34 results on '"10-year risk"'
Search Results
2. Framingham risk scores for determination the 10-year risk of cardiovascular disease in participants with and without the metabolic syndrome: results of the Fasa Persian cohort study.
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Dehghan, Azizallah, Jahangiry, Leila, Khezri, Rozhan, Jafari, Alireza, Pezeshki, Babak, Rezaei, Fatemeh, and Aune, Dagfinn
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CARDIOVASCULAR disease prevention , *RISK assessment , *CROSS-sectional method , *HIGH density lipoproteins , *CARDIOVASCULAR diseases , *RESEARCH funding , *SEX distribution , *SMOKING , *MULTIPLE regression analysis , *CARDIOVASCULAR diseases risk factors , *AGE distribution , *DESCRIPTIVE statistics , *LONGITUDINAL method , *WAIST circumference , *METABOLIC syndrome , *CHOLESTEROL , *SYSTOLIC blood pressure , *TRIGLYCERIDES , *DIABETES - Abstract
Background: Metabolic syndrome (MetS) is a cluster of risk factors and the Framingham risk score (FRS) is a useful metric for measuring the 10-year cardiovascular disease (CVD) risk of the population. The present study aimed to determine the 10-year risk of cardiovascular disease using the Framingham risk score in people with and without MetS in a large Iranian cohort study. Methods: This cross-sectional study was done using the Fasa cohort. Participants aged ≥ 35 years old were recruited to the study from 2015 to 2016. The FRS was calculated using age, sex, current smoking, diabetes, systolic blood pressure (SBP), total cholesterol, and high-density lipoprotein (HDL) cholesterol. MetS was defined as the presence of three or more of the MetS risk factors including triglyceride (TG) level ≥ 150 mg dl− 1, HDL level < 40 mg dl− 1 in men and < 50 mg dl− 1 in women, systolic/diastolic blood pressure ≥ 130/≥85 mmHg or using medicine for hypertension, fasting blood sugar (FBS) level ≥ 100 mg dl− 1 or using diabetes medication and abdominal obesity considered as waist circumference (WC) ≥ 88 cm for women and ≥ 102 cm for men. Multiple logistic regressions were applied to estimate the 10- year CVD risk among people with and without MetS. Results: Of 8949 participants, 1928 people (21.6%) had MetS. The mean age of the participants with and without Mets was 50.4 ± 9.2 years and 46.9 ± 9.1 years respectively. In total 15.3% of participants with MetS and 8.0% of participants without MetS were in the high-risk category of 10-year CVD risk. Among participants with MetS gender, TG, SBP, FBS and in people without MetS gender, TG, SBP, FBS, and HDL showed strong associations with the predicted 10-year CVD risk. Conclusion: Male sex and increased SBP, TG, and FBS parameters were strongly associated with increased 10-year risk of CVD in people with and without MetS. In people without MetS, reduced HDL-cholestrol was strongly associated with increased 10-year risk of CVD. The recognition of participant's TG, blood pressure (BP), FBS and planning appropriate lifestyle interventions related to these characteristics is an important step towards prevention of CVD. [ABSTRACT FROM AUTHOR]
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- 2024
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3. Associations of risk factor burden and genetic predisposition with the 10-year risk of atrial fibrillation: observations from a large prospective study of 348,904 participants
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Junguo Zhang, Ge Chen, ChongJian Wang, Xiaojie Wang, Zhengmin (Min) Qian, Miao Cai, Michael G. Vaughn, Elizabeth Bingheim, Haitao Li, Yanhui Gao, Gregory Y. H. Lip, and Hualiang Lin
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Risk factor burden ,Genetic predisposition ,Atrial fibrillation ,10-year risk ,Medicine - Abstract
Abstract Background Understanding the effects of risk factor burden and genetic predisposition on the long-term risk of atrial fibrillation (AF) is important to improve public health initiatives. However, the 10-year risk of AF considering risk factor burden and genetic predisposition is unknown. Methods A total of 348,904 genetically unrelated participants without AF at baseline from the UK were categorized into three groups: index ages 45 years (n = 84,206), 55 years (n=117,520), and 65 years (n=147,178). Optimal, borderline, or elevated risk factor burden was determined by body mass index, blood pressure, diabetes mellitus, alcohol consumption, smoking status, and history of myocardial infarction or heart failure. Genetic predisposition was estimated using the polygenic risk score (PRS), constructed using 165 predefined genetic risk variants. The combined effects of risk factor burden and PRS on the risk of incident AF in 10 years were estimated for each index age. Fine and Gray models were developed to predict the 10-year risk of AF. Results The overall 10-year risk of AF was 0.67% (95% CI: 0.61–0.73%) for index age 45 years, 2.05% (95% CI: 1.96–2.13%) for index age 55 years, and 6.34% (95% CI: 6.21–6.46%) for index age 65 years, respectively. An optimal risk factor burden was associated with later AF onset regardless of genetic predisposition and sex (P < 0.001). Significant synergistic interactions were observed for risk factor burden with PRS at each index age (P < 0.05). Participants with an elevated risk factor burden and high PRS had the highest 10-year risk of AF in reference to those who had both an optimal risk factor burden and a low PRS. At younger ages, optimal risk burden and high PRS might also lead to later onset of AF, compared to the joint effect of elevated risk burden and low/intermediate PRS. Conclusions Risk factor burden together with a genetic predisposition is associated with the 10-year risk of AF. Our results may be helpful in selecting high-risk individuals for primary prevention of AF and facilitating subsequent health interventions.
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- 2023
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4. Associations of risk factor burden and genetic predisposition with the 10-year risk of atrial fibrillation: observations from a large prospective study of 348,904 participants.
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Zhang, Junguo, Chen, Ge, Wang, ChongJian, Wang, Xiaojie, Qian, Zhengmin, Cai, Miao, Vaughn, Michael G., Bingheim, Elizabeth, Li, Haitao, Gao, Yanhui, Lip, Gregory Y. H., and Lin, Hualiang
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ATRIAL fibrillation , *HEART failure , *DISEASE risk factors , *MYOCARDIAL infarction , *AGE groups , *LONGITUDINAL method - Abstract
Background: Understanding the effects of risk factor burden and genetic predisposition on the long-term risk of atrial fibrillation (AF) is important to improve public health initiatives. However, the 10-year risk of AF considering risk factor burden and genetic predisposition is unknown. Methods: A total of 348,904 genetically unrelated participants without AF at baseline from the UK were categorized into three groups: index ages 45 years (n = 84,206), 55 years (n=117,520), and 65 years (n=147,178). Optimal, borderline, or elevated risk factor burden was determined by body mass index, blood pressure, diabetes mellitus, alcohol consumption, smoking status, and history of myocardial infarction or heart failure. Genetic predisposition was estimated using the polygenic risk score (PRS), constructed using 165 predefined genetic risk variants. The combined effects of risk factor burden and PRS on the risk of incident AF in 10 years were estimated for each index age. Fine and Gray models were developed to predict the 10-year risk of AF. Results: The overall 10-year risk of AF was 0.67% (95% CI: 0.61–0.73%) for index age 45 years, 2.05% (95% CI: 1.96–2.13%) for index age 55 years, and 6.34% (95% CI: 6.21–6.46%) for index age 65 years, respectively. An optimal risk factor burden was associated with later AF onset regardless of genetic predisposition and sex (P < 0.001). Significant synergistic interactions were observed for risk factor burden with PRS at each index age (P < 0.05). Participants with an elevated risk factor burden and high PRS had the highest 10-year risk of AF in reference to those who had both an optimal risk factor burden and a low PRS. At younger ages, optimal risk burden and high PRS might also lead to later onset of AF, compared to the joint effect of elevated risk burden and low/intermediate PRS. Conclusions: Risk factor burden together with a genetic predisposition is associated with the 10-year risk of AF. Our results may be helpful in selecting high-risk individuals for primary prevention of AF and facilitating subsequent health interventions. [ABSTRACT FROM AUTHOR]
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- 2023
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5. Association between dietary fiber intake and atherosclerotic cardiovascular disease risk in adults: a cross-sectional study of 14,947 population based on the National Health and Nutrition Examination Surveys
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Shutang Zhang, Jie Tian, Min Lei, Canye Zhong, and Yan Zhang
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Dietary fiber intake ,Framingham risk score ,Cardiovascular disease ,10-year risk ,Public aspects of medicine ,RA1-1270 - Abstract
Abstract Background This study aimed to investigate the association between dietary fiber intake and long-term cardiovascular disease (CVD) risk based on the National Health and Nutrition Examination Survey (NHANES) database. Methods A total of 14,947 participants aged 20–79 from the NHANES database were included in this study between 2009 and 2018. The atherosclerotic cardiovascular disease (ASCVD) score was utilized to predict the 10-year risk of CVD in individuals (low, borderline, intermediate, and high risk). Weighted univariate and multinomial multivariate logistic regression analyses were used to analyze the association between dietary fiber intake and long-term CVD risk. Results Higher dietary fiber density may be associated with a reduced ASCVD risk in participants with intermediate risk [odds ratio (OR) = 0.76; 95% confidence interval (CI), 0.61–0.94] and high risk (OR = 0.60; 95%CI, 0.45–0.81) compared with those in the group with low risk. Higher total dietary fiber intake may also reduce ASCVD risk in participants with high risk (OR = 0.84; 95%CI, 0.75–0.95). Subgroup analyses showed that higher dietary fiber density may be related to reduced ASCVD risk in intermediate-risk participants aged 20–39 (OR = 0.62; 95%CI, 0.43–0.89) and 40–59 (OR = 0.67; 95%CI, 0.49–0.94). In high-risk participants, higher dietary fiber density may reduce ASCVD risk in 20–39-year-old (OR = 0.38; 95%CI, 0.19–0.77), 40–59-year-old (OR = 0.37; 95%CI, 0.20–0.70), male (OR = 0.47; 95%CI, 0.23–0.97) and female (OR = 0.57; 95%CI, 0.38–0.86) participants. Conclusion Higher dietary fiber density and total dietary fiber intake were associated with a lower long-term CVD risk, especially in the 20–39 and 40–59 age groups, where the reduction was most significant.
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- 2022
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6. Triglyceride-glucose index and estimated 10-year risk of a first hard cardiovascular event
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Hua Qu, Lin-zi Long, Li Chen, Han-tao Wu, Chang-geng Fu, and Shan-shan Zhang
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TyG index ,10-year risk ,atherosclerotic cardiovascular disease ,NHANES ,cross-sectional study ,Diseases of the circulatory (Cardiovascular) system ,RC666-701 - Abstract
BackgroundWhether Triglyceride-glucose (TyG) index is associated with 10-year risk of a first hard atherosclerotic cardiovascular disease (ASCVD) event in the United States remains unclear.MethodsIn this cross-sectional study, the participants, ranged from 40 to 79 years old, were from the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018. TyG index was the independent variable and 10-year risk of a first hard ASCVD was the dependent variable. The other variables, such as age, gender, race, body mass index (BMI), hypertension treatment states, smoking states and low-density lipoprotein cholesterol (LDL-C) et al. were considered as the potential confounding factors. Multivariate linear regression models and smooth curve fittings were used to evaluate the association between TyG index and 10-year risk of a first hard ASCVD event.ResultsA total of 2,142 participants were included in the analysis. The results showed that TyG index was associated with an increased 10-year risk of a first hard ASCVD event [β = 2.208, 95% (1.716, 2.700), P < 0.00001]. The association had statistical significance in both men [β = 3.862 95% CI (3.274, 4.450), P < 0.00001] and women [β = 1.067, 95% CI (0.286, 1.849), P = 0.00756)] according to subgroup analysis. Smooth curve fittings revealed that TyG index was linearly associated with 10-year risk of ASCVD in both male and female.ConclusionTriglyceride-glucose index was associated with an increased 10-year risk of a first hard ASCVD event in the United States, suggesting it is necessary to monitor and control an appropriate range of TyG index.
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- 2023
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7. Association between dietary magnesium and 10-year risk of a first hard atherosclerotic cardiovascular disease event.
