Comparison of Predictability of Future Cardiovascular Events Between Chronic Kidney Disease (CKD) Stage Based on CKD Epidemiology Collaboration Equation and That Based on Modification of Diet in Renal Disease Equation in the Japanese General Population
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- Ohsawa Masaki
- Department of Hygiene and Preventive Medicine, Iwate Medical University
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- Tanno Kozo
- Department of Hygiene and Preventive Medicine, Iwate Medical University
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- Itai Kazuyoshi
- The First Institute of Health Service, Japan Anti-Tuberculosis Association
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- Turin Tanvir Chowdhury
- Department of Medicine, University of Calgary
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- Okamura Tomonori
- Department of Preventive Medicine and Public Health, Keio University
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- Ogawa Akira
- Department of Neurosurgery, Iwate Medical University
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- Ogasawara Kuniaki
- Department of Neurosurgery, Iwate Medical University
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- Fujioka Tomoaki
- Department of Urology, Iwate Medical University
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- Onoda Toshiyuki
- Department of Hygiene and Preventive Medicine, Iwate Medical University
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- Yoshida Yuki
- Department of Neurosurgery, Iwate Medical University
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- Omama Shin-ichi
- Department of Neurosurgery, Iwate Medical University
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- Ishibashi Yasuhiro
- Department of Internal Medicine, Iwate Medical University
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- Nakamura Motoyuki
- Department of Internal Medicine, Iwate Medical University
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- Makita Shinji
- Department of Internal Medicine, Iwate Medical University
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- Tanaka Fumitaka
- Department of Internal Medicine, Iwate Medical University
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- Kuribayashi Toru
- Department of Health and Physical Education, Faculty of Education, Iwate University
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- Koyama Tomiko
- Iwate Health Service Association
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- Sakata Kiyomi
- Department of Hygiene and Preventive Medicine, Iwate Medical University
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- Okayama Akira
- The First Institute of Health Service, Japan Anti-Tuberculosis Association
書誌事項
- タイトル別名
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- – Iwate KENCO Study –
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説明
Background: Whether estimated glomerular filtration rate (eGFR) calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) Study equation (eGFRCKDEPI) improves risk prediction compared to that calculated using the Modification of Diet in Renal Disease (MDRD) study equation (eGFRMDRD) has not been examined in a prospective study in Japanese people. Methods and Results: Participants (n=24,560) were divided into 4 stages (1, ≥90; 2, 60–89 (reference); 3a, 45–59; 3b+ <45ml·min–1·1.73m–2) according to eGFRCKDEPI or eGFRMDRD. Endpoints were all-cause death, myocardial infarction (MI) and stroke. Area under the receiver operating characteristic curves (95% confidence intervals) for predicting all-cause death, MI and stroke by eGFRCKDEPI vs. eGFRMDRD were 0.680 (0.662–0.697) vs. 0.582 (0.562–0.602); 0.718 (0.665–0.771) vs. 0.642 (0.581–0.703); and 0.656 (0.636–0.676) vs. 0.576 (0.553–0.599), respectively. Multivariate-adjusted Cox regression and Poisson regression analysis results were similar for adjusted incidence rates and adjusted hazard ratios in each corresponding stage between the 2 models and no differences were found in model assessment parameters. Net reclassification improvement (NRI) for predicting all-cause death, MI and stroke were estimated to be 6.7% (P<0.001), –1.89% (P=0.029) and –0.20% (P=0.421), respectively. Conclusions: Better discrimination was achieved using eGFRCKDEPI than eGFRMDRD on univariate analysis. NRI analysis indicated that the use of eGFRCKDEPI instead of eGFRMDRD offered a significant improvement in reclassification of death risk. (Circ J 2013; 77: 1315–1325)<br>
収録刊行物
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- Circulation Journal
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Circulation Journal 77 (5), 1315-1325, 2013
一般社団法人 日本循環器学会
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詳細情報 詳細情報について
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- CRID
- 1390001205105504000
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- NII論文ID
- 10031151396
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- NII書誌ID
- AA11591968
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- COI
- 1:STN:280:DC%2BC3svgt1Wjsw%3D%3D
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- ISSN
- 13474820
- 13469843
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- PubMed
- 23428718
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- Crossref
- PubMed
- CiNii Articles
- KAKEN
- OpenAIRE
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- 抄録ライセンスフラグ
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