Abstract
Early detection of sudden cardiac arrest (SCA) is critical to prevent serious repercussion such as irreversible neurological damage and death. Currently, the most effective method involves analyzing electrocardiogram (ECG) features obtained during ventricular fibrillation. In this study, data from 10 normal patients and 10 SCA patients obtained from Physiobank were used to statistically compare features, such as heart rate, R-R interval duration, and heart rate variability (HRV) features from which the HRV features were then selected for classification via linear discriminant analysis (LDA) and linear and fine Gaussian support vector machines (SVM) in order to determine the ideal time-frame in which SCA can be accurately detected. The best accuracy was obtained at 2 and 8 min prior to SCA onset across all three classifiers. However, accuracy rates of 75–80% were also obtained at time-frames as early as 50 and 40 min prior to SCA onset. These results are clinically important in the field of SCA, as early detection improves overall patient survival.
Highlights
Sudden cardiac arrest (SCA) is the sudden unexpected loss of heart function less than 1 h from the onset of symptoms [1,2]
Compared to the normal patients, sudden cardiac arrest (SCA) patients exhibited a higher mean resting heart rate, with an 18.7 ± 3.5 bpm difference observed between the two cohorts (See Table A1, Appendix A)
Post-hoc analyses using Tukey Honestly Significant Difference (Tukey honest significant difference (HSD)) indicated that there was a significant difference in mean resting heart rate observed between both patient cohorts at 3 h prior to SCA (p = 0.04), but found no significant difference in mean resting heart rate observed between the two patient cohorts at 6 min prior to SCA onset (p = 0.06) (See Table A4, Appendix B)
Summary
Sudden cardiac arrest (SCA) is the sudden unexpected loss of heart function less than 1 h from the onset of symptoms [1,2]. SCA can occur at any age in a patient with or without a detectable heart disease [4]. 15,000 Australians per year experience SCA and only 6–13% of patients survive more than one year after the event [5]. SCA is one of the major causes of cardiovascular mortality and is a major public health issue both nationally and globally, with the annual cost of SCA amounting to approximately. $33 billion USD [6]. This economic and health burden of SCA poses to society can be reduced with the improvement of patient outcomes through better detection systems [7]
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