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Yang Z, Zhang Y, Gao J, Yang Q, Qu H, and Shi J
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- Humans, Middle Aged, Male, Female, Cross-Sectional Studies, Aged, Adult, Risk Factors, Nutrition Surveys, Diet, Cardiovascular Diseases epidemiology, Cardiovascular Diseases etiology, Magnesium administration & dosage, Atherosclerosis epidemiology
- Abstract
Background: To test whether dietary magnesium is associated with 10-year risk of a first hard atherosclerotic cardiovascular disease event., Methods: In this cross-sectional study, a total of 2980 participants, aged 40 to 79 years, from the National Health and Nutrition Examination Survey 1999-2018 were analyzed. The association between dietary magnesium and 10-year risk of a first hard atherosclerotic cardiovascular disease (ASCVD) event was assessed following adjustment for clinical risk factors, including sex, age, race, educational level, body mass index (BMI), alcohol drinking, smoking, systolic blood pressure (SBP), diastolic blood pressure (DBP), hypertension treated or not, diabetes and low density lipoprotein cholesterol (LDL-C), total energy and dietary fiber. We performed multivariate linear regression models and smooth curve fittings to evaluate the associations between dietary magnesium and 10-year risk of a first hard atherosclerotic cardiovascular disease event., Results: We observed a significant inverse association between dietary magnesium and predicted 10-year risk of a first hard atherosclerotic cardiovascular disease event (β=-0.01, [95% CI: -0.01, -0.00], P = 0.0256). We divided the 10-year risk into two categories, with a statistically significant reduction of ASCVD risk when the 10-year risk ≥7.5% (β=-0.01, [95% CI: -0.01, -0.00], P = 0.0440)., Conclusions: Dietary magnesium intake was inversely associated with the predicted 10-year risk of a first hard atherosclerotic cardiovascular disease event., Competing Interests: Competing interests The authors declare that they have no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
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- 2024
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8. Association between dietary fiber intake and atherosclerotic cardiovascular disease risk in adults: a cross-sectional study of 14,947 population based on the National Health and Nutrition Examination Surveys.
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Zhang, Shutang, Tian, Jie, Lei, Min, Zhong, Canye, and Zhang, Yan
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CARDIOVASCULAR disease prevention , *ATHEROSCLEROSIS prevention , *DIETARY fiber , *CROSS-sectional method , *CARDIOVASCULAR diseases , *ATHEROSCLEROSIS , *SURVEYS - Abstract
Background: This study aimed to investigate the association between dietary fiber intake and long-term cardiovascular disease (CVD) risk based on the National Health and Nutrition Examination Survey (NHANES) database.Methods: A total of 14,947 participants aged 20-79 from the NHANES database were included in this study between 2009 and 2018. The atherosclerotic cardiovascular disease (ASCVD) score was utilized to predict the 10-year risk of CVD in individuals (low, borderline, intermediate, and high risk). Weighted univariate and multinomial multivariate logistic regression analyses were used to analyze the association between dietary fiber intake and long-term CVD risk.Results: Higher dietary fiber density may be associated with a reduced ASCVD risk in participants with intermediate risk [odds ratio (OR) = 0.76; 95% confidence interval (CI), 0.61-0.94] and high risk (OR = 0.60; 95%CI, 0.45-0.81) compared with those in the group with low risk. Higher total dietary fiber intake may also reduce ASCVD risk in participants with high risk (OR = 0.84; 95%CI, 0.75-0.95). Subgroup analyses showed that higher dietary fiber density may be related to reduced ASCVD risk in intermediate-risk participants aged 20-39 (OR = 0.62; 95%CI, 0.43-0.89) and 40-59 (OR = 0.67; 95%CI, 0.49-0.94). In high-risk participants, higher dietary fiber density may reduce ASCVD risk in 20-39-year-old (OR = 0.38; 95%CI, 0.19-0.77), 40-59-year-old (OR = 0.37; 95%CI, 0.20-0.70), male (OR = 0.47; 95%CI, 0.23-0.97) and female (OR = 0.57; 95%CI, 0.38-0.86) participants.Conclusion: Higher dietary fiber density and total dietary fiber intake were associated with a lower long-term CVD risk, especially in the 20-39 and 40-59 age groups, where the reduction was most significant. [ABSTRACT FROM AUTHOR]- Published
- 2022
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9. The Association Between Remnant Cholesterol and the Estimated 10-Year Risk of a First Hard Cardiovascular Event
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Zhen Yang, Kuo Yang, Junhe Shi, Qiaoning Yang, Ying Zhang, Jie Gao, Dazhuo Shi, and Hua Qu
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Remnant cholesterol ,10-year risk ,atherosclerotic cardiovascular disease ,NHANES ,cross-sectional study ,Diseases of the circulatory (Cardiovascular) system ,RC666-701 - Abstract
BackgroundRemnant cholesterol (Remnant-C), rather than TG, is believed to increase the risk of atherosclerotic cardiovascular disease. We evaluated whether Remnant-C is associated with an estimated 10-year risk of a first hard atherosclerotic cardiovascular disease event.MethodsThis cross-sectional study was performed on 2,048 participants (1,130 men and 918 women), aged 40 to 79 years, from the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018. The independent variable was Remnant-C; the dependent variable was the 10-year risk of a first hard atherosclerotic cardiovascular disease event (defined as non-fatal myocardial infarction, coronary heart disease death, or stroke, over a 10-year period among people free from atherosclerotic cardiovascular disease at the beginning of the period). The other variables, such as smoking behavior, hypertension, diabetes etc., were considered as the potential effect modifiers. Multivariate linear regression models and smooth curve fittings were used to evaluate the association between Remnant-C and the 10-year risk of a first hard atherosclerotic cardiovascular disease event. Subgroup analyses stratified by gender and race were also performed.ResultsA positive association between Remnant-C and the 10-year risk of a first hard atherosclerotic cardiovascular disease event was demonstrated in the fully adjusted model (β = 0.078, [95%CI: 0.061–0.094], P < 0.001). The 10-year risk was increased by 0.078% for each 1 mg/dl increase in Remnant-C. In the subgroup analysis for gender, this association remained in both men (β = 0.128, [95%CI: 0.108–0.148], P < 0.001) and women (β = 0.043, [95%CI: 0.016–0.070], P = 0.00179). However, in the subgroup analysis for race, the association between Remnant-C and the 10-year risk reached an inflection point at remnant-C 38 mg/dL, where a positive association was not as obvious for the non-Hispanic Black population as for other racial groups.ConclusionsRemnant-C positively correlates with a 10-year risk of a first hard atherosclerotic cardiovascular disease event.
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- 2022
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10. Does the Carotid Bulb Offer a Better 10-Year CVD/Stroke Risk Assessment Compared to the Common Carotid Artery? A 1516 Ultrasound Scan Study.
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Viswanathan, Vijay, Jamthikar, Ankush D., Gupta, Deep, Puvvula, Anudeep, Khanna, Narendra N., Saba, Luca, Viskovic, Klaudija, Mavrogeni, Sophie, Laird, John R., Pareek, Gyan, Miner, Martin, Sfikakis, Petros P., Protogerou, Athanasios, Sharma, Aditya, Kancharana, Priyanka, Misra, Durga Prasanna, Agarwal, Vikas, Kitas, George D., Nicolaides, Andrew, and Suri, Jasjit S.
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ATHEROSCLEROSIS complications , *CARDIOVASCULAR diseases risk factors , *CAROTID artery , *CAROTID artery diseases , *CHRONIC kidney failure , *HYPERTENSION , *MEDICAL records , *TYPE 2 diabetes , *RISK assessment , *STROKE , *PHENOTYPES , *RETROSPECTIVE studies , *DESCRIPTIVE statistics , *ACQUISITION of data methodology , *DISEASE complications - Abstract
The objectives of this study are to (1) examine the "10-year cardiovascular risk" in the common carotid artery (CCA) versus carotid bulb using an integrated calculator called "AtheroEdge Composite Risk Score 2.0" (AECRS2.0) and (2) evaluate the performance of AECRS2.0 against "conventional cardiovascular risk calculators." These objectives are met by measuring (1) image-based phenotypes and AECRS2.0 score computation and (2) performance evaluation of AECRS2.0 against 12 conventional cardiovascular risk calculators. The Asian–Indian cohort (n = 379) with type 2 diabetes mellitus (T2DM), chronic kidney disease (CKD), or hypertension were retrospectively analyzed by acquiring the 1516 carotid ultrasound scans (mean age: 55 ± 10.1 years, 67% males, ∼92% with T2DM, ∼83% with CKD [stage 1-5], and 87.5% with hypertension [stage 1-2]). The carotid bulb showed a higher 10-year cardiovascular risk compared to the CCA by 18% (P <.0001). Patients with T2DM and/or CKD also followed a similar trend. The carotid bulb demonstrated a superior risk assessment compared to CCA in patients with T2DM and/or CKD by showing: (1) ∼13% better than CCA (0.93 vs 0.82, P =.0001) and (2) ∼29% better compared with 12 types of risk conventional calculators (0.93 vs 0.72, P =.06). [ABSTRACT FROM AUTHOR]
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- 2020
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11. Statin Eligibility for Primary Prevention of Cardiovascular Disease According to 2021 European Prevention Guidelines Compared With Other International Guidelines
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Mortensen, Martin Bødtker, Tybjærg-Hansen, Anne, and Nordestgaard, Børge G
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10-YEAR RISK ,RISK THRESHOLDS ,American Heart Association ,AMERICAN-COLLEGE ,Atherosclerosis ,THERAPY ,VALIDATION ,United States ,Cohort Studies ,Primary Prevention ,CLINICAL-PRACTICE ,Cardiovascular Diseases ,SCORE ,Humans ,ASSOCIATION TASK-FORCE ,SOCIETIES ,Hydroxymethylglutaryl-CoA Reductase Inhibitors ,Cardiology and Cardiovascular Medicine ,Original Investigation - Abstract
Importance: For primary prevention of atherosclerotic cardiovascular disease (ASCVD), the 2021 European Society of Cardiology (ESC) guidelines on statin use (hereafter European-ESC) recommend a new risk model (Systematic Coronary Risk Evaluation 2 [European-SCORE2]) as well as new age-specific treatment thresholds (≥7.5% 10-year ASCVD risk if aged 40-49 years and ≥10% if aged 50-69 years).Objective: To compare the clinical performance of the 2021 European-ESC, American College of Cardiology/American Heart Association (hereafter US-ACC/AHA), UK National Institute for Health and Care Excellence (UK-NICE), and 2019 ESC/European Atherosclerosis Society (EAS) guidelines in apparently healthy individuals.Design, Setting, and Participants: This population-based contemporary cohort study included 66 909 individuals from the Copenhagen General Population Study. Participants were aged 40 to 69 years and were free of ASCVD, diabetes, chronic kidney disease, and statin use at baseline in 2003 to 2015. Mean follow-up time was 9.2 years. Data were analyzed from November 2021 to April 2022.Exposures: Statin treatment according to guideline criteria.Main Outcomes and Measures: Calibration of risk calculators, statin eligibility, sensitivity, and specificity for ASCVD events according to guideline criteria.Results: During follow-up, a range of 2962 to 4277 nonfatal and fatal ASCVD events was observed, as defined by the 2021 European-SCORE2, US pooled cohort equations (PCE), and UK-QRISK3 models, and 180 fatal ASCVD events were noted as defined by the 2019 European-SCORE1 model. European-SCORE2 was slightly better calibrated with a predicted/observed ASCVD event ratio of 0.8 vs 1.3 for US-PCE, 1.3 for UK-QRISK3, and 5.8 for European-SCORE1. For primary prevention class I recommendations in individuals aged 40 to 69 years, 2862 of 66 909 (4%) qualified for statins according to the 2021 European-ESC guidelines compared with 23 029 (34%) with US-ACC/AHA, 17 659 (26%) with UK-NICE, and 13 496 (20%) with 2019 European-ESC/EAS guidelines, with associated sensitivities for detecting future European-SCORE2-defined ASCVD events of 12%, 60%, 51%, and 36%, respectively. The sensitivity of the European-ESC guidelines was improved considerably by lowering the treatment thresholds, resulting in smaller losses in specificity. To obtain similar clinical performance with the 2021 European-ESC guidelines as in the other guidelines, the threshold with European-SCORE2 should be reduced to 5% overall to match US-ACC/AHA, to 6% to match UK-NICE, and to 7% to match 2019 European-ESC/EAS guidelines.Conclusions and Relevance: Despite an improved European-SCORE2 prediction model, the new treatment thresholds in the 2021 European-ESC guidelines dramatically reduce eligibility for primary prevention with statins in low-risk European countries. Using lower treatment thresholds can improve overall guideline performance.
