Abstract
Brugada syndrome (BS) is an inherited cardiopathy that predisposes individuals without structural heart disease to sudden cardiac death. The diagnosis is performed by detecting a typical pattern in the electrocardiogram (ECG), called Type 1 Brugada pattern, but this is not always visible, so the diagnosis is not straightforward. In this study, we investigated other ECG markers, independent of the typical pattern, which exhibited a good ability to differentiate the carriers and the non-carriers of the genetic mutation responsible for this disease. The combination of these markers through linear models has led to enhancing the ability of each marker to discriminate between the two groups. We found linear combinations of these markers for which the area under the ROC curve (AUC) was greater than 0.9, which suggests an excellent ability to discriminate between the two groups. This study points towards good alternatives for diagnosing BS which may prevent searching for the Type 1 Brugada pattern in an ECG, but these alternatives should be investigated with a larger database in order to produce a good effective predictive model.
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Henriques, C., Matos, A.C., Santos, L.F.d. (2014). Brugada Syndrome Diagnosis: Three Approaches to Combining Diagnostic Markers. In: Pacheco, A., Santos, R., Oliveira, M., Paulino, C. (eds) New Advances in Statistical Modeling and Applications. Studies in Theoretical and Applied Statistics(). Springer, Cham. https://doi.org/10.1007/978-3-319-05323-3_20
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DOI: https://doi.org/10.1007/978-3-319-05323-3_20
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