| 1. |
- Kaptoge, S., et al.
(författare)
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World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions
- 2019
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Ingår i: Lancet Global Health. - : Elsevier BV. - 2214-109X. ; 7:10
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Tidskriftsartikel (refereegranskat)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. Copyright (C) 2019 The Author(s). Published by Elsevier Ltd.
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| 2. |
- Pennells, Lisa, et al.
(författare)
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Equalization of four cardiovascular risk algorithms after systematic recalibration : individual-participant meta-analysis of 86 prospective studies
- 2019
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Ingår i: European Heart Journal. - : Oxford University Press (OUP). - 0195-668X .- 1522-9645. ; 40:7, s. 621-
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Tidskriftsartikel (refereegranskat)abstract
- Aims: There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after ‘recalibration’, a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied.Methods and results: Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at ‘high’ 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29–39% of individuals aged ≥40 years as high risk. By contrast, recalibration reduced this proportion to 22–24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44–51 such individuals using original algorithms, in contrast to 37–39 individuals with recalibrated algorithms.Conclusion: Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need.
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| 3. |
- Wood, Angela M., et al.
(författare)
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Risk thresholds for alcohol consumption : combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies
- 2018
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Ingår i: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 391:10129, s. 1513-1523
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Tidskriftsartikel (refereegranskat)abstract
- Background: Low-risk limits recommended for alcohol consumption vary substantially across different national guidelines. To define thresholds associated with lowest risk for all-cause mortality and cardiovascular disease, we studied individual-participant data from 599 912 current drinkers without previous cardiovascular disease.Methods: We did a combined analysis of individual-participant data from three large-scale data sources in 19 high-income countries (the Emerging Risk Factors Collaboration, EPIC-CVD, and the UK Biobank). We characterised dose-response associations and calculated hazard ratios (HRs) per 100 g per week of alcohol (12.5 units per week) across 83 prospective studies, adjusting at least for study or centre, age, sex, smoking, and diabetes. To be eligible for the analysis, participants had to have information recorded about their alcohol consumption amount and status (ie, non-drinker vs current drinker), plus age, sex, history of diabetes and smoking status, at least 1 year of follow-up after baseline, and no baseline history of cardiovascular disease. The main analyses focused on current drinkers, whose baseline alcohol consumption was categorised into eight predefined groups according to the amount in grams consumed per week. We assessed alcohol consumption in relation to all-cause mortality, total cardiovascular disease, and several cardiovascular disease subtypes. We corrected HRs for estimated long-term variability in alcohol consumption using 152 640 serial alcohol assessments obtained some years apart (median interval 5.6 years [5th-95th percentile 1.04-13.5]) from 71 011 participants from 37 studies.Findings: In the 599 912 current drinkers included in the analysis, we recorded 40 310 deaths and 39 018 incident cardiovascular disease events during 5.4 million person-years of follow-up. For all-cause mortality, we recorded a positive and curvilinear association with the level of alcohol consumption, with the minimum mortality risk around or below 100 g per week. Alcohol consumption was roughly linearly associated with a higher risk of stroke (HR per 100 g per week higher consumption 1.14, 95% CI, 1.10-1.17), coronary disease excluding myocardial infarction (1.06, 1.00-1.11), heart failure (1.09, 1.03-1.15), fatal hypertensive disease (1.24, 1.15-1.33); and fatal aortic aneurysm (1.15, 1.03-1.28). By contrast, increased alcohol consumption was loglinearly associated with a lower risk of myocardial infarction (HR 0.94, 0.91-0.97). In comparison to those who reported drinking >0-<= 100 g per week, those who reported drinking >100-<= 200 g per week, >200-<= 350 g per week, or >350 g per week had lower life expectancy at age 40 years of approximately 6 months, 1-2 years, or 4-5 years, respectively.Interpretation: In current drinkers of alcohol in high-income countries, the threshold for lowest risk of all-cause mortality was about 100 g/week. For cardiovascular disease subtypes other than myocardial infarction, there were no clear risk thresholds below which lower alcohol consumption stopped being associated with lower disease risk. These data support limits for alcohol consumption that are lower than those recommended in most current guidelines.
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| 4. |
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| 5. |
- He, L, et al.
(författare)
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Impact of classical risk factors of type 2 diabetes among Asian Indian, Chinese and Japanese populations
- 2015
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Ingår i: Diabetes & Metabolism. - : Elsevier. - 1262-3636 .- 1878-1780. ; 41:5, s. 401-409
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Tidskriftsartikel (refereegranskat)abstract
- Aims. This review investigated the population impact of major modifiable type 2 diabetes (T2D) risk factors, with special focus on native Asian Indians, to estimate population attributable risks (PARs) and compare them with estimates from Chinese and Japanese populations. Methods. Information was obtained on risk factors in 21,041 Asian Indian, 17,774 Chinese and 17,986 Japanese populations from multiple, large, cross-sectional studies (the DECODA project) of T2D. Crude and adjusted PARs were estimated for the major T2D risk factors. Results. Age had the highest crude and adjusted PARs among Asian Indians and Chinese in contrast to waist hip ratio among Japanese. After adjusting for age, the PAR for body mass index (BMI) in Asian Indians (41.4% [95% CI: 37.2%; 45.4%]) was second only to triglycerides (46.4% [95% CI: 39.5%; 52.8%]) compared with 35.8% [95% CI: 29.9%; 41.4%] in Japanese and 38.4% [95% CI: 33.5%; 43.2%] in Chinese people. The PAR for BMI adjusted for age, LDL and triglycerides (39.7% [95% CI: 31.6%; 47.2%]) was higher than for any other factor in Asian Indians, and was much higher than in the Chinese (16.8% [95% CI: 3.0%; 30.9%]) and Japanese (30.4% [95% CI: 17.5%; 42.2%]) populations. Conclusion. This review provides estimates of the association between major risk factors and prevalences of T2D among Asian populations by examining their PARs from large population-based samples. From a public-health point of view, the importance of BMI in Asian Indians is especially highlighted in comparison to the other Asian populations. Given these results and other recent findings on the causality link between BMI and T2D, it can be postulated that obesity may be involved in the aetiology of T2D through interaction with ethnic-specific genetic factors, although ethnicity itself is not a direct risk factor for T2D as people of all ethnic backgrounds develop diabetes.
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