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- 2023
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12. Dietary Saturated, Monounsaturated, or Polyunsaturated Fatty Acids and Estimated 10-Year Risk of a First Hard Cardiovascular Event.
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Yang, Zhen, Yang, Kuo, Zhang, Xuan, Yang, Qiaoning, Zhang, Ying, Gao, Jie, Qu, Hua, and Shi, Junhe
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UNSATURATED fatty acids , *MONOUNSATURATED fatty acids , *SATURATED fatty acids , *HEALTH & Nutrition Examination Survey , *FATTY acids - Abstract
The effects of dietary saturated, monounsaturated, or polyunsaturated fatty acids on the risk of cardiovascular events remain controversial. This cross-sectional study was performed in 4211 patients, aged 40 to 79 years, from the National Health and Nutrition Examination Survey between 1999 and 2018. The independent variables were saturated fatty acids, monounsaturated fatty acids, and polyunsaturated fatty acids. The dependent variable was the 10-year risk of a first hard atherosclerotic cardiovascular event. The other variables were considered as the potential confounding factors. Multivariate linear regression models and smooth curve fittings were used to evaluate the association between saturated fatty acids, polyunsaturated fatty acids, or monounsaturated fatty acids and the 10-year risk. There was no association between dietary saturated fatty acids and 10-year risk after adjusting for all the potential confounding factors; 10-year risk decreased by 0.022% each 1-g increase in monounsaturated fatty acids intake from 0 to 153.772 g, and 0.025% each 1-g increase in polyunsaturated fatty acids intake from 0 to 98.323 g, respectively. Moreover, subgroup analysis showed that monounsaturated fatty acids and polyunsaturated fatty acids were both negatively correlated to 10-year risk in nondiabetes and non-high–low-density lipoprotein patients; monounsaturated fatty acids were also negatively associated with 10-year risk in hypertensive patients. There was no association between dietary saturated fatty acids and 10-year risk. Increased dietary intake of monounsaturated fatty acids or polyunsaturated fatty acids decreased 10-year risk, particularly in nondiabetes, non-high-low density lipoprotein patients. [ABSTRACT FROM AUTHOR]
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- 2023
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13. Does the Carotid Bulb Offer a Better 10-Year CVD/Stroke Risk Assessment Compared to the Common Carotid Artery? A 1516 Ultrasound Scan Study
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Vikas Agarwal, Luca Saba, Klaudija Višković, Jasjit S. Suri, Aditya Sharma, Andrew Nicolaides, Petros P. Sfikakis, Durga Prasanna Misra, Priyanka Kancharana, Vijay Viswanathan, Martin Miner, George D Kitas, Sophie Mavrogeni, Gyan Pareek, Deep Gupta, John R Laird, Athanasios Protogerou, Narendra N. Khanna, Anudeep Puvvula, and Ankush D Jamthikar
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Adult ,Male ,medicine.medical_specialty ,Carotid Artery, Common ,India ,Type 2 diabetes ,030204 cardiovascular system & hematology ,Carotid Intima-Media Thickness ,Risk Assessment ,03 medical and health sciences ,0302 clinical medicine ,Asian People ,Internal medicine ,medicine.artery ,medicine ,Humans ,Common carotid artery ,Renal Insufficiency, Chronic ,Stage (cooking) ,Aged ,Retrospective Studies ,Framingham Risk Score ,business.industry ,Type 2 Diabetes Mellitus ,Middle Aged ,medicine.disease ,10-year risk ,atherosclerosis ,cardiovascular risk ,carotid bulb ,chronic kidney disease ,common carotid artery ,risk assessment ,type 2 diabetes ,Stroke ,Diabetes Mellitus, Type 2 ,Hypertension ,Cohort ,Cardiology ,Female ,Cardiology and Cardiovascular Medicine ,Risk assessment ,business ,030217 neurology & neurosurgery ,Kidney disease - Abstract
The objectives of this study are to (1) examine the “10-year cardiovascular risk” in the common carotid artery (CCA) versus carotid bulb using an integrated calculator called “AtheroEdge Composite Risk Score 2.0” (AECRS2.0) and (2) evaluate the performance of AECRS2.0 against “conventional cardiovascular risk calculators.” These objectives are met by measuring (1) image-based phenotypes and AECRS2.0 score computation and (2) performance evaluation of AECRS2.0 against 12 conventional cardiovascular risk calculators. The Asian–Indian cohort (n = 379) with type 2 diabetes mellitus (T2DM), chronic kidney disease (CKD), or hypertension were retrospectively analyzed by acquiring the 1516 carotid ultrasound scans (mean age: 55 ± 10.1 years, 67% males, ∼92% with T2DM, ∼83% with CKD [stage 1-5], and 87.5% with hypertension [stage 1-2]). The carotid bulb showed a higher 10-year cardiovascular risk compared to the CCA by 18% ( P < .0001). Patients with T2DM and/or CKD also followed a similar trend. The carotid bulb demonstrated a superior risk assessment compared to CCA in patients with T2DM and/or CKD by showing: (1) ∼13% better than CCA (0.93 vs 0.82, P = .0001) and (2) ∼29% better compared with 12 types of risk conventional calculators (0.93 vs 0.72, P = .06).
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- 2020
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14. Using clinical prediction models to personalise lifestyle interventions for cardiovascular disease prevention: A systematic literature review
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Patient-specific modeling ,Decision support techniques ,cardiovascular ,PRIMARY-CARE ,10-YEAR RISK ,BLOOD-PRESSURE ,COMMUNICATION ,Cardiovascular diseases/prevention and control ,Models ,GENERAL-PRACTICE ,CORONARY-HEART-DISEASE ,RISK-MANAGEMENT ANCHOR ,TRIAL ,HEALTH ,FOLLOW-UP ,Behavioral medicine - Abstract
This study aimed to systematically review the use of clinical prediction models (CPMs) in personalised lifestyle interventions for the prevention of cardiovascular disease. We searched PubMed and PsycInfo for articles describing relevant studies published up to August 1, 2021. These were supplemented with items retrieved via screening references of citations and cited by references. In total, 32 studies were included. Nineteen different CPMs were used to guide the intervention. Most frequently, a version of the Framingham risk score was used. The CPM was used to inform the intensity of the intervention in five studies (16 %), and the intervention's type in 31 studies (97 %). The CPM was supplemented with relative risk estimates for additional risk factors in three studies (9 %), and relative risk estimates for intervention effects in four (13 %). In addition to the estimated risk, the personalisation was determined using criteria based on univariable risk factors in 18 studies (56 %), a lifestyle score in three (9 %), and a physical examination index in one (3 %). We noted insufficient detail in reporting regarding the CPM's use in 20 studies (63 %). In 15 studies (47 %), the primary outcome was a CPM estimate. A statistically significant effect favouring the intervention to the comparator arm was reported in four out of eight analyses (50 %), and a statistically significant improvement compared to baseline in five out of seven analyses (71 %). Due to the design of the included studies, the effect of the use of CPMs is still unclear. Therefore, we see a need for future research.
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- 2022
15. Using clinical prediction models to personalise lifestyle interventions for cardiovascular disease prevention: A systematic literature review
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Anke Bruninx, Bart Scheenstra, Andre Dekker, Jos Maessen, Arnoud van 't Hof, Bas Kietselaer, and Iñigo Bermejo
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Models, cardiovascular ,Patient-specific modeling ,cardiovascular ,Decision support techniques ,Public Health, Environmental and Occupational Health ,PRIMARY-CARE ,10-YEAR RISK ,Health Informatics ,BLOOD-PRESSURE ,COMMUNICATION ,Review Article ,Cardiovascular diseases/prevention and control ,Models ,GENERAL-PRACTICE ,Medicine ,CORONARY-HEART-DISEASE ,RISK-MANAGEMENT ANCHOR ,TRIAL ,HEALTH ,FOLLOW-UP ,Behavioral medicine - Abstract
Highlights • The use of clinical prediction models (CPMs) to personalise interventions varies. • We reviewed 32 CPM-guided lifestyle interventions to prevent cardiovascular disease. • CPMs were mainly used to determine the intervention’s type, rarely its intensity. • CPMs were supplemented with univariable risk factors, relative risk estimates, etc. • Often reporting lacked detail and designs were unfit to assess the CPM’s impact., This study aimed to systematically review the use of clinical prediction models (CPMs) in personalised lifestyle interventions for the prevention of cardiovascular disease. We searched PubMed and PsycInfo for articles describing relevant studies published up to August 1, 2021. These were supplemented with items retrieved via screening references of citations and cited by references. In total, 32 studies were included. Nineteen different CPMs were used to guide the intervention. Most frequently, a version of the Framingham risk score was used. The CPM was used to inform the intensity of the intervention in five studies (16 %), and the intervention’s type in 31 studies (97 %). The CPM was supplemented with relative risk estimates for additional risk factors in three studies (9 %), and relative risk estimates for intervention effects in four (13 %). In addition to the estimated risk, the personalisation was determined using criteria based on univariable risk factors in 18 studies (56 %), a lifestyle score in three (9 %), and a physical examination index in one (3 %). We noted insufficient detail in reporting regarding the CPM’s use in 20 studies (63 %). In 15 studies (47 %), the primary outcome was a CPM estimate. A statistically significant effect favouring the intervention to the comparator arm was reported in four out of eight analyses (50 %), and a statistically significant improvement compared to baseline in five out of seven analyses (71 %). Due to the design of the included studies, the effect of the use of CPMs is still unclear. Therefore, we see a need for future research.
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- 2022
16. Correction
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Vo Tam, Anselme Derese, Stefan Heytens, Dirk Devroey, Ho Anh Hien, Nguyen Minh Tam, Huynh Van Minh, Nguyen Phuong Hoa, Medicine and Pharmacy academic/administration, Family Medicine and Chronic Care, and Commodore-Mensah, Yvonne
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Male ,Physiology ,Cross-sectional study ,10-YEAR RISK ,Blood Pressure ,Cardiovascular Medicine ,030204 cardiovascular system & hematology ,Vascular Medicine ,Infographics ,DISEASE ,Geographical Locations ,Medical Conditions ,Endocrinology ,0302 clinical medicine ,Prevalence ,Medicine and Health Sciences ,WHO/ISH ,Medicine ,030212 general & internal medicine ,POPULATION ,Data Management ,education.field_of_study ,Multidisciplinary ,medicine.diagnostic_test ,General Medicine ,Middle Aged ,Cardiovascular disease ,40-69 years ,Charts ,Physiological Parameters ,Vietnam ,Cardiovascular Diseases ,Hypertension ,Female ,General Agricultural and Biological Sciences ,Risk assessment ,Research Article ,Adult ,Computer and Information Sciences ,Asia ,Endocrine Disorders ,Science ,Population ,Cardiology ,Genetics and Molecular Biology ,World Health Organization ,Risk Assessment ,03 medical and health sciences ,Predictive Value of Tests ,Diabetes mellitus ,Environmental health ,Diabetes Mellitus ,Humans ,Blood test ,Obesity ,Mortality ,education ,Aged ,business.industry ,MORTALITY ,Data Visualization ,Body Weight ,Public Health, Environmental and Occupational Health ,Correction ,Biology and Life Sciences ,Blood Pressure Determination ,ADULTS ,Cardiovascular Disease Risk ,Anthropometry ,medicine.disease ,PREVENTION ,Cross-Sectional Studies ,Blood pressure ,Heart Disease Risk Factors ,Metabolic Disorders ,General Biochemistry ,People and Places ,Morbidity ,Prediction ,business - Abstract
Introduction Cardiovascular disease (CVD) being the leading cause of the morbidity and mortality in Vietnam, the objective of this study was to estimate the total 10-year CVD risk among adults aged 40–69 years by utilizing World Health Organization/International Society of Hypertension (WHO/ISH) risk prediction charts in Central Vietnam. Materials and methods In this cross-sectional study, multi-staged sampling was used to select 938 participants from a general population aged from 40 to 69. The CVD risk factors were then collected throughout the interviews with a standardized questionnaire, anthropometric measurements and a blood test. The cardiovascular risk was calculated using the WHO/ISH risk prediction charts. Results According to the WHO/ISH charts, the proportion of moderate risk (10–20%) and high risk (>20%) among the surveyed participants were equal (5.1%). When “blood pressure of more than 160/100 mmHg” was applied, the proportion of moderate risk reduced to 2.3% while the high risk increased markedly to 12.8%. Those proportions were higher in men than in women (at 18.3% and 8.5% respectively, p-value Conclusions There was a high burden of CVD risk in Central Vietnam as assessed with the WHO/ISH risk prediction charts, especially in men and among the ethnic minorities. The use of WHO/ISH charts provided a feasible and affordable screening tool in estimating the cardiovascular risk in primary care settings.
