Relationship between resting 12-lead electrocardiogram and all-cause death in patients without structural heart disease: Shinken Database analysis.
Action Potentials
Adult
Aged
Aged, 80 and over
Databases, Factual
Electrocardiography
Female
Heart Conduction System
/ physiopathology
Heart Diseases
/ diagnosis
Heart Rate
Humans
Incidence
Male
Middle Aged
Predictive Value of Tests
Prognosis
Risk Assessment
Risk Factors
Signal Processing, Computer-Assisted
Support Vector Machine
Time Factors
Tokyo
/ epidemiology
Death
Electrocardiogram
Mortality
Prediction
Journal
BMC cardiovascular disorders
ISSN: 1471-2261
Titre abrégé: BMC Cardiovasc Disord
Pays: England
ID NLM: 100968539
Informations de publication
Date de publication:
10 02 2021
10 02 2021
Historique:
received:
12
08
2020
accepted:
11
01
2021
entrez:
11
2
2021
pubmed:
12
2
2021
medline:
5
10
2021
Statut:
epublish
Résumé
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. 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. 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. 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.
Sections du résumé
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.
Identifiants
pubmed: 33568066
doi: 10.1186/s12872-021-01864-3
pii: 10.1186/s12872-021-01864-3
pmc: PMC7874456
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
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