scholarly journals Utility of single versus sequential measurements of risk factors for prediction of stroke in Chinese adults

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Matthew Chun ◽  
Robert Clarke ◽  
Tingting Zhu ◽  
David Clifton ◽  
Derrick Bennett ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Temporal Trends ◽  
Single Visit ◽  
Risk Estimates ◽  
Incident Cases ◽  
Single Versus ◽  
Sequential Measurements

Abstract Absolute risks of stroke are typically estimated using measurements of cardiovascular disease risk factors recorded at a single visit. However, the comparative utility of single versus sequential risk factor measurements for stroke prediction is unclear. Risk factors were recorded on three separate visits on 13,753 individuals in the prospective China Kadoorie Biobank. All participants were stroke-free at baseline (2004–2008), first resurvey (2008), and second resurvey (2013–2014), and were followed-up for incident cases of first stroke in the 3 years following the second resurvey. To reflect the models currently used in clinical practice, sex-specific Cox models were developed to estimate 3-year risks of stroke using single measurements recorded at second resurvey and were retrospectively applied to risk factor data from previous visits. Temporal trends in the Cox-generated risk estimates from 2004 to 2014 were analyzed using linear mixed effects models. To assess the value of more flexible machine learning approaches and the incorporation of longitudinal data, we developed gradient boosted tree (GBT) models for 3-year prediction of stroke using both single measurements and sequential measurements of risk factor inputs. Overall, Cox-generated estimates for 3-year stroke risk increased by 0.3% per annum in men and 0.2% per annum in women, but varied substantially between individuals. The risk estimates at second resurvey were highly correlated with the annual increase of risk for each individual (men: r = 0.91, women: r = 0.89), and performance of the longitudinal GBT models was comparable with both Cox and GBT models that considered measurements from only a single visit (AUCs: 0.779–0.811 in men, 0.724–0.756 in women). These results provide support for current clinical guidelines, which recommend using risk factor measurements recorded at a single visit for stroke prediction.

Abstract MP74: Long Term Risk-Factor Profiles for Chronic Kidney Disease in the Framingham Heart Study

Circulation ◽  
2013 ◽  
Vol 127 (suppl_12) ◽  
Author(s):  
Gearoid M McMahon ◽  
Sarah R Preis ◽  
Shih-Jen Hwang ◽  
Caroline S Fox
Keyword(s):  
Risk Factors ◽  
Chronic Kidney Disease ◽  
Risk Factor ◽  
Kidney Disease ◽  
Framingham Heart Study ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Standard Deviation Increase ◽  
Heart Study ◽  
Increased Risk

Background: Chronic Kidney Disease (CKD) is an important public health issue and is associated with an increased risk of cardiovascular disease. Risk factors for CKD are well established, but most are typically assessed at or near the time of CKD diagnosis. Our hypothesis was that risk factors for CKD are present earlier in the course of the disease. We compared the prevalence of risk factors between CKD cases and controls at time points up to 30 years prior to CKD diagnosis. Methods: Participants were drawn from the Framingham Heart Study Offspring cohort. CKD was defined as an estimated glomerular filtration rate of ≤60ml/min/1.73m2. Incident CKD cases occurring at examination cycles 6, 7, and 8 were age- and sex-matched 1:2 to controls. Risk factors including systolic blood pressure (SBP), hypertension, lipids, diabetes, smoking status, body mass index (BMI) and dipstick proteinuria were measured at the time of CKD diagnosis and 10, 20 and 30 years prior. Logistic regression models, adjusted for age, sex, and time period, were constructed to compare risk factor profiles at each time point between cases and controls Results: During follow-up, 441 new cases of CKD were identified and these were matched to 882 controls (mean age 69.2 years, 52.4% women). Up to 30 years prior to CKD diagnosis, those who ultimately developed CKD were more likely to have hypertension (OR 1.74, CI 1.21-2.49), be obese (OR 1.74, CI 1.15-2.63) and have higher triglycerides (OR 1.43, CI 1.12-1.84, p=0.005 per 1 standard deviation increase). Each 10mmHg increase in SBP was associated with an OR of 1.22 for future CKD (95% CI 1.10-1.35) Additionally, cases were more likely to have diabetes (OR 2.90, CI 1.59-5.29) and be on antihypertensive therapy (OR 1.65, CI 1.14-2.40, p=0.009) up to 20 years prior to diagnosis. Increasing HDLc was associated with a lower risk of CKD (OR 0.84, CI 0.81-0.97 per 10mg/dl). Conclusions: As many as 30 years prior to diagnosis, risk factors for CKD are identifiable. In particular, modifiable risk factors such as obesity, hypertension and dyslipidemia are present early in the course of the disease. These findings demonstrate the importance of early identification of risk factors in patients at risk of CKD through a life-course approach.