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- 2021
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17. Triglyceride-glucose index and estimated 10-year risk of a first hard cardiovascular event.
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Qu H, Long LZ, Chen L, Wu HT, Fu CG, and Zhang SS
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Background: Whether Triglyceride-glucose (TyG) index is associated with 10-year risk of a first hard atherosclerotic cardiovascular disease (ASCVD) event in the United States remains unclear., Methods: In this cross-sectional study, the participants, ranged from 40 to 79 years old, were from the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018. TyG index was the independent variable and 10-year risk of a first hard ASCVD was the dependent variable. The other variables, such as age, gender, race, body mass index (BMI), hypertension treatment states, smoking states and low-density lipoprotein cholesterol (LDL-C) et al. were considered as the potential confounding factors. Multivariate linear regression models and smooth curve fittings were used to evaluate the association between TyG index and 10-year risk of a first hard ASCVD event., Results: A total of 2,142 participants were included in the analysis. The results showed that TyG index was associated with an increased 10-year risk of a first hard ASCVD event [β = 2.208, 95% (1.716, 2.700), P < 0.00001]. The association had statistical significance in both men [β = 3.862 95% CI (3.274, 4.450), P < 0.00001] and women [β = 1.067, 95% CI (0.286, 1.849), P = 0.00756)] according to subgroup analysis. Smooth curve fittings revealed that TyG index was linearly associated with 10-year risk of ASCVD in both male and female., Conclusion: Triglyceride-glucose index was associated with an increased 10-year risk of a first hard ASCVD event in the United States, suggesting it is necessary to monitor and control an appropriate range of TyG index., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Qu, Long, Chen, Wu, Fu and Zhang.)
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- 2023
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18. Predicted 10-year risk of cardiovascular disease among Canadian adults using modified Framingham Risk Score in association with dietary intake.
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Setayeshgar, Solmaz, Whiting, Susan J., Pahwa, Punam, and Vatanparast, Hassanali
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BREAKFASTS , *CARDIOVASCULAR diseases risk factors , *CONFIDENCE intervals , *DIET , *FRUIT , *INGESTION , *OBESITY , *RISK assessment , *VEGETABLES , *LOGISTIC regression analysis , *EDUCATIONAL attainment , *CROSS-sectional method , *DATA analysis software , *DESCRIPTIVE statistics , *ODDS ratio - Abstract
Initial risk assessment to estimate 10-year risk of cardiovascular disease (CVD) is completed by Framingham Risk Score (FRS). In 2012 2 modifications were added to FRS by the Canadian Cardiovascular Society: FRS is doubled in subjects aged 30-59 years who have CVD present in a first-degree relative before 55 years of age for men and 65 years of age for women; and cardiovascular age is calculated for each individual. Our aim was to implement these modifications and evaluate differences compared with traditional FRS. Further, we evaluated the association between dietary intake and 10-year risk. The Canadian Health Measures Survey data cycle 1 was used among participants aged 30-74 years ( n = 2730). Descriptive and logistic regression analyses were conducted using STATA SE 11. Using modified FRS for predicting 10-year risk of CVD significantly increased the estimated risk compared with the traditional approach, 8.66% ± 0.35% versus 6.06% ± 0.18%, respectively. Greater impact was observed with the 'cardiovascular age' modification in men versus women. The distribution of Canadians in low- (<10%) and high-risk (≥20%) categories of CVD show a significant difference between modified and traditional FRS: 67.4% versus 79.6% (low risk) and 13.7% versus 4.5% (high risk), respectively. The odds of having risk ≥10% was significantly greater in low-educated, abdominally obese individuals or those with lower consumption of breakfast cereal and fruit and vegetable and greater potato and potato products consumption. In conclusion, the traditional FRS method significantly underestimates CVD risk in Canadians; thus, applying modified FRS is beneficial for screening. Additionally, fibre consumption from fruit and vegetable or breakfast cereals might be beneficial in reducing CVD risks. [ABSTRACT FROM AUTHOR]
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- 2015
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19. The feasibility and outcome of a community-based primary prevention program for cardiovascular disease in the 21st century
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Susanna Kuneinen, Mikael Ekblad, Johan G. Eriksson, Päivi Korhonen, Hannu Kautiainen, Clinicum, Research Programs Unit, Johan Eriksson / Principal Investigator, Department of General Practice and Primary Health Care, University of Helsinki, and Helsinki University Hospital Area
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medicine.medical_specialty ,Heart disease ,Population ,primary prevention ,10-YEAR RISK ,Disease ,HEART-DISEASE ,Outcome (game theory) ,Asymptomatic ,03 medical and health sciences ,0302 clinical medicine ,Risk Factors ,Primary prevention ,SCORE ,medicine ,Humans ,030212 general & internal medicine ,Risk factor ,Intensive care medicine ,education ,Life Style ,POPULATION ,Aged ,Community based ,general practice ,education.field_of_study ,business.industry ,030503 health policy & services ,screening ,MORTALITY ,Public Health, Environmental and Occupational Health ,Original Articles ,Middle Aged ,medicine.disease ,Cardiovascular disease ,Cardiovascular Diseases ,3121 General medicine, internal medicine and other clinical medicine ,Feasibility Studies ,Public aspects of medicine ,RA1-1270 ,medicine.symptom ,0305 other medical science ,business ,Research Article - Abstract
Objective There is no evidence that systematic screening and risk factor modification in an unselected, asymptomatic population will reduce cardiovascular disease (CVD) mortality. This study aimed to evaluate the effectiveness of a primary care CVD prevention program on mortality during a 13-year follow-up. Design A risk factor survey was sent, followed by a nurse-led lifestyle counselling to respondents with at least one CVD risk factor, and a general practitioner’s (GP) appointment for high-risk persons. Screening and interventions were performed during 2005–2006. Setting A public health care centre in the town of Harjavalta, Finland. Subjects All home-dwelling 45–70-year old inhabitants without manifested CVD or diabetes. Main outcome measures All-cause and CVD mortality. Results Altogether 74% (2121/2856) inhabitants responded to the invitation. The intervention was received by 1465 individuals (52% of the invited population): 398 risk persons had an appointment with a nurse, followed by an appointment with a GP for 1067 high-risk persons. During the follow-up, 370 persons died. Mortality among the non-respondents was twofold compared to the participants’. In subjects who received the intervention, the age- and gender-adjusted hazard ratio for all-cause mortality was 0.44 (95% CI: 0.36 to 0.54) compared to the subjects who did not receive the intervention. Conclusions Reducing mortality is possible in a primary care setting by raising health awareness in the community with screening, by targeted lifestyle counselling and evidence-based preventive medication for persons at high risk for CVD. Subjects not willing to participate in health surveys have the worst prognosis.Key PointsPreviously, there is no evidence that systematic screening and risk factor modification in an unselected, asymptomatic population will reduce cardiovascular disease (CVD) mortality.With a stepwise screening program it is possible to scale the magnitude of CVD prevention in the community.Reducing mortality in a community is possible by screening, targeted lifestyle counselling, and by evidence-based preventive medication for high-risk persons.Subjects not willing to participate in health surveys have the worst prognosis.
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- 2021
20. Cardiovascular/stroke risk predictive calculators: a comparison between statistical and machine learning models
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Luca Saba, Athanasios Protogerou, Gyan Pareek, Deep Gupta, John R. Laird, Martin Miner, Jasjit S. Suri, Ankush D Jamthikar, Klaudija Višković, George D. Kitas, Aditya Sharma, Narendra N. Khanna, Vijay Viswanathan, Andrew Nicolaides, Tadashi Araki, Sophie Mavrogeni, and Petros P. Sfikakis
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020205 medical informatics ,business.industry ,Mean age ,02 engineering and technology ,030204 cardiovascular system & hematology ,Machine learning ,computer.software_genre ,medicine.disease ,Stroke risk ,03 medical and health sciences ,0302 clinical medicine ,Cardiovascular Stroke ,Risk stratification ,0202 electrical engineering, electronic engineering, information engineering ,Medicine ,Original Article on Advanced Imaging in The Diagnosis of Cardiovascular Diseases ,Artificial intelligence ,Atherosclerosis ,cardiovascular disease (CVD) ,stroke ,10-year risk ,statistical risk calculator ,integrated models ,machine learning-based calculator ,Cardiology and Cardiovascular Medicine ,business ,computer ,Stroke - Abstract
BACKGROUND: Statistically derived cardiovascular risk calculators (CVRC) that use conventional risk factors, generally underestimate or overestimate the risk of cardiovascular disease (CVD) or stroke events primarily due to lack of integration of plaque burden. This study investigates the role of machine learning (ML)-based CVD/stroke risk calculators (CVRC(ML)) and compares against statistically derived CVRC (CVRC(Stat)) based on (I) conventional factors or (II) combined conventional with plaque burden (integrated factors). METHODS: The proposed study is divided into 3 parts: (I) statistical calculator: initially, the 10-year CVD/stroke risk was computed using 13 types of CVRC(Stat) (without and with plaque burden) and binary risk stratification of the patients was performed using the predefined thresholds and risk classes; (II) ML calculator: using the same risk factors (without and with plaque burden), as adopted in 13 different CVRC(Stat), the patients were again risk-stratified using CVRC(ML) based on support vector machine (SVM) and finally; (III) both types of calculators were evaluated using AUC based on ROC analysis, which was computed using combination of predicted class and endpoint equivalent to CVD/stroke events. RESULTS: An Institutional Review Board approved 202 patients (156 males and 46 females) of Japanese ethnicity were recruited for this study with a mean age of 69±11 years. The AUC for 13 different types of CVRC(Stat) calculators were: AECRS2.0 (AUC 0.83, P
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- 2020
21. Artificial intelligence framework for predictive cardiovascular and stroke risk assessment models: A narrative review of integrated approaches using carotid ultrasound
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Jasjit S. Suri, Vijay Viswanathan, Amer M. Johri, Aditya Sharma, Gyan Pareek, Deep Gupta, Naveed Sattar, Athanasios Protogerou, John R. Laird, Sophie Mavrogeni, Petros P. Sfikakis, Narendra N. Khanna, Ankush D Jamthikar, Raghu Kolluri, Klaudija Višković, Andrew Nicolaides, Luca Saba, George D. Kitas, and Martin Miner
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0301 basic medicine ,Carotid ultrasound ,Cvd risk ,Baseline risk ,Health Informatics ,Disease ,Risk Assessment ,Stroke risk ,03 medical and health sciences ,0302 clinical medicine ,Artificial Intelligence ,Risk Factors ,Humans ,Medicine ,cardiovascular diseases ,Modalities ,business.industry ,10-Year risk ,Artificial intelligence-based risk assessment ,Atherosclerosis ,Cardiovascular disease ,Integrated models ,Statistical risk calculator ,Stroke ,Plaque, Atherosclerotic ,Computer Science Applications ,Carotid Arteries ,030104 developmental biology ,Cardiovascular Diseases ,Narrative review ,Artificial intelligence ,business ,Healthcare providers ,030217 neurology & neurosurgery - Abstract
Recent findings Cardiovascular disease (CVD) is the leading cause of mortality and poses challenges for healthcare providers globally. Risk-based approaches for the management of CVD are becoming popular for recommending treatment plans for asymptomatic individuals. Several conventional predictive CVD risk models based do not provide an accurate CVD risk assessment for patients with different baseline risk profiles. Artificial intelligence (AI) algorithms have changed the landscape of CVD risk assessment and demonstrated a better performance when compared against conventional models, mainly due to its ability to handle the input nonlinear variations. Further, it has the flexibility to add risk factors derived from medical imaging modalities that image the morphology of the plaque. The integration of noninvasive carotid ultrasound image-based phenotypes with conventional risk factors in the AI framework has further provided stronger power for CVD risk prediction, so-called “integrated predictive CVD risk models.” Purpose of the review: The objective of this review is (i) to understand several aspects in the development of predictive CVD risk models, (ii) to explore current conventional predictive risk models and their successes and challenges, and (iii) to refine the search for predictive CVD risk models using noninvasive carotid ultrasound as an exemplar in the artificial intelligence-based framework. Conclusion Conventional predictive CVD risk models are suboptimal and could be improved. This review examines the potential to include more noninvasive image-based phenotypes in the CVD risk assessment using powerful AI-based strategies.
