Automatic SVM classification of sudden cardiac death and pump failure death from autonomic and repolarization ECG markers

Ramírez, Julia; Monasterio, Violeta; Mincholé, Ana; Llamedo, Mariano; Lenis, Gustavo; Cygankiewicz, Iwona; Luna, Antonio; Malik, Marek; Martínez, Juan Pablo; Laguna, Pablo; Pueyo, Esther

doi:10.1016/j.jelectrocard.2015.04.002

Cited by 34 publications

(30 citation statements)

References 15 publications

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“…[38][39][40][41] Overall, a total of 25 and 20 cohorts of patients were included in the qualitative and quantitative analysis, respectively. Despite they met eligibility criteria, 5 studies 27,28,30,36,37 were not included in the meta-analysis because of heterogeneity in data presentation (raw data were not available nor derivable). The end points varied in the different cohorts, including TM and CD and AE (Table 1).…”

Section: What the Study Addsmentioning

confidence: 99%

“…Four cohorts (all with EF>30%) analyzed post-AMI patients [25][26][27][28] and 1 HF patients. 37 Data were not meta-analyzed because of heterogeneities in data reporting and statistical analysis. In all 5 cohorts and for both CD and AE end points, the RRs/HRs (Table 4) displayed a consistent increase when the TWA marker was added to HRT (in post-AMI patients the RRs/HRs increased by a factor ranging from 1.4-4.9).…”

Section: Predictive Power Of Hrt In Combination With Other Arrhythmicmentioning

confidence: 99%

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Heart Rate Turbulence Is a Powerful Predictor of Cardiac Death and Ventricular Arrhythmias in Postmyocardial Infarction and Heart Failure Patients

Disertori

Masè

Rigoni

et al. 2016

Circ: Arrhythmia and Electrophysiology

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Background-Heart rate turbulence (HRT) has been proposed as a candidate marker of altered autonomic tone, and some studies showed its prognostic value for both cardiac death (CD) and sudden death. Nevertheless, HRT is not currently used in the clinical practice. Methods and Results-We performed a systematic review and meta-analysis of the predictive value of HRT for the end points of total mortality, CD, and fatal and nonfatal ventricular arrhythmias in postacute myocardial infarction and heart failure patients. MEDLINE and The Cochrane Library databases were systematically searched to identify studies, which analyzed the predictive value of abnormal HRT for the defined end points. Twenty studies (25 cohorts: 12 832 patients) were identified by the systematic review, and 15 studies (20 cohorts: 11 499 patients) were included in the meta-analyses. Abnormal HRT was a predictive marker for all the end points in heart failure patients and more markedly in postacute myocardial infarction patients, where 9 out of the 10 cohorts had an ejection fraction >30%. In postacute myocardial infarction patients, HRT had pooled risk ratios of 3.53 (95% confidence interval [CI], 2.54-4.90), 4.82 (95% CI, 3.12-7.45), and 4.48 (95% CI, 3.04-6.60), and positive likelihood ratios of 3.5 (95% CI, 2.6-4.8), 4.1 (95% CI, 3.0-5.7), and 2.7 (95% CI, 2.2-3.3) for total mortality, CD, and arrhythmic events, respectively. The combination of abnormal HRT and T-wave alternans (5 cohorts: 1516 patients) increased the predictive power for CD and arrhythmic events. Conclusions-HRT is a powerful predictor of both CD and arrhythmic events, particularly in postacute myocardial infarction patients with ejection fraction >30%. HRT power increases in combination with T-wave alternans analysis.(Circ Arrhythm Electrophysiol. 2016;9:e004610.

