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We began analyzing https://www.nature.com/articles/s41598-021-93840-2, but it redirected us to https://www.nature.com/articles/s41598-021-93840-2. The analysis below is for the second page.

Title[redir]:
Prediction of 8-year risk of cardiovascular diseases in Korean adult population | Scientific Reports
Description:
Although many prediction models for cardiovascular diseases (CVDs) have been developed and validated for Western populations, the development of CVD prediction models for Asians has been slow. Our cohort study retrospectively analyzed the incidence of CVD that occurred between January 1, 2009, and December 31, 2016, in all Koreans who underwent national health screening. This dataset included 21,581,796 adults between the ages of 40 and 79 years (10,412,947 men, 11,168,849 women) without CVD at baseline. The primary outcome, CVD, was defined as the development of any of the following: acute coronary syndrome, cerebral infarction, and cerebral hemorrhage, as defined with health insurance claims data. The prediction model was constructed by Cox proportional hazard regression and validated with tenfold cross-validation. The performance of the models was evaluated through Harrell’s C-index and Brier score. The discrimination of the models was assessed by the area under the receiver operating characteristic curve (AUROC). Our model showed an AUROC of 0.762 in men and 0.811 in women. The Brier score of our model was 0.018 in men and 0.010 in women, which was better than the pooled cohort equation (PCE). Our novel model performed better than the FRS and PCE for Koreans.

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Keywords {🔍}

risk, cvd, model, article, women, men, google, scholar, pubmed, health, study, data, prediction, cohort, disease, alcohol, cardiovascular, pce, population, nature, heart, consumption, models, screening, korea, smoking, coronary, results, table, activity, years, hazard, korean, national, auroc, physical, cas, analysis, developed, cox, proportional, countries, information, year, koreans, performance, pooled, variables, studies, statistical,

Topics {✒️}

nature portfolio kr/portal/eng/index privacy policy nature advertising future research considerations social media hyung-jin yoon reprints china regional research receiver-operator characteristic curve receiver-operating characteristic curve cigarette smoking status/dose/duration world health organization author information authors bmj open 7 cardiology/american heart association gamma-glutamyl transferase level su hwan kim body mass index small p-values indicating permissions sex-specific prediction model world health organ author correspondence original author tenfold cross-validation technique high-density lipoprotein cholesterol low-density lipoprotein cholesterol identifying high-risk groups 2013 acc/aha guideline machine learning derived acc/aha guidelines randomized controlled trial pooled cohort equations atherosclerotic cardiovascular disease health screening data long-term cohort study national registry data blood/urine test conducted offline model development percutaneous coronary intervention full size image world population ageing proportional hazard assumption korean adult population seoul national university single insurance system

Schema {🗺️}

WebPage:
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         headline:Prediction of 8-year risk of cardiovascular diseases in Korean adult population
         description:Although many prediction models for cardiovascular diseases (CVDs) have been developed and validated for Western populations, the development of CVD prediction models for Asians has been slow. Our cohort study retrospectively analyzed the incidence of CVD that occurred between January 1, 2009, and December 31, 2016, in all Koreans who underwent national health screening. This dataset included 21,581,796 adults between the ages of 40 and 79 years (10,412,947 men, 11,168,849 women) without CVD at baseline. The primary outcome, CVD, was defined as the development of any of the following: acute coronary syndrome, cerebral infarction, and cerebral hemorrhage, as defined with health insurance claims data. The prediction model was constructed by Cox proportional hazard regression and validated with tenfold cross-validation. The performance of the models was evaluated through Harrell’s C-index and Brier score. The discrimination of the models was assessed by the area under the receiver operating characteristic curve (AUROC). Our model showed an AUROC of 0.762 in men and 0.811 in women. The Brier score of our model was 0.018 in men and 0.010 in women, which was better than the pooled cohort equation (PCE). Our novel model performed better than the FRS and PCE for Koreans.
         datePublished:2021-07-12T00:00:00Z
         dateModified:2021-07-12T00:00:00Z
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      headline:Prediction of 8-year risk of cardiovascular diseases in Korean adult population
      description:Although many prediction models for cardiovascular diseases (CVDs) have been developed and validated for Western populations, the development of CVD prediction models for Asians has been slow. Our cohort study retrospectively analyzed the incidence of CVD that occurred between January 1, 2009, and December 31, 2016, in all Koreans who underwent national health screening. This dataset included 21,581,796 adults between the ages of 40 and 79 years (10,412,947 men, 11,168,849 women) without CVD at baseline. The primary outcome, CVD, was defined as the development of any of the following: acute coronary syndrome, cerebral infarction, and cerebral hemorrhage, as defined with health insurance claims data. The prediction model was constructed by Cox proportional hazard regression and validated with tenfold cross-validation. The performance of the models was evaluated through Harrell’s C-index and Brier score. The discrimination of the models was assessed by the area under the receiver operating characteristic curve (AUROC). Our model showed an AUROC of 0.762 in men and 0.811 in women. The Brier score of our model was 0.018 in men and 0.010 in women, which was better than the pooled cohort equation (PCE). Our novel model performed better than the FRS and PCE for Koreans.
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