risk for developing atherosclerotic cardiovascular disease in Chinese population: the China-PAR project

Evidence on the lifetime risk for atherosclerotic cardiovascular disease (ASCVD) is insufficient; yet, estimating an individual's lifetime risk allows for a comprehensive assessment of ASCVD burden. We developed and validated lifetime risk prediction equations for ASCVD using four large and ongoing prospective cohorts of Chinese, the China-PAR project (Prediction for ASCVD Risk in China). Sex-specific equations were developed using two cohorts (as the derivation cohort) of 21,320 participants. Two other independent cohorts with 14,123 and 70,838 participants were used for their external validation, respectively. We evaluated both calibration and discrimination measures for model performance. Furthermore, we estimated ASCVD-free years lost or excess absolute risk attributable to high 10-year risk (≥10.0%) and/or high lifetime risk (≥32.8%). After 12.3 years' follow-up of the derivation cohort, 1048 ASCVD events and 1304 non-ASCVD deaths were identified. Our sex-specific equations had good internal validation, with discriminant C statistics of 0.776 (95% confidence interval [CI]: 0.757-0.794) and 0.801 (95% CI: 0.778-0.825), and calibration χ² of 9.2 (P = 0.418) and 5.6 (P = 0.777) for men and women, respectively. Good external validation was also demonstrated with predicted rates closely matched to the observed ones. Compared with men having both low 10-year and low lifetime risk, men would develop ASCVD 3.0, 4.6 and 8.6 years earlier if they had high 10-year risk alone, high lifetime risk alone, or both high 10-year and high lifetime risk at the index age of 35 years, respectively. We developed well-performed lifetime risk prediction equations that will help to identify those with the greatest potential to avert ASCVD burden after implementation of innovative clinical and public health interventions in China.

Blood pressure, heart rate, and double product in a pooled cohort: the Japan Arteriosclerosis Longitudinal Study

OBJECTIVE

To identify the characteristics of blood pressure (BP), heart rate (HR), and double product in a Japanese population sample.

METHODS

We pooled individual records from 1999 to 2005 for 111 007 participants in 25 community-based cohorts and seven worksite-based cohorts. The data were analyzed to provide information on BP, HR, and double product according to age-sex groups and use of antihypertensive medication.

RESULTS

Average BP was 130/77 mmHg among men and women combined. Among untreated individuals, SBP increased with age, whereas DBP reached a ceiling around the age of 60 years. The average SBP of treated participants was around 140 mmHg, irrespective of age, whereas DBP decreased linearly with age, and 56.4% of treated participants had a BP of 140/90 mmHg or over. HR did not differ across age groups or treatment status. The double product, also called the rate-pressure product, calculated by multiplying the SBP and the HR, increased with age among untreated individuals, whereas it first decreased and then increased with age among treated individuals.

CONCLUSION

Based on these collaborative data, insufficient BP control in Japan, where the average life expectancy is the longest in the world, was seen.

The J-curve Association between Systolic Blood Pressure and Clinical Outcomes in Ischemic Stroke or TIA: The BOSS Study

We aimed to assess the association between systolic blood pressure (SBP) and clinical outcome in 2,397 ischemic stroke (IS) or transient ischemic attack (TIA) patients from the Blood Pressure and Clinical Outcome in TIA or Ischemic Stroke (BOSS) study. BOSS study was a hospital-based, prospective cohort study. The SBP was defined as mean value of 90 days self-measured SBP after onset. Cox proportional hazards models were conducted to test the risk of combined vascular events (CVE) and stroke recurrence among different SBP categories. Restricted cubic splines were used to explore the shape of associations between SBP and clinical outcomes. A J-shaped association of SBP with CVE and stroke recurrence within 90 days was observed (P nonlinearity < 0.001 for both). After adjusting for age, gender, medical history, atrial fibrillation, admission NHISS score, and secondary prevention. The hazard ratios (95% confidence intervals) of SBP <115 and ⩾165 mmHg compared with 125–134 mmHg were 3.45 (1.11–10.66) and 7.20 (2.91–17.80) for CVE, 2.68 (0.75–9.53) and 9.69 (3.86–24.35) for stroke recurrence, respectively. Similar J-shaped relationships were found after 1 year of follow-up. In conclusion, both high and low SBP are associated with poor prognosis in this population.