Dataset Information

A coronary heart disease prediction model: the Korean Heart Study.

ABSTRACT:

Objective

The objectives of this study were to develop a coronary heart disease (CHD) risk model among the Korean Heart Study (KHS) population and compare it with the Framingham CHD risk score.

Design

A prospective cohort study within a national insurance system.

Setting

18 health promotion centres nationwide between 1996 and 2001 in Korea.

Participants

268 315 Koreans between the ages of 30 and 74 years without CHD at baseline.

Outcome measure

Non-fatal or fatal CHD events between 1997 and 2011. During an 11.6-year median follow-up, 2596 CHD events (1903 non-fatal and 693 fatal) occurred in the cohort. The optimal CHD model was created by adding high-density lipoprotein (HDL)-cholesterol, low-density lipoprotein (LDL)-cholesterol and triglycerides to the basic CHD model, evaluating using the area under the receiver operating characteristic curve (ROC) and continuous net reclassification index (NRI).

Results

The optimal CHD models for men and women included HDL-cholesterol (NRI=0.284) and triglycerides (NRI=0.207) from the basic CHD model, respectively. The discrimination using the CHD model in the Korean cohort was high: the areas under ROC were 0.764 (95% CI 0.752 to 0.774) for men and 0.815 (95% CI 0.795 to 0.835) for women. The Framingham risk function predicted 3-6 times as many CHD events than observed. Recalibration of the Framingham function using the mean values of risk factors and mean CHD incidence rates of the KHS cohort substantially improved the performance of the Framingham functions in the KHS cohort.

Conclusions

The present study provides the first evidence that the Framingham risk function overestimates the risk of CHD in the Korean population where CHD incidence is low. The Korean CHD risk model is well-calculated alternations which can be used to predict an individual's risk of CHD and provides a useful guide to identify the groups at high risk for CHD among Koreans.

SUBMITTER: Jee SH

PROVIDER: S-EPMC4039825 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A coronary heart disease prediction model: the Korean Heart Study.

Jee Sun Ha SH Jang Yangsoo Y Oh Dong Joo DJ Oh Byung-Hee BH Lee Sang Hoon SH Park Seong-Wook SW Seung Ki-Bae KB Mok Yejin Y Jung Keum Ji KJ Kimm Heejin H Yun Young Duk YD Baek Soo Jin SJ Lee Duk Chul DC Choi Sung Hee SH Kim Moon Jong MJ Sung Jidong J Cho BeLong B Kim Eung Soo ES Yu Byung-Yeon BY Lee Tae-Yong TY Kim Jong Sung JS Lee Yong-Jin YJ Oh Jang-Kyun JK Kim Sung Hi SH Park Jong-Ku JK Koh Sang Baek SB Park Sat Byul SB Lee Soon Young SY Yoo Cheol-In CI Kim Moon Chan MC Kim Hong-Kyu HK Park Joo-Sung JS Kim Hyeon Chang HC Lee Gyu Jang GJ Woodward Mark M

BMJ open 20140521 5

<h4>Objective</h4>The objectives of this study were to develop a coronary heart disease (CHD) risk model among the Korean Heart Study (KHS) population and compare it with the Framingham CHD risk score.<h4>Design</h4>A prospective cohort study within a national insurance system.<h4>Setting</h4>18 health promotion centres nationwide between 1996 and 2001 in Korea.<h4>Participants</h4>268 315 Koreans between the ages of 30 and 74 years without CHD at baseline.<h4>Outcome measure</h4>Non-fatal or fa ...[more]

PMID: 24848088

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Project description:ObjectiveTo analyze the influential factors of frailty in elderly patients with coronary heart disease (CHD), develop a nomogram-based risk prediction model for this population, and validate its predictive performance.MethodsA total of 592 elderly patients with CHD were conveniently selected and enrolled from 3 tertiary hospitals, 5 secondary hospitals, and 3 community health service centers in China between October 2022 and January 2023. Data collection involved the use of the general information questionnaire, the Frail scale, and the instrumental ability of daily living assessment scale. And the patients were categorized into two groups based on frailty, and χ2 test as well as logistic regression analysis were used to identify and determine the influencing factors of frailty. The nomograph prediction model for elderly patients with CHD was developed using R software (version 4.2.2). The Hosmer-Lemeshow test and the area under the receiver operating characteristic (ROC) curve were employed to assess the predictive performance of the model. Additionally, the Bootstrap resampling method was utilized to validate the model and generate the calibration curve of the prediction model.ResultsThe prevalence of frailty in elderly patients with CHD was 30.07%. The multiple factor analysis revealed that poor health status (OR = 28.169)/general health status (OR = 18.120), age (OR = 1.046), social activities (OR = 0.673), impaired instrumental ability of daily living (OR = 2.384) were independent risk factors for frailty (all P < 0.05). The area under the ROC curve of the nomograph prediction model was 0.847 (95% CI: 0.809 ~ 0.878, P < 0.001), with a sensitivity of 0.801, and specificity of 0.793; the Hosmer- Lemeshow χ2 value was 12.646 (P = 0.125). The model validation results indicated that the C value of 0.839(95% CI: 0.802 ~ 0.879) and Brier score of 0.139, demonstrating good consistency between predicted and actual values.ConclusionThe prevalence of frailty is high among elderly patients with CHD, and it is influenced by various factors such as health status, age, lack of social participation, and impaired ability of daily life. These factors have certain predictive value for identifying frailty early and intervention in elderly patients with CHD.

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Dataset Information

A coronary heart disease prediction model: the Korean Heart Study.

Objective

Design

Setting

Participants

Outcome measure

Results

Conclusions

Publications

A coronary heart disease prediction model: the Korean Heart Study.

Similar Datasets

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