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- 2020
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22. Distribution of 10-year risk for coronary heart disease and eligibility for therapeutic approaches among Tehranian adults.
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Barzin, M., Mirmiran, P., Afghan, M., and Azizi, F.
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CORONARY disease , *HEART disease risk factors , *LIPIDS , *BIOMOLECULES , *GLUCOSE - Abstract
Objectives: To establish the distribution of 10-year risk for coronary heart disease (CHD) and eligibility for therapeutic approaches among Tehranian adults within the framework of the Tehran Lipid and Glucose Study (TLGS). Study design: Cross-sectional study conducted on data from Phase III of the TLGS (12,521 people aged ≥3 years). Methods: The modified Framingham algorithm adopted by the National Cholesterol Education Program Adult Treatment Panel III was used to estimate participants' 10-year risk of developing CHD; only participants aged 20-79 years were included. Following the exclusion of subjects without full relevant data, 9483 participants (42.6% men) were enrolled in the final analysis. The distributions of the population needing therapeutic lifestyle changes (TLCs) and additional drug therapy were calculated. Results: Overall, the mean (standard deviation) age was 43.7 (15.4) years; 44.6 (15.9) for men and 43.0 (14.9) for women. Ten-year risk for CHD of <10%, 10-20% and >20% was observed in 86.0%, 12.0% and 2.0% of participants with at least two risk factors and without CHD or a CHD risk equivalent, respectively. For subjects with less than two risk factors and without CHD or a CHD risk equivalent, these values were 14.0%, 8.3% and 14.7%, respectively; 63.1% of subjects had less than two risk factors. The need for TLCs and additional drug therapy was observed in 12% and 12.5% of subjects, respectively. Conclusions: Regarding the estimated 10-year risk for CHD, about one-quarter of Tehranian adults are eligible for therapeutic approaches. [ABSTRACT FROM AUTHOR]
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- 2011
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23. The gender- and age-specific 10-year and lifetime absolute fracture risk in Tromsø, Norway.
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Ahmed, Luai, Schirmer, Henrik, Bjørnerem, Åshild, Emaus, Nina, Jørgensen, Lone, Størmer, Jan, and Joakimsen, Ragnar
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BONE fractures ,OSTEOPOROSIS ,DISEASE risk factors ,SHOULDER dislocations ,FOREARM injuries - Abstract
Aim of this study is to estimate the gender- and age-specific 10-year and lifetime absolute risks of non-vertebral and osteoporotic (included hip, distal forearm and proximal humerus) fractures in a large cohort of men and women. This is a population-based 10 years follow-up study of 26,891 subjects aged 25 years and older in Tromsø, Norway. All non-vertebral fractures were registered from 1995 throughout 2004 by computerized search in radiographic archives. Absolute risks were estimated by life-table method taking into account the competing risk of death. The absolute fracture risk at each year of age was estimated for the next 10 years (10-year risk) or up to the age of 90 years (lifetime risk). The estimated 10-year absolute risk of all non-vertebral fracture was higher in men than women before but not after the age of 45 years. The 10-year absolute risk for non-vertebral and osteoporotic fractures was over 10%, respectively, in men over 65 and 70 years and in women over 45 and 50 years of age. The 10-year absolute risks of hip fractures at the age of 65 and 80 years were 4.2 and 18.6% in men, and 9.0 and 24.0% in women, respectively. The risk estimates for distal forearm and proximal humerus fractures were under 5% in men and 13% in women. The estimated lifetime risks for all fracture locations were higher in women than men at all ages. At the age of 50 years, the risks were 38.1 and 24.8% in men and 67.4 and 55.0% in women for all non-vertebral and osteoporotic fractures, respectively. The estimated gender- and age-specific 10-year and lifetime absolute fracture risk were higher in Tromsø than in other populations. The high lifetime fracture risk reflects the increased burden of fractures in this cohort. [ABSTRACT FROM AUTHOR]
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- 2009
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24. A low-cost machine learning-based cardiovascular/stroke risk assessment system: integration of conventional factors with image phenotypes
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Petros P. Sfikakis, Jasjit S. Suri, Andrew Nicolaides, Vijay Viswanathan, Tadashi Araki, Monika Turk, Athanasios Protogerou, Martin Miner, Ankush D Jamthikar, Narendra N. Khanna, Luca Saba, John R. Laird, Sophie Mavrogeni, George D. Kitas, Harman S. Suri, Ajay Gupta, Klaudija Višković, Deepak L. Bhatt, Gyan Pareek, and Deep Gupta
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Atherosclerosis ,conventional risk factors (CRF) ,carotid ultrasound (CUS) ,carotid intima-media thickness (cIMT) ,carotid stenosis ,cardiovascular disease (CVD) ,stroke ,10-year risk ,machine learning (ML) ,business.industry ,Carotid arteries ,030204 cardiovascular system & hematology ,Machine learning ,computer.software_genre ,Random forest ,03 medical and health sciences ,0302 clinical medicine ,Principal component analysis ,Cardiovascular Stroke ,Medicine ,System integration ,Original Article ,Artificial intelligence ,Cardiology and Cardiovascular Medicine ,business ,Risk assessment ,Feature set ,computer ,Classifier (UML) ,030217 neurology & neurosurgery - Abstract
ackground: Most cardiovascular (CV)/stroke risk calculators using the integration of carotid ultrasound image-based phenotypes (CUSIP) with conventional risk factors (CRF) have shown improved risk stratification compared with either method. However such approaches have not yet leveraged the potential of machine learning (ML). Most intelligent ML strategies use follow-ups for the endpoints but are costly and time-intensive. We introduce an integrated ML system using stenosis as an endpoint for training and determine whether such a system can lead to superior performance compared with the conventional ML system. Methods: The ML-based algorithm consists of an offline and online system. The offline system extracts 47 features which comprised of 13 CRF and 34 CUSIP. Principal component analysis (PCA) was used to select the most significant features. These offline features were then trained using the event-equivalent gold standard (consisting of percentage stenosis) using a random forest (RF) classifier framework to generate training coefficients. The online system then transforms the PCA-based test features using offline trained coefficients to predict the risk labels on test subjects. The above ML system determines the area under the curve (AUC) using a 10-fold cross- validation paradigm. The above system so-called “AtheroRisk-Integrated” was compared against “AtheroRisk-Conventional”, where only 13 CRF were considered in a feature set. Results: Left and right common carotid arteries of 202 Japanese patients (Toho University, Japan) were retrospectively examined to obtain 395 ultrasound scans. AtheroRisk-Integrated system [AUC =0.80, P
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- 2019
25. World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions
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Angelantonio, E. di, Kaptoge, S., Pennells, L., Bacquer, D. de, Cooney, M.T., Kavousi, M., Stevens, G., Riley, L., Savin, S., Altay, S., Amouyel, P., Assmann, G., Bell, S., Ben-Shlomo, Y., Berkman, L., Beulens, J.W., Bjorkelund, C., Blaha, M.J., Blazer, D.G., Bolton, T., Bonita, R., Brenner, B.H., Brunner, E.J., Casiglia, E., Chamnan, P., Choi, Y.H., Chowdhury, R., Coady, S., Crespo, C.J., Cushman, M., Dagenais, G.R., D'Agostino, R.B., Daimon, M., Davidson, K.W., Engstrom, G., Fang, X.H., Ford, I., Gallacher, J., Gansevoort, R.T., Gaziano, T.A., Giampaoli, S., Grandits, G., Grimsgaard, S., Grobbee, D.E., Gudnason, V., Guo, Q., Humphries, S., Iso, H., Jukema, J.W., Kauhanen, J., Kengne, A.P., Khalili, D., Khan, T., Knuiman, M., Koenig, W., Kromhout, D., Krumholz, H.M., Lam, T.H., Laughlin, G., Ibanez, A.M., Moons, K.G.M., Nietert, P.J., Ninomiya, T., Nordestgaard, B.G., O'Donnell, C., Palmieri, L., Patel, A., Perel, P., Price, J.F., Costa, R.B.D.E., Ridker, P.M., Rodriguez, B., Rosengren, A., Roussel, R., Sakurai, M., Salomaa, V., Sato, S., Schottker, B., Shara, N., Shaw, J.E., Shin, H.C., Simons, L.A., Sofianopoulou, E., Sundstrom, J., Tolonen, H., Ueshima, H., Volzke, H., Wallace, R.B., Wareham, N.J., Willeit, P., Wood, D., Wood, A., Zhao, D., Onuma, O., Woodward, M., Danaei, G., Roth, G., Mendis, S., Graham, I., Varghese, C., Ezzati, M., Jackson, R., Danesh, J., Nambi, V., Matsushita, K., Couper, D., Diabetes, A., Zimmet, P.Z., Barr, E.L.M., Atkins, R., Whincup, P.H., Study, B., Kiechl, S., Willeit, J., Rungger, G., Sofat, R., Dale, C., Casas, J.P., Tikhonoff, V., Hunt, K.J., Sutherland, S.E., Psaty, B.M., Tracy, R., Frikke-Schmidt, R., Jensen, G.B., Schnohr, P., Donfrancesco, C., Vanuzzo, D., Panico, S., Balkau, B., Bonnet, F., Fumeron, F., Simons, J., McLachlan, S., Guralnik, J., Khaw, K.T., Brenner, H., Zhang, Y., Holleczek, B., Cohort, F., Vartiainen, E., Jousilahti, P., Harald, K., Massaro, J.J., Pencina, M., Ramachandran, V., Susa, S., Oizumi, T., Kayama, T., Wilhelmsen, L., Lissner, L., Hange, D., Mehlig, K., Hata, J., Yoshida, D., Hirakawa, Y., Rutters, F., Elders, P.J.M., Kyowa, I., Kiyama, M., Yamagishi, K., Tuomainen, T.P., Virtanen, J., Salonen, J.T., Meade, T.W., Nilsson, P.M., Melander, O., Boer, I.H. de, DeFilippis, A.P., Kuller, L.H., Juan, S.I., Gillum, R.F., Kirkland, S., Shimbo, D., Schwartz, J.E., Imano, H., Harst, P. van der, Hillige, J.L., Bakker, S.J., Dallongeville, J., Ferrieres, J., Moitry, M., Stott, D.J., Despres, J.P., Laughlin, G.A., Daniels, L.B., McEvoy, L.K., Aspelund, T., Thorsson, B., Gudmundsson, E.F., Aribas, E., Rueda-Ochoa, O.L., Ikram, M.K., Heshmatollah, A., Ikram, M.A., Dorr, M., Nauck, M., Howard, B., Can, G., Ishizaki, M., Wilsgaard, T., Mathiesen, E., Giedraitis, V., Ingelsson, M., Cook, N., Buring, J., Schouw, Y.T. van der, Claessen, H., Rothenbacher, D., Arndt, V., Study, W.I., Shipley, M., Packard, C., Robertson, M., Young, R., Feskens, E., Geleijnse, J.M., Fang, X., Gu, D.F., Huxley, R., Imai, Y., Kim, H.C., Pan, W.H., Rodgers, A., Suh, I., Town, A., Okayama, A., Maegawa, H., Nakamura, M., Aoki, N., Wu, Z.S., Yao, C.H., Luszcz, M., Tang, Z., Liu, L.S., Xie, J.X., Norton, R., Ameratunga, S., MacMahon, S., Whitlock, G., Knuiman, M.W., Christensen, H., Wu, X.G., Zhou, J., Yu, X.H., Tamakoshi, W.A., Wu, Z.L., Chen, L.Q., Shan, G.L., Sritara, P., Duan, X.F., Li, Y.H., Jiang, C.Q., Woo, J., Ho, S.C., Hong, Z., Huang, M.S., Zhou, B., Fuh, J.L., Kita, Y., Choudhury, S.R., Jee, S.H., Kim, Woodward, M, Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Epidemiology, Epidemiology and Data Science, ACS - Diabetes & metabolism, ACS - Heart failure & arrhythmias, and APH - Health Behaviors & Chronic Diseases