scholarly journals Identification of Endothelial Proteins in Plasma Associated With Cardiovascular Risk Factors

2021 ◽  
Author(s):  
Maria J. Iglesias ◽  
Larissa D. Kruse ◽  
Laura Sanchez-Rivera ◽  
Linnea Enge ◽  
Philip Dusart ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Body Mass Index ◽  
Risk Factor ◽  
Total Cholesterol ◽  
Body Mass ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Cardiovascular Disease Risk Factor ◽  
Venous Disease

Objective: Endothelial cell (EC) dysfunction is a well-established response to cardiovascular disease risk factors, such as smoking and obesity. Risk factor exposure can modify EC signaling and behavior, leading to arterial and venous disease development. Here, we aimed to identify biomarker panels for the assessment of EC dysfunction, which could be useful for risk stratification or to monitor treatment response. Approach and Results: We used affinity proteomics to identify EC proteins circulating in plasma that were associated with cardiovascular disease risk factor exposure. Two hundred sixteen proteins, which we previously predicted to be EC-enriched across vascular beds, were measured in plasma samples (n=1005) from the population-based SCAPIS (Swedish Cardiopulmonary Bioimage Study) pilot. Thirty-eight of these proteins were associated with body mass index, total cholesterol, low-density lipoprotein, smoking, hypertension, or diabetes. Sex-specific analysis revealed that associations predominantly observed in female- or male-only samples were most frequently with the risk factors body mass index, or total cholesterol and smoking, respectively. We show a relationship between individual cardiovascular disease risk, calculated with the Framingham risk score, and the corresponding biomarker profiles. Conclusions: EC proteins in plasma could reflect vascular health status.

scholarly journals Inequalities in the Distribution of Cardiovascular Disease Risk Factors in Argentina. A Study from the 2005, 2009 and 2013 National Risk Factor Survey (NRFS)

2016 ◽  
Vol 84 (2) ◽  
pp. 133-139
Author(s):  
Daniel Ferrante ◽  
Natalia Jörgensen ◽  
Martín Langsam ◽  
Cynthia Marchioni ◽  
Santiago Torales ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Risk Factor ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Cardiovascular Disease Risk Factors

Cycling and cardiovascular disease risk factors including body composition, blood lipids and cardiorespiratory fitness analysed as continuous variables: Part 2—systematic review with meta-analysis

2019 ◽  
Vol 53 (14) ◽  
pp. 879-885 ◽  
Author(s):  
Solveig Nordengen ◽  
Lars Bo Andersen ◽  
Ane K Solbraa ◽  
Amund Riiser
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Body Composition ◽  
Risk Factor ◽  
Cardiorespiratory Fitness ◽  
Blood Lipids ◽  
Disease Risk ◽  
Meta Analysis ◽  
Cardiovascular Disease Risk ◽  
Continuous Variables

