Literature DB >> 23449266

Development of a point-based prediction model for the incidence of total stroke: Japan public health center study.

Hiroshi Yatsuya1, Hiroyasu Iso, Kazumasa Yamagishi, Yoshihiro Kokubo, Isao Saito, Kazuo Suzuki, Norie Sawada, Manami Inoue, Shoichiro Tsugane.   

Abstract

BACKGROUND AND
PURPOSE: An individualized risk score for the development of stroke may be a useful tool to motivate patients to modify their risk behaviors. We developed and validated a point-based prediction model (risk score) for stroke incidence using a Japanese cohort of general men and women.
METHODS: The Japan Public Health Center-based prospective study cohort II (age range, 40-69 years at baseline in 1993-1994; n=15 672) was used to derive the point-based model according to Cox regression results. The model was externally validated using the Japan Public Health Center study cohort I and also by bootstrap methods within cohort II. The model discrimination was evaluated by the area under the receiver operating characteristic curve, model calibration, by the Grønnesby-Borgan χ(2) statistic. Vascular age was also calculated.
RESULTS: During 14 years of follow-up, 790 incident stroke cases occurred. Variables selected for the model were age, sex, current smoking, body mass index, blood pressure, antihypertensive medication use, and diabetes mellitus. Interactions of sex with current smoking and of antihypertensive medication use with systolic blood pressure were statistically significant. The point-based model discriminated reasonably well (area under the receiver operating characteristic curve, 0.73). The area under the receiver operating characteristic curve of the point-based model applied externally to cohort I was reasonably good: 0.69. A 50-year-old man with diabetes mellitus and hypertension has an estimated vascular age of 69 years. High normal blood pressure and grade 1 hypertension accounted for one third of the stroke incidence.
CONCLUSIONS: We developed score to predict 10-year stroke risk using variables that are easily available in the community setting.

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Year:  2013        PMID: 23449266     DOI: 10.1161/STROKEAHA.111.677534

Source DB:  PubMed          Journal:  Stroke        ISSN: 0039-2499            Impact factor:   7.914


  13 in total

Review 1.  A systematic review of the status and methodological considerations for estimating risk of first ever stroke in the general population.

Authors:  Wei Xu; Jiuyi Huang; Qingsong Yu; Hongfan Yu; Yang Pu; Qiuling Shi
Journal:  Neurol Sci       Date:  2021-03-30       Impact factor: 3.307

2.  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

Review 3.  The Lifelong Health Support 10: a Japanese prescription for a long and healthy life.

Authors:  Ahmed Arafa; Yoshihiro Kokubo; Rena Kashima; Masayuki Teramoto; Yukie Sakai; Saya Nosaka; Youko M Nakao; Emi Watanabe
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4.  Factors associated with stroke among patients with type 2 diabetes mellitus in China: a propensity score matched study.

Authors:  Chenlu He; Wei Wang; Qian Chen; Ziyuan Shen; Enchun Pan; Zhongming Sun; Peian Lou; Xunbao Zhang
Journal:  Acta Diabetol       Date:  2021-06-14       Impact factor: 4.280

5.  The impact of acute kidney injury on the long-term risk of stroke.

Authors:  Vin-Cent Wu; Pei-Chen Wu; Che-Hsiung Wu; Tao-Min Huang; Chia-Hsuin Chang; Pi-Ru Tsai; Wen-Je Ko; Likwang Chen; Cheng-Yi Wang; Tzong-Shinn Chu; Kwan-Dun Wu
Journal:  J Am Heart Assoc       Date:  2014-07-15       Impact factor: 5.501

Review 6.  C-reactive protein and cardiovascular disease in East asians: a systematic review.

Authors:  Isao Saito; Koutatsu Maruyama; Eri Eguchi
Journal:  Clin Med Insights Cardiol       Date:  2015-02-03

7.  Risk Factor of Cardiovascular Disease Among Older Individuals.

Authors:  Hiroshi Yatsuya; Masaaki Matsunaga; Yuanying Li; Atsuhiko Ota
Journal:  J Atheroscler Thromb       Date:  2016-10-26       Impact factor: 4.928

8.  A Model for Risk Prediction of Cerebrovascular Disease Prevalence-Based on Community Residents Aged 40 and above in a City in China.

Authors:  Qin Zhu; Die Luo; Xiaojun Zhou; Xianxu Cai; Qi Li; Yuanan Lu; Jiayan Chen
Journal:  Int J Environ Res Public Health       Date:  2021-06-18       Impact factor: 3.390

9.  Dynamic prediction model and risk assessment chart for cardiovascular disease based on on-treatment blood pressure and baseline risk factors.

Authors:  Satoshi Teramukai; Yasuyuki Okuda; Shigeru Miyazaki; Ryuzo Kawamori; Masayuki Shirayama; Tamio Teramoto
Journal:  Hypertens Res       Date:  2015-11-26       Impact factor: 3.872

10.  Synthesis of clinical prediction models under different sets of covariates with one individual patient data.

Authors:  Daisuke Yoneoka; Masayuki Henmi; Norie Sawada; Manami Inoue
Journal:  BMC Med Res Methodol       Date:  2015-11-19       Impact factor: 4.615

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