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Male ,10-YEAR RISK ,BLOOD-PRESSURE ,0302 clinical medicine ,Risk Factors ,Medicine and Health Sciences ,Medicine ,Uganda ,Cardiac and Cardiovascular Systems ,Prospective Studies ,030212 general & internal medicine ,Aged, 80 and over ,Medicine(all) ,Kardiologi ,lcsh:Public aspects of medicine ,PRIMARY-CARE ,Public Health, Global Health, Social Medicine and Epidemiology ,General Medicine ,Middle Aged ,3. Good health ,Pooled analysis ,Cardiovascular Diseases ,Egypt ,Female ,Adult ,PROSPECTIVE COHORTS ,030231 tropical medicine ,195 COUNTRIES ,Primary care ,World Health Organization ,Risk Assessment ,Article ,World health ,POOLED ANALYSIS ,03 medical and health sciences ,SDG 3 - Good Health and Well-being ,Primary prevention ,Environmental health ,SYSTEMATIC ANALYSIS ,Humans ,Aged ,CHINESE POPULATION ,Chinese population ,business.industry ,Individual participant data ,lcsh:RA1-1270 ,R1 ,Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi ,Disease risk ,business ,INDIVIDUAL PARTICIPANT DATA ,PRIMARY PREVENTION - Abstract
Background: To help adapt cardiovascular disease risk prediction approaches to low-income and middle-income countries, WHO has convened an effort to develop, evaluate, and illustrate revised risk models. Here, we report the derivation, validation, and illustration of the revised WHO cardiovascular disease risk prediction charts that have been adapted to the circumstances of 21 global regions. Methods: In this model revision initiative, we derived 10-year risk prediction models for fatal and non-fatal cardiovascular disease (ie, myocardial infarction and stroke) using individual participant data from the Emerging Risk Factors Collaboration. Models included information on age, smoking status, systolic blood pressure, history of diabetes, and total cholesterol. For derivation, we included participants aged 40–80 years without a known baseline history of cardiovascular disease, who were followed up until the first myocardial infarction, fatal coronary heart disease, or stroke event. We recalibrated models using age-specific and sex-specific incidences and risk factor values available from 21 global regions. For external validation, we analysed individual participant data from studies distinct from those used in model derivation. We illustrated models by analysing data on a further 123 743 individuals from surveys in 79 countries collected with the WHO STEPwise Approach to Surveillance. Findings: Our risk model derivation involved 376 177 individuals from 85 cohorts, and 19 333 incident cardiovascular events recorded during 10 years of follow-up. The derived risk prediction models discriminated well in external validation cohorts (19 cohorts, 1 096 061 individuals, 25 950 cardiovascular disease events), with Harrell's C indices ranging from 0·685 (95% CI 0·629–0·741) to 0·833 (0·783–0·882). For a given risk factor profile, we found substantial variation across global regions in the estimated 10-year predicted risk. For example, estimated cardiovascular disease risk for a 60-year-old male smoker without diabetes and with systolic blood pressure of 140 mm Hg and total cholesterol of 5 mmol/L ranged from 11% in Andean Latin America to 30% in central Asia. When applied to data from 79 countries (mostly low-income and middle-income countries), the proportion of individuals aged 40–64 years estimated to be at greater than 20% risk ranged from less than 1% in Uganda to more than 16% in Egypt. Interpretation: We have derived, calibrated, and validated new WHO risk prediction models to estimate cardiovascular disease risk in 21 Global Burden of Disease regions. The widespread use of these models could enhance the accuracy, practicability, and sustainability of efforts to reduce the burden of cardiovascular disease worldwide. Funding: World Health Organization, British Heart Foundation (BHF), BHF Cambridge Centre for Research Excellence, UK Medical Research Council, and National Institute for Health Research. The WHO CVD Risk Chart Working Group, for complete list of authors see http://dx.doi.org/10.1016/S2214-109X(19)30318-3
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- 2019
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26. Application of non-HDL cholesterol for population-based cardiovascular risk stratification: results from the Multinational Cardiovascular Risk Consortium
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Philipp S. Wild, Francesco Gianfagna, Christoph Waldeyer, Maryam Kavousi, Mark Woodward, Ulf Risérus, Susana Sans, Barbara Thorand, Martin Ingelsson, Ramachandran S. Vasan, Christa Meisinger, Yuriy P. Nikitin, Börge Schmidt, Olle Melander, Wojciech Drygas, Stefan Blankenberg, Frank Kee, Demosthenes B. Panagiotakos, Kari Kuulasmaa, Torben Jørgensen, Wolfgang Koenig, Ben Schöttker, Jean Ferrières, Annette J. Dobson, Fabian J. Brunner, Veikko Salomaa, David M. Leistner, Pekka Jousilahti, Marie Moitry, Jonathan E. Shaw, Philippe Amouyel, Karl-Heinz Jöckel, Jens Klotsche, Andres Metspalu, Giovanni Veronesi, Mats Eliasson, Graham G. Giles, Allan Linneberg, Christos Pitsavos, Guido Grassi, Ellisiv B. Mathiesen, Hermann Brenner, Stephan J. L. Bakker, Tom Wilsgaard, Magnus Nakrem Lyngbakken, Peter H. Whincup, T. Jaaskelainen, Kristian Hveem, Marcus Dörr, Steven Shea, Robin P. F. Dullaart, Teemu J. Niiranen, Nataliya Makarova, Stefan Söderberg, Satu Männistö, Abdonas Tamosiunas, Licia Iacoviello, Jean Dallongeville, Karl J. Lackner, Maris Alver, Tanja Zeller, Raphael Twerenbold, Dianna J. Magliano, S. Goya Wannamethee, Matthias Nauck, Ulf Landmesser, Allison M. Hodge, Francisco Ojeda, Paolo Brambilla, Thiess Lorenz, Sofia Malyutina, Chiara Donfrancesco, Jukka Kontto, Henry Völzke, Martin Bobak, Annette Peters, Gunnar Engström, James A. de Lemos, Hugh Tunstall-Pedoe, Stefano Signorini, Simona Giampaoli, Simona Costanzo, Andrzej Pajak, Leon A. Simons, M. Kamran Ikram, Emelia J. Benjamin, Torbjørn Omland, Lifestyle Medicine (LM), Groningen Institute for Organ Transplantation (GIOT), Groningen Kidney Center (GKC), Brunner, F, Waldeyer, C, Ojeda, F, Salomaa, V, Kee, F, Sans, S, Thorand, B, Giampaoli, S, Brambilla, P, Tunstall-Pedoe, H, Moitry, M, Iacoviello, L, Veronesi, G, Grassi, G, Mathiesen, E, Söderberg, S, Linneberg, A, Brenner, H, Amouyel, P, Ferrières, J, Tamosiunas, A, Nikitin, Y, Drygas, W, Melander, O, Jöckel, K, Leistner, D, Shaw, J, Panagiotakos, D, Simons, L, Kavousi, M, Vasan, R, Dullaart, R, Wannamethee, S, Risérus, U, Shea, S, de Lemos, J, Omland, T, Kuulasmaa, K, Landmesser, U, Blankenberg, S, Zeller, T, Kontto, J, Männistö, S, Metspalu, A, Lackner, K, Wild, P, Peters, A, Meisinger, C, Donfrancesco, C, Signorini, S, Alver, M, Woodward, M, Gianfagna, F, Costanzo, S, Wilsgaard, T, Eliasson, M, Jørgensen, T, Völzke, H, Dörr, M, Nauck, M, Schöttker, B, Lorenz, T, Makarova, N, Twerenbold, R, Dallongeville, J, Dobson, A, Malyutina, S, Pajak, A, Engström, G, Bobak, M, Schmidt, B, Jääskeläinen, T, Niiranen, T, Jousilahti, P, Giles, G, Hodge, A, Klotsche, J, Magliano, D, Lyngbakken, M, Hveem, K, Pitsavos, C, Benjamin, E, Bakker, S, Whincup, P, Ikram, M, Ingelsson, M, Koenig, W, and Epidemiology
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Male ,PREDICTION ,Medizin ,Blood lipids ,10-YEAR RISK ,Disease ,Familial hypercholesterolemia ,030204 cardiovascular system & hematology ,chemistry.chemical_compound ,0302 clinical medicine ,Risk Factors ,Medicine ,PARTICIPANTS ,Cardiac and Cardiovascular Systems ,030212 general & internal medicine ,FAMILIAL HYPERCHOLESTEROLEMIA ,Medicine(all) ,GENERAL-POPULATION ,Kardiologi ,Incidence (epidemiology) ,General Medicine ,ASSOCIATION ,Middle Aged ,3. Good health ,Europe ,Cholesterol ,DENSITY-LIPOPROTEIN CHOLESTEROL ,Cardiovascular Diseases ,Cohort ,Endokrinologi och diabetes ,Female ,lipids (amino acids, peptides, and proteins) ,Risk assessment ,Adult ,medicine.medical_specialty ,APOLIPOPROTEIN-B ,Endocrinology and Diabetes ,Risk Assessment ,03 medical and health sciences ,SDG 3 - Good Health and Well-being ,Internal medicine ,Humans ,VDP::Medisinske Fag: 700 ,CORONARY-HEART-DISEASE ,ddc:610 ,Aged ,business.industry ,Australia ,Cholesterol, LDL ,Guideline ,medicine.disease ,United States ,VDP::Medical disciplines: 700 ,chemistry ,business ,TASK-FORCE - Abstract
Background: The relevance of blood lipid concentrations to long-term incidence of cardiovascular disease and the relevance of lipid-lowering therapy for cardiovascular disease outcomes is unclear. We investigated the cardiovascular disease risk associated with the full spectrum of bloodstream non-HDL cholesterol concentrations. We also created an easy-to-use tool to estimate the long-term probabilities for a cardiovascular disease event associated with non-HDL cholesterol and modelled its risk reduction by lipid-lowering treatment. Methods: In this risk-evaluation and risk-modelling study, we used Multinational Cardiovascular Risk Consortium data from 19 countries across Europe, Australia, and North America. Individuals without prevalent cardiovascular disease at baseline and with robust available data on cardiovascular disease outcomes were included. The primary composite endpoint of atherosclerotic cardiovascular disease was defined as the occurrence of the coronary heart disease event or ischaemic stroke. Sex-specific multivariable analyses were computed using non-HDL cholesterol categories according to the European guideline thresholds, adjusted for age, sex, cohort, and classical modifiable cardiovascular risk factors. In a derivation and validation design, we created a tool to estimate the probabilities of a cardiovascular disease event by the age of 75 years, dependent on age, sex, and risk factors, and the associated modelled risk reduction, assuming a 50% reduction of non-HDL cholesterol. Findings: Of the 524 444 individuals in the 44 cohorts in the Consortium database, we identified 398 846 individuals belonging to 38 cohorts (184 055 [48·7%] women; median age 51·0 years [IQR 40·7–59·7]). 199 415 individuals were included in the derivation cohort (91 786 [48·4%] women) and 199 431 (92 269 [49·1%] women) in the validation cohort. During a maximum follow-up of 43·6 years (median 13·5 years, IQR 7·0–20·1), 54 542 cardiovascular endpoints occurred. Incidence curve analyses showed progressively higher 30-year cardiovascular disease event-rates for increasing non-HDL cholesterol categories (from 7·7% for non-HDL cholesterol
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- 2019
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27. The Association Between Remnant Cholesterol and the Estimated 10-Year Risk of a First Hard Cardiovascular Event.