ObjectivesWe aimed to examine the relationship between cycling (particularly commuter cycling) and risk factors associated with cardiovascular diseases (CVDs) including body composition, blood lipids and cardiorespiratory fitness. This study differed from our recent (Part 1) systematic review in that risk factors for CVD were analysed as continuous variables rather than being present or absent.DesignSystematic review and meta-analysis.Eligibility criteriaWe searched four databases (Web of Science, MEDLINE, SPORTDiscus and Scopus). All quantitative studies, published until August 2017, were included when a general population was investigated, cycling was assessed either in total or as a transportation mode, and CVD risk factors were reported.MethodsWe analysed body composition, physical activity (PA), cardiorespiratory fitness (CRF), blood lipids and blood pressure (BP). Skinfold, waist circumference and body mass index were analysed and prioritised in that order when more than one measure were available. PA included measures of counts per minutes, moderate-to-vigorous PA or minutes per week. CRF included results of maximal tests with or without expired air or submaximal test. For blood lipids and BP, separate analyses were run for low-density and high-density lipoprotein, triglycerides, total cholesterol, systolic BP and diastolic BP. Studies were excluded when reporting dichotomous outcomes or when cycling and walking were combined. Heterogeneity was investigated using I2.ResultsFifteen studies were included; the majority reported commuter cycling. In total, we included 5775 cyclists and 39 273 non-cyclists. Cyclists had more favourable risk factor levels in body composition −0.08 (95% CI −0.13 to −0.04), PA 0.13 (95% CI 0.06 to 0.20), CRF 0.28 (95% CI 0.22 to 0.35) and blood lipids compared with non-cyclists. There was no sex difference in risk reduction.Conclusion/implicationCycling mitigated the risk factor profile for CVD. A strength of this systematic review is that all the risk factors were analysed as continuous variables. These data provide evidence for practitioners, stakeholders, policy-makers and city planners to accommodate and promote cycling.Systematic review registrationPROSPERO CRD42016052421.

scholarly journals Association of antecedent cardiovascular risk factor levels and trajectories with cardiovascular magnetic resonance-derived cardiac function and structure

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Roberto Lorbeer ◽  
Susanne Rospleszcz ◽  
Christopher L. Schlett ◽  
Sophia D. Rado ◽  
Barbara Thorand ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Cardiac Function ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Individual Risk ◽  
The Individual ◽  
And Function ◽  
Individual Risk Factors

Abstract Background The association of longitudinal trajectories of cardiovascular risk factors with cardiovascular magnetic resonance (CMR)-measures of cardiac structure and function in the community is not well known. Therefore we aimed to relate risk factor levels from different examination cycles to CMR-measures of the left ventricle (LV) and right ventricle in a population-based cohort. Methods We assessed conventional cardiovascular disease risk factors in 349 participants (143 women; aged 25–59 years) at three examination cycles (Exam 1 [baseline], at Exam 2 [7-years follow-up] and at Exam 3 [14-years follow-up]) of the KORA S4 cohort and related single-point measurements of individual risk factors and longitudinal trajectories of these risk factors to various CMR-measures obtained at Exam 3. Results High levels of diastolic blood pressure, waist circumference, and LDL-cholesterol at the individual exams were associated with worse cardiac function and structure. Trajectory clusters representing higher levels of the individual risk factors were associated with worse cardiac function and structure compared to low risk trajectory clusters of individual risk factors. Multivariable (combining different risk factors) trajectory clusters were associated with different cardiac parameters in a graded fashion (e.g. decrease of LV stroke volume for middle risk cluster β = − 4.91 ml/m2, 95% CI − 7.89; − 1.94, p < 0.01 and high risk cluster β = − 7.00 ml/m2, 95% CI − 10.73; − 3.28, p < 0.001 compared to the low risk cluster). The multivariable longitudinal trajectory clusters added significantly to explain variation in CMR traits beyond the multivariable risk profile obtained at Exam 3. Conclusions Cardiovascular disease risk factor levels, measured over a time period of 14 years, were associated with CMR-derived measures of cardiac structure and function. Longitudinal multivariable trajectory clusters explained a greater proportion of the inter-individual variation in cardiac traits than multiple risk factor assessed contemporaneous with the CMR exam.

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