Literature DB >> 23918839

Cumulative impact of axial, structural, and repolarization ECG findings on long-term cardiovascular mortality among healthy individuals in Japan: National Integrated Project for Prospective Observation of Non-Communicable Disease and its Trends in the Aged, 1980 and 1990.

Taku Inohara1, Shun Kohsaka2, Tomonori Okamura1, Makoto Watanabe3, Yasuyuki Nakamura4, Aya Higashiyama5, Aya Kadota6, Nagako Okuda7, Yoshitaka Murakami8, Takayoshi Ohkubo9, Katsuyuki Miura8, Akira Okayama10, Hirotsugu Ueshima8.   

Abstract

AIMS: Various cohort studies have shown a close association between long-term cardiovascular disease (CVD) outcomes and individual electrocardiographic (ECG) abnormalities such as axial, structural, and repolarization changes. The combined effect of these ECG abnormalities, each assumed to be benign, has not been thoroughly investigated. METHODS AND
RESULTS: Community-dwelling Japanese residents from the National Integrated Project for Perspective Observation of Non-Communicable Disease and its Trends in the Aged, 1980-2004 and 1990-2005 (NIPPON DATA80 and 90), were included in this study. Baseline ECG findings were classified using the Minnesota Code and categorized into axial (left axis deviation, clockwise rotation), structural (left ventricular hypertrophy, atrial enlargement), and repolarization (minor and major ST-T changes) abnormalities. The hazard ratios of the cumulative impacts of ECG findings on long-term CVD death were estimated by stratified Cox proportional hazard models, including adjustments for cohort strata. In all, 16,816 participants were evaluated. The average age was 51.2 ± 13.5 years; 42.7% participants were male. The duration of follow up was 300,924 person-years (mean 17.9 ± 5.8 years); there were 1218 CVD deaths during that time. Overall, 4203 participants (25.0%) had one or more categorical ECG abnormalities: 3648 (21.7%) had a single abnormality, and 555 (3.3%) had two or more. The risk of CVD mortality increased as the number of abnormalities accumulated (single abnormality HR 1.29, 95% CI 1.13-1.48; ≥2 abnormalities HR 2.10, 95% CI 1.73-2.53).
CONCLUSIONS: Individual ECG abnormalities had an additive effect in predicting CVD outcome risk in our large-scale cohort study. © The European Society of Cardiology 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Entities:  

Keywords:  Cardiovascular outcomes; NIPPON DATA80; NIPPON DATA90; cohort study; electrocardiography

Mesh:

Year:  2013        PMID: 23918839     DOI: 10.1177/2047487313500568

Source DB:  PubMed          Journal:  Eur J Prev Cardiol        ISSN: 2047-4873            Impact factor:   7.804


  7 in total

1.  Clinical predictors of all-cause mortality in patients presenting to specialist heart failure clinic with raised NT-proBNP and no heart failure.

Authors:  Pankaj Garg; Steven Wood; Andrew J Swift; Graham Fent; Nigel Lewis; Dominic Rogers; Alexander Rothman; Athanasios Charalampopoulos; Abdallah Al-Mohammad
Journal:  ESC Heart Fail       Date:  2020-06-04

2.  Electrocardiographic ST-T Abnormities Are Associated With Stroke Risk in the REGARDS Study.

Authors:  Mitsuaki Sawano; Ya Yuan; Shun Kohsaka; Taku Inohara; Takeki Suzuki; Tomonori Okamura; George Howard; Virginia J Howard; Suzanne Judd; Elsayed Z Soliman; Mary Cushman
Journal:  Stroke       Date:  2020-03-04       Impact factor: 7.914

3.  Usefulness of Maintaining a Normal Electrocardiogram Over Time for Predicting Cardiovascular Health.

Authors:  Elsayed Z Soliman; Zhu-Ming Zhang; Lin Y Chen; Larisa G Tereshchenko; Dan Arking; Alvaro Alonso
Journal:  Am J Cardiol       Date:  2016-10-08       Impact factor: 2.778

4.  Abnormal electrocardiographic QRS transition zone and risk of mortality in individuals free of cardiovascular disease.

Authors:  Natalie Bradford; Amit J Shah; Andrew Usoro; Wesley K Haisty; Elsayed Z Soliman
Journal:  Europace       Date:  2014-06-17       Impact factor: 5.214

5.  Independent Prognostic Value of Single and Multiple Non-Specific 12-Lead Electrocardiographic Findings for Long-Term Cardiovascular Outcomes: A Prospective Cohort Study.

Authors:  Mitsuaki Sawano; Shun Kohsaka; Tomonori Okamura; Taku Inohara; Daisuke Sugiyama; Yasuyuki Shiraishi; Makoto Watanabe; Yasuyuki Nakamura; Aya Higashiyama; Aya Kadota; Nagako Okuda; Yoshitaka Murakami; Takayoshi Ohkubo; Akira Fujiyoshi; Katsuyuki Miura; Akira Okayama; Hirotsugu Ueshima
Journal:  PLoS One       Date:  2016-06-30       Impact factor: 3.240

6.  Progression of Electrocardiographic Abnormalities in Type 1 Diabetes During 16 Years of Follow-up: The Epidemiology of Diabetes Interventions and Complications (EDIC) Study.

Authors:  Elsayed Z Soliman; Jye-Yu C Backlund; Ionut Bebu; Yabing Li; Zhu-Ming Zhang; Patricia A Cleary; John M Lachin
Journal:  J Am Heart Assoc       Date:  2016-03-14       Impact factor: 5.501

7.  Influence of Optimization Design Based on Artificial Intelligence and Internet of Things on the Electrocardiogram Monitoring System.

Authors:  Ming Yin; Ru Tang; Miao Liu; Ke Han; Xiao Lv; Maolin Huang; Ping Xu; Yongdeng Hu; Baobao Ma; Yanrong Gai
Journal:  J Healthc Eng       Date:  2020-10-26       Impact factor: 2.682

  7 in total

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