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Yang Z, Yang K, Shi J, Yang Q, Zhang Y, Gao J, Shi D, and Qu H
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Background: Remnant cholesterol (Remnant-C), rather than TG, is believed to increase the risk of atherosclerotic cardiovascular disease. We evaluated whether Remnant-C is associated with an estimated 10-year risk of a first hard atherosclerotic cardiovascular disease event., Methods: This cross-sectional study was performed on 2,048 participants (1,130 men and 918 women), aged 40 to 79 years, from the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018. The independent variable was Remnant-C; the dependent variable was the 10-year risk of a first hard atherosclerotic cardiovascular disease event (defined as non-fatal myocardial infarction, coronary heart disease death, or stroke, over a 10-year period among people free from atherosclerotic cardiovascular disease at the beginning of the period). The other variables, such as smoking behavior, hypertension, diabetes etc., were considered as the potential effect modifiers. Multivariate linear regression models and smooth curve fittings were used to evaluate the association between Remnant-C and the 10-year risk of a first hard atherosclerotic cardiovascular disease event. Subgroup analyses stratified by gender and race were also performed., Results: A positive association between Remnant-C and the 10-year risk of a first hard atherosclerotic cardiovascular disease event was demonstrated in the fully adjusted model (β = 0.078, [95%CI: 0.061-0.094], P < 0.001). The 10-year risk was increased by 0.078% for each 1 mg/dl increase in Remnant-C. In the subgroup analysis for gender, this association remained in both men (β = 0.128, [95%CI: 0.108-0.148], P < 0.001) and women (β = 0.043, [95%CI: 0.016-0.070], P = 0.00179). However, in the subgroup analysis for race, the association between Remnant-C and the 10-year risk reached an inflection point at remnant-C 38 mg/dL, where a positive association was not as obvious for the non-Hispanic Black population as for other racial groups., Conclusions: Remnant-C positively correlates with a 10-year risk of a first hard atherosclerotic cardiovascular disease event., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Yang, Yang, Shi, Yang, Zhang, Gao, Shi and Qu.)
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- 2022
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28. Prediction models for cardiovascular disease risk in the general population: systematic review
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Gary S. Collins, Michael Maia Schlüssel, Lotty Hooft, Yvonne T. van der Schouw, Karel G.M. Moons, Ioanna Tzoulaki, Virginia Chiocchia, Linda M. Peelen, Camille Lassale, Johanna A A G Damen, Corran Roberts, Thomas P. A. Debray, George C.M. Siontis, Ewoud Schuit, Pauline Heus, James A. Black, and Stephen Gerry
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EXTERNAL VALIDATION ,DYNAMIC PREDICTION ,Population ,MEDLINE ,10-YEAR RISK ,Disease ,Review ,030204 cardiovascular system & hematology ,computer.software_genre ,03 medical and health sciences ,0302 clinical medicine ,Medicine, General & Internal ,Risk Factors ,General & Internal Medicine ,Journal Article ,Humans ,Medicine ,CORONARY-HEART-DISEASE ,COHORT ,030212 general & internal medicine ,education ,METAANALYSIS ,Medicine(all) ,education.field_of_study ,Science & Technology ,business.industry ,REGRESSION-ANALYSIS ,Research ,DIAGNOSIS TRIPOD ,Regression analysis ,General Medicine ,3. Good health ,PROGNOSTIC MODEL ,1117 Public Health And Health Services ,Cardiovascular Diseases ,Predictive value of tests ,Cohort ,Data mining ,business ,Risk assessment ,INDIVIDUAL PARTICIPANT DATA ,computer ,Life Sciences & Biomedicine ,Predictive modelling ,Demography - Abstract
Objective: To provide an overview of prediction models for risk of cardiovascular disease (CVD) in the general population. Design: Systematic review. Data sources: Medline and Embase until June 2013. Eligibility criteria for study selection: Studies describing the development or external validation of a multivariable model for predicting CVD risk in the general population. Results: 9965 references were screened, of which 212 articles were included in the review, describing the development of 363 prediction models and 473 external validations. Most models were developed in Europe (n=167, 46%), predicted risk of fatal or non-fatal coronary heart disease (n=118, 33%) over a 10 year period (n=209, 58%). The most common predictors were smoking (n=325, 90%) and age (n=321, 88%), and most models were sex specific (n=250, 69%). Substantial heterogeneity in predictor and outcome definitions was observed between models, and important clinical and methodological information were often missing. The prediction horizon was not specified for 49 models (13%), and for 92 (25%) crucial information was missing to enable the model to be used for individual risk prediction. Only 132 developed models (36%) were externally validated and only 70 (19%) by independent investigators. Model performance was heterogeneous and measures such as discrimination and calibration were reported for only 65% and 58% of the external validations, respectively. Conclusions: There is an excess of models predicting incident CVD in the general population. The usefulness of most of the models remains unclear owing to methodological shortcomings, incomplete presentation, and lack of external validation and model impact studies. Rather than developing yet another similar CVD risk prediction model, in this era of large datasets, future research should focus on externally validating and comparing head-to-head promising CVD risk models that already exist, on tailoring or even combining these models to local settings, and investigating whether these models can be extended by addition of new predictors.
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- 2016
29. Predicting CHD risk in France: a pooled analysis of the D.E.S.I.R., Three City, PRIME, and SU.VI.MAX studies
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Muriel Tafflet, Jean Philippe Empana, Michèle Montaye, Sébastien Czernichow, S Bineau, Jean-Bernard Ruidavets, Sylvie Escolano, Pierre Ducimetière, Beverley Balkau, Bernadette Haas, AC Vergnaux, Paris-Centre de Recherche Cardiovasculaire (PARCC - UMR-S U970), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de la Santé et de la Recherche Médicale (INSERM), Unité de Recherche en Epidémiologie Nutritionnelle (UREN), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Sorbonne Paris Cité (USPC)-Université Paris 13 (UP13)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut National de la Recherche Agronomique (INRA), INSERM, U708, Université Paris 06, Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, Université Lille Nord de France (COMUE), Université de Strasbourg (UNISTRA), Dept Publ Hlth, Universiteit Gent = Ghent University [Belgium] (UGENT), Fondation pour la Recherche Medicale, Caisse Nationale Maladie des Travailleurs Salaries, Direction Generale de la Sante, MGEN, Institut de la Longevite, Conseils Regionaux of Aquitaine and Bourgogne, Fondation de France, Ministry of Research, INSERM contracts with CNAMTS [Caisse Nationale d'Assurance Maladie de Travailleurs Salaries (French National Health Insurance Agency for Wage Earners)], Lilly Novartis Pharma, sanofi-aventis, INSERM (Reseaux en Sante Publique, Interactions entre les determinants de la sante, Cohortes Sante TGIR), Association Diabete Risque Vasculaire, Federation Francaise de Cardiologie, La Fondation de France, ALFEDIAM, ONIVINS, Ardix Medical, Bayer Diagnostics, Becton Dickinson, Cardionics, Merck Sante, NovoNordisk, Pierre Fabre, Roche, and Topcon
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Male ,MULTIPLE BIOMARKERS ,Pediatrics ,Time Factors ,Epidemiology ,[SDV]Life Sciences [q-bio] ,10-YEAR RISK ,Coronary Disease ,Kaplan-Meier Estimate ,030204 cardiovascular system & hematology ,risk prediction ,0302 clinical medicine ,FRAMINGHAM ,Multicenter Studies as Topic ,risk factors ,Medicine ,030212 general & internal medicine ,Family history ,10. No inequality ,POPULATION ,Randomized Controlled Trials as Topic ,2. Zero hunger ,Framingham Risk Score ,MEN ,Middle Aged ,Prognosis ,3. Good health ,Coronary heart disease ,CARDIOVASCULAR-DISEASE ,Disease Progression ,Population study ,Female ,France ,Cardiology and Cardiovascular Medicine ,Risk assessment ,Algorithms ,medicine.medical_specialty ,Waist ,Risk Assessment ,VALIDATION ,03 medical and health sciences ,Humans ,CORONARY-HEART-DISEASE ,COHORT ,Aged ,Proportional Hazards Models ,business.industry ,Proportional hazards model ,Reproducibility of Results ,Asymptomatic Diseases ,FOLLOW-UP ,business ,Body mass index ,Demography - Abstract
International audience; Background: We aimed to develop and validate a simple coronary heart disease (CHD) risk algorithm applicable to asymptomatic men and women in France, and to compare its accuracy with that of the last published version of the Framingham risk function for cardiovascular disease. Design: A pooled analysis of four French prospective general-population studies. Methods: The baseline and follow-up data from D.E.S.I.R., PRIME, Three City, and SU.VI.MAX studies were used. The 10-year CHD risk was estimated by the Cox proportional hazards model with candidate variables including age, gender, body mass index, waist circumference, family history of coronary heart disease, smoking status, diabetes status, systolic blood pressure, and total and high-density lipoprotein (HDL) cholesterol. Results: The study population included 22,256 subjects (61.4% men) aged (SD) 56.0 years (8.3) without a personal history of CHD at baseline. After a mean follow-up of 8.0 years (2.3), 788 first CHD events occurred, 726 in men and 62 in women. The final model included age, gender, age x gender interaction, current smoking status, diabetes status, systolic blood pressure, total and HDL cholesterol. Using this model, the number of predicted coronary events fitted that given by the 10-year Kaplan-Meier survival estimates within each decile of estimated risk (calibration). This model had fair discrimination: Harrell C-index, 0.7831 (95% CI: 0.7704-0.7957). For comparison, the recalibrated Framingham risk function had equivalent performances compared to the French risk equation. Conclusion: Our 10-year French CHD risk equation based on traditional risk factors performed at least as well as the recalibrated Framingham cardiovascular disease risk function.
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- 2011
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30. Artificial intelligence framework for predictive cardiovascular and stroke risk assessment models: A narrative review of integrated approaches using carotid ultrasound.
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Jamthikar AD, Gupta D, Saba L, Khanna NN, Viskovic K, Mavrogeni S, Laird JR, Sattar N, Johri AM, Pareek G, Miner M, Sfikakis PP, Protogerou A, Viswanathan V, Sharma A, Kitas GD, Nicolaides A, Kolluri R, and Suri JS
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- Artificial Intelligence, Carotid Arteries diagnostic imaging, Humans, Risk Assessment, Risk Factors, Cardiovascular Diseases diagnostic imaging, Cardiovascular Diseases epidemiology, Plaque, Atherosclerotic, Stroke diagnostic imaging, Stroke epidemiology
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Recent Findings: Cardiovascular disease (CVD) is the leading cause of mortality and poses challenges for healthcare providers globally. Risk-based approaches for the management of CVD are becoming popular for recommending treatment plans for asymptomatic individuals. Several conventional predictive CVD risk models based do not provide an accurate CVD risk assessment for patients with different baseline risk profiles. Artificial intelligence (AI) algorithms have changed the landscape of CVD risk assessment and demonstrated a better performance when compared against conventional models, mainly due to its ability to handle the input nonlinear variations. Further, it has the flexibility to add risk factors derived from medical imaging modalities that image the morphology of the plaque. The integration of noninvasive carotid ultrasound image-based phenotypes with conventional risk factors in the AI framework has further provided stronger power for CVD risk prediction, so-called "integrated predictive CVD risk models.", Purpose: of the review: The objective of this review is (i) to understand several aspects in the development of predictive CVD risk models, (ii) to explore current conventional predictive risk models and their successes and challenges, and (iii) to refine the search for predictive CVD risk models using noninvasive carotid ultrasound as an exemplar in the artificial intelligence-based framework., Conclusion: Conventional predictive CVD risk models are suboptimal and could be improved. This review examines the potential to include more noninvasive image-based phenotypes in the CVD risk assessment using powerful AI-based strategies., (Copyright © 2020 Elsevier Ltd. All rights reserved.)