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Section: What the Study Addsmentioning

confidence: 99%

Section: Predictive Power Of Hrt In Combination With Other Arrhythmicmentioning

confidence: 99%

Heart Rate Turbulence Is a Powerful Predictor of Cardiac Death and Ventricular Arrhythmias in Postmyocardial Infarction and Heart Failure Patients

Disertori

Masè

Rigoni

et al. 2016

Circ: Arrhythmia and Electrophysiology

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“…The value of the index Δα for risk stratification has been explored in different populations, as in patients who developed TdP after sotalol administration [121], in patients with hypertrophic cardiomyopathy [122] and in patients with heart failure [123], where the prognostic value of Δα could be corroborated in retrospective studies, and with the provided information being complementary to that obtained from other repolarization or autonomic indices measuring TWA (IAA parameter) or heart rate turbulence (HRT).…”

Section: Ecgs and δαmentioning

confidence: 99%

“…Taking into account the different etiology and complexity of factors involved in SCD, it is also important to consider the combination of different markers that have been proved to be associated with risk separately (possibly including also chemical and genetic biomarkers). While some single non-invasive indices may have in their own modest incremental value, combining indices quantifying different physiological phenomena may provide more robust prediction or help to discriminate between different types of negative outcomes [123]. In the same manner as standardized databases have helped in the development, validation and comparison of computerized methods in electrocardiography, the establishment of baseline risk models for common patient groups (including the general population) [133] and the availability of ECG and clinical data from well-designed riskstratification-based trials would lead to more focused efforts in risk stratification, accelerating the way to clinical impact.…”

Section: Challenges and Future Perspectivesmentioning

confidence: 99%

Techniques for Ventricular Repolarization Instability Assessment From the ECG

2016

Self Cite

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Abstract-Instabilities in ventricular repolarization have been documented to be tightly linked to arrhythmia vulnerability. Translation of the information contained in the repolarization phase of the ECG into valuable clinical decision-making tools remains challenging. This work aims at providing an overview of the last advances in the proposal and quantification of ECG-derived indices that describe repolarization properties and whose alterations are related with threatening arrhythmogenic conditions. A review of the state-of-the-art is provided, spanning from the electrophysiological basis of ventricular repolarization to its characterization on the surface ECG through a set of temporal and spatial risk markers.Index Terms-Electrophysiological basis of the ECG, ECG waves, ECG intervals, repolarization instabilities, spatial and temporal ventricular repolarization dispersion, cardiac arrhythmias, biophysical modeling of the ECG, ECG signal processing, repolarization risk markers, T wave alternans, QT variability.

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“…The prediction of re-hospitalizations [9][10][11][12][13][14][15] and mortality [11], [16][17][18][19][20][21][22][23] has gained the interest of researchers who developed prediction models exploiting different categories of information (e.g. sociodemographic, clinical examination, medical condition, lab tests, medication intake, phenotypic data, sensor data) along with machine learning techniques.…”

Section: Introductionmentioning

confidence: 99%

Predicting Heart Failure Patient Events by Exploiting Saliva and Breath Biomarkers Information

Tripoliti

Karanasiou

Kalatzis

et al. 2017

2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)

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Abstract-The aim of this work is to present a machine learning based method for the prediction of adverse events (mortality and relapses) in patients with heart failure (HF) by exploiting, for the first time, measurements of breath and saliva biomarkers (Tumor Necrosis Factor Alpha, Cortisol and Acetone). Data from 27 patients are used in the study and the prediction of adverse events is achieved with high accuracy (77%) using the Rotation Forest algorithm. As in the near future, biomarkers can be measured at home, together with other physiological data, the accurate prediction of adverse events on the basis of home based measurements can revolutionize HF management.

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Automatic SVM classification of sudden cardiac death and pump failure death from autonomic and repolarization ECG markers

Cited by 34 publications

References 15 publications

Heart Rate Turbulence Is a Powerful Predictor of Cardiac Death and Ventricular Arrhythmias in Postmyocardial Infarction and Heart Failure Patients

Heart Rate Turbulence Is a Powerful Predictor of Cardiac Death and Ventricular Arrhythmias in Postmyocardial Infarction and Heart Failure Patients

Techniques for Ventricular Repolarization Instability Assessment From the ECG

Predicting Heart Failure Patient Events by Exploiting Saliva and Breath Biomarkers Information

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