| Autor: |
Naomi Hirota, Shinya Suzuki, Takuto Arita, Naoharu Yagi, Takayuki Otsuka, Mikio Kishi, Hiroaki Semba, Hiroto Kano, Shunsuke Matsuno, Yuko Kato, Tokuhisa Uejima, Yuji Oikawa, Minoru Matsuhama, Mitsuru Iida, Tatsuya Inoue, Junji Yajima, Takeshi Yamashita |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
BMC Cardiovascular Disorders, Vol 21, Iss 1, Pp 1-8 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
1471-2261 |
| DOI: |
10.1186/s12872-021-01864-3 |
| Popis: |
Abstract Background Resting 12-lead electrocardiography is widely used for the detection of cardiac diseases. Electrocardiogram readings have been reported to be affected by aging and, therefore, can predict patient mortality. Methods A total of 12,837 patients without structural heart disease who underwent electrocardiography at baseline were identified in the Shinken Database among those registered between 2010 and 2017 (n = 19,170). Using 438 electrocardiography parameters, predictive models for all-cause death and cardiovascular (CV) death were developed by a support vector machine (SVM) algorithm. Results During the observation period of 320.4 days, 55 all-cause deaths and 23 CV deaths were observed. In the SVM prediction model, the mean c-statistics of 10 cross-validation models with training and testing datasets were 0.881 ± 0.027 and 0.927 ± 0.101, respectively, for all-cause death and 0.862 ± 0.029 and 0.897 ± 0.069, respectively for CV death. For both all-cause and CV death, high values of permutation importance in the ECG parameters were concentrated in the QRS complex and ST-T segment. Conclusions Parameters acquired from 12-lead resting electrocardiography could be applied to predict the all-cause and CV deaths of patients without structural heart disease. The ECG parameters that greatly contributed to the prediction were concentrated in the QRS complex and ST-T segment. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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