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- 2020
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31. Cardiovascular/stroke risk predictive calculators: a comparison between statistical and machine learning models.
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Jamthikar A, Gupta D, Saba L, Khanna NN, Araki T, Viskovic K, Mavrogeni S, Laird JR, Pareek G, Miner M, Sfikakis PP, Protogerou A, Viswanathan V, Sharma A, Nicolaides A, Kitas GD, and Suri JS
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Background: Statistically derived cardiovascular risk calculators (CVRC) that use conventional risk factors, generally underestimate or overestimate the risk of cardiovascular disease (CVD) or stroke events primarily due to lack of integration of plaque burden. This study investigates the role of machine learning (ML)-based CVD/stroke risk calculators (CVRC
ML ) and compares against statistically derived CVRC (CVRCStat ) based on (I) conventional factors or (II) combined conventional with plaque burden (integrated factors)., Methods: The proposed study is divided into 3 parts: (I) statistical calculator: initially, the 10-year CVD/stroke risk was computed using 13 types of CVRCStat (without and with plaque burden) and binary risk stratification of the patients was performed using the predefined thresholds and risk classes; (II) ML calculator: using the same risk factors (without and with plaque burden), as adopted in 13 different CVRCStat , the patients were again risk-stratified using CVRCML based on support vector machine (SVM) and finally; (III) both types of calculators were evaluated using AUC based on ROC analysis, which was computed using combination of predicted class and endpoint equivalent to CVD/stroke events., Results: An Institutional Review Board approved 202 patients (156 males and 46 females) of Japanese ethnicity were recruited for this study with a mean age of 69±11 years. The AUC for 13 different types of CVRCStat calculators were: AECRS2.0 (AUC 0.83, P<0.001), QRISK3 (AUC 0.72, P<0.001), WHO (AUC 0.70, P<0.001), ASCVD (AUC 0.67, P<0.001), FRScardio (AUC 0.67, P<0.01), FRSstroke (AUC 0.64, P<0.001), MSRC (AUC 0.63, P=0.03), UKPDS56 (AUC 0.63, P<0.001), NIPPON (AUC 0.63, P<0.001), PROCAM (AUC 0.59, P<0.001), RRS (AUC 0.57, P<0.001), UKPDS60 (AUC 0.53, P<0.001), and SCORE (AUC 0.45, P<0.001), while the AUC for the CVRCML with integrated risk factors (AUC 0.88, P<0.001), a 42% increase in performance. The overall risk-stratification accuracy for the CVRCML with integrated risk factors was 92.52% which was higher compared all the other CVRCStat. , Conclusions: ML-based CVD/stroke risk calculator provided a higher predictive ability of 10-year CVD/stroke compared to the 13 different types of statistically derived risk calculators including integrated model AECRS 2.0., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/cdt.2020.01.07). The series “Advanced Imaging in The Diagnosis of Cardiovascular Diseases” was commissioned by the editorial office without any funding or sponsorship. LS served as the unpaid Guest Editor of the series and serves as an unpaid editorial board member of Cardiovascular Diagnosis and Therapy from July 2019 to June 2021. JSS is affiliated to AtheroPointTM, focused in the area of stroke and cardiovascular imaging. The authors have no other conflicts of interest to declare., (2020 Cardiovascular Diagnosis and Therapy. All rights reserved.)- Published
- 2020
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32. A low-cost machine learning-based cardiovascular/stroke risk assessment system: integration of conventional factors with image phenotypes.
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Jamthikar A, Gupta D, Khanna NN, Saba L, Araki T, Viskovic K, Suri HS, Gupta A, Mavrogeni S, Turk M, Laird JR, Pareek G, Miner M, Sfikakis PP, Protogerou A, Kitas GD, Viswanathan V, Nicolaides A, Bhatt DL, and Suri JS
- Abstract
Background: Most cardiovascular (CV)/stroke risk calculators using the integration of carotid ultrasound image-based phenotypes (CUSIP) with conventional risk factors (CRF) have shown improved risk stratification compared with either method. However such approaches have not yet leveraged the potential of machine learning (ML). Most intelligent ML strategies use follow-ups for the endpoints but are costly and time-intensive. We introduce an integrated ML system using stenosis as an endpoint for training and determine whether such a system can lead to superior performance compared with the conventional ML system., Methods: The ML-based algorithm consists of an offline and online system. The offline system extracts 47 features which comprised of 13 CRF and 34 CUSIP. Principal component analysis (PCA) was used to select the most significant features. These offline features were then trained using the event-equivalent gold standard (consisting of percentage stenosis) using a random forest (RF) classifier framework to generate training coefficients. The online system then transforms the PCA-based test features using offline trained coefficients to predict the risk labels on test subjects. The above ML system determines the area under the curve (AUC) using a 10-fold cross-validation paradigm. The above system so-called "AtheroRisk-Integrated" was compared against "AtheroRisk-Conventional", where only 13 CRF were considered in a feature set., Results: Left and right common carotid arteries of 202 Japanese patients (Toho University, Japan) were retrospectively examined to obtain 395 ultrasound scans. AtheroRisk-Integrated system [AUC =0.80, P<0.0001, 95% confidence interval (CI): 0.77 to 0.84] showed an improvement of ~18% against AtheroRisk-Conventional ML (AUC =0.68, P<0.0001, 95% CI: 0.64 to 0.72)., Conclusions: ML-based integrated model with the event-equivalent gold standard as percentage stenosis is powerful and offers low cost and high performance CV/stroke risk assessment., Competing Interests: Conflicts of Interest: Dr. Suri is affiliated to AtheroPoint™, focused in the area of stroke and cardiovascular imaging. Dr. Bhatt discloses the following relationships—Advisory Board: Cardax, Cereno Scientific, Elsevier Practice Update Cardiology, Medscape Cardiology, PhaseBio, Regado Biosciences; Board of Directors: Boston VA Research Institute, Society of Cardiovascular Patient Care, TobeSoft; Chair: American Heart Association Quality Oversight Committee; Data Monitoring Committees: Baim Institute for Clinical Research (formerly Harvard Clinical Research Institute, for the PORTICO trial, funded by St. Jude Medical, now Abbott), Cleveland Clinic (including for the ExCEED trial, funded by Edwards), Duke Clinical Research Institute, Mayo Clinic, Mount Sinai School of Medicine (for the ENVISAGE trial, funded by Daiichi Sankyo), Population Health Research Institute; Honoraria: American College of Cardiology (Senior Associate Editor, Clinical Trials and News, ACC.org; Vice-Chair, ACC Accreditation Committee), Baim Institute for Clinical Research (formerly Harvard Clinical Research Institute; RE-DUAL PCI clinical trial steering committee funded by Boehringer Ingelheim; AEGIS-II executive committee funded by CSL Behring), Belvoir Publications (Editor in Chief, Harvard Heart Letter), Duke Clinical Research Institute (clinical trial steering committees), HMP Global (Editor in Chief, Journal of Invasive Cardiology), Journal of the American College of Cardiology (Guest Editor; Associate Editor), Medtelligence/ReachMD (CME steering committees), Population Health Research Institute (for the COMPASS operations committee, publications committee, steering committee, and USA national co-leader, funded by Bayer), Slack Publications (Chief Medical Editor, Cardiology Today’s Intervention), Society of Cardiovascular Patient Care (Secretary/Treasurer), WebMD (CME steering committees); Other: Clinical Cardiology (Deputy Editor), NCDR-ACTION Registry Steering Committee (Chair), VA CART Research and Publications Committee (Chair); Research Funding: Abbott, Amarin, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Chiesi, CSL Behring, Eisai, Ethicon, Ferring Pharmaceuticals, Forest Laboratories, Idorsia, Ironwood, Ischemix, Lilly, Medtronic, PhaseBio, Pfizer, Regeneron, Roche, Sanofi Aventis, Synaptic, The Medicines Company; Royalties: Elsevier (Editor, Cardiovascular Intervention: A Companion to Braunwald’s Heart Disease); Site Co-Investigator: Biotronik, Boston Scientific, St. Jude Medical (now Abbott), Svelte; Trustee: American College of Cardiology; Unfunded Research: FlowCo, Fractyl, Merck, Novo Nordisk, PLx Pharma, Takeda. The other authors have no conflicts of interest to declare., (2019 Cardiovascular Diagnosis and Therapy. All rights reserved.)
- Published
- 2019
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33. Evaluation of cardiovascular risk predicted by different SCORE equations: The Netherlands as an example
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Daan Kromhout, W. M. Monique Verschuren, Ineke van Dis, Johanna M. Geleijnse, and Jolanda M. A. Boer
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Adult ,Male ,Time Factors ,Nutrition and Disease ,Epidemiology ,clinical-practice ,cholesterol determination ,Risk Assessment ,Sex Factors ,project ,Predictive Value of Tests ,Risk Factors ,Cause of Death ,Voeding en Ziekte ,medicine ,Health Status Indicators ,Humans ,Prospective Studies ,Risk factor ,Prospective cohort study ,Risk management ,Netherlands ,Cause of death ,VLAG ,disease ,Models, Statistical ,Framingham Risk Score ,business.industry ,10-year risk ,Reproducibility of Results ,Guideline ,Middle Aged ,medicine.disease ,mortality ,Cardiovascular Diseases ,Predictive value of tests ,Female ,Medical emergency ,Cardiology and Cardiovascular Medicine ,business ,Risk assessment ,europe ,Follow-Up Studies ,Demography - Abstract
Background: In Europe, for primary prevention of cardiovascular diseases (CVD), the Systematic COronary Risk Evaluation (SCORE) risk charts for high-risk and low-risk regions (SCORE-high and SCORE-low, respectively) are used. For the Dutch ‘Clinical Practice Guideline for Cardiovascular Risk Management’ an adapted SCORE risk chart (SCORE-NL) was developed in collaboration with the SCORE group. We evaluated these three SCORE equations using Dutch risk factor and mortality data. Design: Prospective cohort study with 10-year follow-up. Methods: Baseline data were collected between 1987 and 1997 in 32 885 persons aged 37.5–62.5 years. Vital status was checked and causes of death were obtained from Statistics Netherlands. On the basis of the level of risk factors, the expected number of CVD deaths was calculated by applying the three SCORE equations and compared with the observed number. Results: The observed CVD mortality was three-fold higher in men (n=242; 1.6%) than in women (n=83; 0.5%). On the basis of SCORE-NL, 8.5% of the men and 0.8% of the women had a CVD mortality risk of 5% or more. The ratio of the observed-to-expected number of CVD deaths was 0.75 for men and 0.55 for women using SCORE-NL, 0.54 and 0.56 using SCORE-high, and 1.11 and 0.95 using SCORE-low. Conclusion: At the population level, SCORE-low predicts the number of CVD deaths well, whereas both SCORE-NL and SCORE-high overestimate the number of CVD deaths by a factor 1.5–2
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- 2010
34. Statins for Primary Prevention of Cardiovascular Disease: Review of Evidence and Recommendations for Clinical Practice.
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Kazi DS, Penko JM, and Bibbins-Domingo K
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- Age Factors, Cardiovascular Diseases prevention & control, Cost-Benefit Analysis, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors adverse effects, Hydroxymethylglutaryl-CoA Reductase Inhibitors economics, Life Style, Practice Guidelines as Topic, Randomized Controlled Trials as Topic, Risk Assessment, Atherosclerosis prevention & control, Hydroxymethylglutaryl-CoA Reductase Inhibitors administration & dosage, Primary Prevention methods
- Abstract
Numerous large randomized clinical trials have shown that statin therapy is effective and safe for primary prevention of atherosclerotic cardiovascular disease (CVD) for adults aged 40 to 75 years and support the use of 10-year CVD risk as a means to identify individuals for treatment. Uncertainty exists in those older than 75 years who may be more likely to benefit because of their underlying CVD risk, but also face uncertain harms. Several high-quality mathematical simulation models have shown that statin therapy is cost-effective for primary prevention of atherosclerotic CVD. Despite effectiveness and safety, statins are underutilized for primary prevention., (Copyright © 2017 Elsevier Inc. All rights reserved.)
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- 2017
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