Literature DB >> 33162431

Cardiac Risk in Prediction Models.

Hisashi Adachi1.   

Abstract

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Year:  2020        PMID: 33162431      PMCID: PMC8326167          DOI: 10.5551/jat.ED149

Source DB:  PubMed          Journal:  J Atheroscler Thromb        ISSN: 1340-3478            Impact factor:   4.928


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There are several exceptional models for cardiac risk prediction in the U.S. and Japan. In the U.S., the Framingham coronary heart disease (CHD) prediction scores were used to assist clinicians in estimating the absolute risk of any individuals [1)] . Recently, some studies have reported a 10-year cardiac risk using Framingham risk score (FRS) [2 - 4)] . Lagerweij GR, et al. [4)] suggested that the absolute predicted 10-year risks from different prediction models cannot be directly compared, and that treatment decisions often depend on which prediction model is applied and its recommended risk threshold, introducing unwanted practice variation into risk-based preventive strategies for cardiovascular disease (CVD). In our country, the Suita score was also developed to predict CHD for the Japanese urban population [5)] . Using the score, prediction of CHD model for patients with cardiac diseases was made in the Japan Atherosclerosis Society Guidelines for Prevention of Atherosclerotic Cardiovascular Diseases 2017 [6)] . Moreover, a new risk prediction model of CHD in participants with and without diabetes was also assessed [7)] . In particular, Nishimura K, et al. [5)] reported that a predictive score as a coronary risk factor for the Japanese population was more accurate for predicting CHD than the original FRS. Hirai H, et al. [7)] also showed that their new models could be useful to predict 3-year risk of CHD at least in the Japanese population and particularly in diabetic subjects. Menotti A, et al. [8)] reported that the magnitude of multivariable coefficients and hazard ratios of four cardiovascular risk factors across five worldwide regions of the Seven Countries Study (SCS) in predicting 50-year coronary deaths were compared. In the Tanushimaru study, one of the cohorts of the SCS, we have presented a computer model to predict individual survival and death based on six conventional atherosclerotic risk factors for the first time, using the supervised statistical pattern recognition method [9)] . Unfortunately, this model was not used to predict CHD risk because of the extremely low incidence of CHD in our cohort. Recently, Li Y, et al. [10)] reported the absolute 10-year risk of death from CHD, stroke, and CVD in 44,869 individuals in the age group of 40-79 years from 8 Japanese prospective cohorts. The strength of their study is the integrated individual participant data from multiple high-quality prospective cohorts with relatively recent baseline year along with the fact and that the large sample size enables creation of prediction models by CHD, stroke, and CVD. Moreover, these models showed good response in case of both men and women in terms of discrimination across end points for not only CHD but also stroke or CVD. This study appears to be very novel compared with the other studies mentioned above.

Conflicts of Interest

None.
  10 in total

1.  Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation.

Authors:  R B D'Agostino; S Grundy; L M Sullivan; P Wilson
Journal:  JAMA       Date:  2001-07-11       Impact factor: 56.272

2.  Predicting coronary heart disease using risk factor categories for a Japanese urban population, and comparison with the framingham risk score: the suita study.

Authors:  Kunihiro Nishimura; Tomonori Okamura; Makoto Watanabe; Michikazu Nakai; Misa Takegami; Aya Higashiyama; Yoshihiro Kokubo; Akira Okayama; Yoshihiro Miyamoto
Journal:  J Atheroscler Thromb       Date:  2014-03-25       Impact factor: 4.928

3.  Japan Atherosclerosis Society (JAS) Guidelines for Prevention of Atherosclerotic Cardiovascular Diseases 2017.

Authors:  Makoto Kinoshita; Koutaro Yokote; Hidenori Arai; Mami Iida; Yasushi Ishigaki; Shun Ishibashi; Seiji Umemoto; Genshi Egusa; Hirotoshi Ohmura; Tomonori Okamura; Shinji Kihara; Shinji Koba; Isao Saito; Tetsuo Shoji; Hiroyuki Daida; Kazuhisa Tsukamoto; Juno Deguchi; Seitaro Dohi; Kazushige Dobashi; Hirotoshi Hamaguchi; Masumi Hara; Takafumi Hiro; Sadatoshi Biro; Yoshio Fujioka; Chizuko Maruyama; Yoshihiro Miyamoto; Yoshitaka Murakami; Masayuki Yokode; Hiroshi Yoshida; Hiromi Rakugi; Akihiko Wakatsuki; Shizuya Yamashita
Journal:  J Atheroscler Thromb       Date:  2018-08-22       Impact factor: 4.928

4.  The strength of the multivariable associations of major risk factors predicting coronary heart disease mortality is homogeneous across different areas of the Seven Countries Study during 50-year follow-up.

Authors:  Alessandro Menotti; Paolo Emilio Puddu; Hisashi Adachi; Anthony Kafatos; Hanna Tolonen; Daan Kromhout
Journal:  Acta Cardiol       Date:  2017-08-08       Impact factor: 1.718

5.  New computer model for prediction of individual 10-year mortality on the basis of conventional atherosclerotic risk factors.

Authors:  Kinuka Ogata; Takanobu Miyamoto; Hisashi Adachi; Yuji Hirai; Mika Enomoto; Ako Fukami; Kanako Yokoi; Akiko Kasahara; Eri Tsukagawa; Ayako Yoshimura; Aya Obuchi; Sachiko Nakamura; Tsutomu Imaizumi
Journal:  Atherosclerosis       Date:  2013-01-12       Impact factor: 5.162

6.  New risk prediction model of coronary heart disease in participants with and without diabetes: Assessments of the Framingham risk and Suita scores in 3-year longitudinal database in a Japanese population.

Authors:  Hiroyuki Hirai; Koichi Asahi; Satoshi Yamaguchi; Hirotaka Mori; Hiroaki Satoh; Kunitoshi Iseki; Toshiki Moriyama; Kunihiro Yamagata; Kazuhiko Tsuruya; Shouichi Fujimoto; Ichiei Narita; Tsuneo Konta; Masahide Kondo; Yugo Shibagaki; Masato Kasahara; Tsuyoshi Watanabe; Michio Shimabukuro
Journal:  Sci Rep       Date:  2019-02-26       Impact factor: 4.379

7.  Interpretation of CVD risk predictions in clinical practice: Mission impossible?

Authors:  G R Lagerweij; K G M Moons; G A de Wit; H Koffijberg
Journal:  PLoS One       Date:  2019-01-09       Impact factor: 3.240

8.  Comparison of coronary heart disease risk assessments among individuals with metabolic syndrome using three diagnostic definitions: a cross-sectional study from China.

Authors:  Xiaolin Peng; Liping Hao; Juan Zhou; Qin Gao; Jun Wang; Min Zhang; Jianping Ma; Changyi Wang; Hongen Chen
Journal:  BMJ Open       Date:  2018-10-25       Impact factor: 2.692

9.  Estimation of 10-Year Risk of Death from Coronary Heart Disease, Stroke, and Cardiovascular Disease in a Pooled Analysis of Japanese Cohorts: EPOCH-JAPAN.

Authors:  Yuanying Li; Hiroshi Yatsuya; Sachiko Tanaka; Hiroyasu Iso; Akira Okayama; Ichiro Tsuji; Kiyomi Sakata; Yoshihiro Miyamoto; Hirotsugu Ueshima; Katsuyuki Miura; Yoshitaka Murakami; Tomonori Okamura
Journal:  J Atheroscler Thromb       Date:  2020-10-10       Impact factor: 4.928

  10 in total

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