Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Más filtros












Base de datos
Intervalo de año de publicación
1.
Chin Med J (Engl) ; 132(12): 1406-1413, 2019 Jun 20.
Artículo en Inglés | MEDLINE | ID: mdl-31205097

RESUMEN

BACKGROUND: The long-term predicted value of microvolt T-wave alternans (MTWA) for ventricular tachyarrhythmia in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC) remains unclear. Our study explored the characteristics of MTWA and its prognostic value when combined with an electrophysiologic study (EPS) in patients with ARVC. METHODS: All patients underwent non-invasive MTWA examination with modified moving average (MMA) analysis and an EPS. A positive event was defined as the first occurrence of sudden cardiac death, documented sustained ventricular tachycardia (VT), ventricular fibrillation, or the administration of appropriate implantable cardioverter defibrillator therapy including shock or anti-tachycardia pacing. RESULTS: Thirty-five patients with ARVC (age 38.6 ±â€Š11.0 years; 28 males) with preserved left ventricular (LV) function were recruited. The maximal TWA value (MaxValt) was 17.0 (11.0-27.0) µV. Sustained VT was induced in 22 patients by the EPS. During a median follow-up of 99.9 ±â€Š7.7 months, 15 patients had positive clinical events. When inducible VT was combined with the MaxValt, the area under the curve improved from 0.739 to 0.797. The receiver operating characteristic curve showed that a MaxValt of 23.5 µV was the optimal cutoff value to identify positive events. The multivariate Cox regression model for survival showed that MTWA (MaxValt, hazard ratio [HR], 1.06; 95% confidence interval [CI], 1.01-1.11; P = 0.01) and inducible VT (HR, 5.98; 95% CI, 1.33-26.8; P = 0.01) independently predicted positive events in patients with ARVC. CONCLUSIONS: MTWA assessment with MMA analysis complemented by an EPS might provide improved prognostic ability in patients with ARVC with preserved LV function during long-term follow-up.


Asunto(s)
Arritmias Cardíacas/diagnóstico , Displasia Ventricular Derecha Arritmogénica/diagnóstico , Electrocardiografía/métodos , Electrofisiología/métodos , Taquicardia Ventricular/diagnóstico , Adulto , Prueba de Esfuerzo , Femenino , Estudios de Seguimiento , Humanos , Masculino , Persona de Mediana Edad , Función Ventricular Izquierda/fisiología
2.
Stud Health Technol Inform ; 160(Pt 2): 856-60, 2010.
Artículo en Inglés | MEDLINE | ID: mdl-20841807

RESUMEN

Classification is an important medical decision support function that can be seriously affected by disproportionate class distribution in the training data. In medical decision making, the rate of misclassification and the cost of misclassifying a minority (positive) class as a majority (negative) class are especially high. In this paper, we propose a new model-driven sampling approach to balancing data samples. Most existing data sampling methods produce new data points based on local, deterministic information. Our approach extends the idea of generative sampling to produce new data points based on an induced probabilistic graphical model. We present the motivation and the design of the proposed algorithm, and compare it with two representative imbalanced data sampling approaches on four medical data sets varying in size, imbalance ratio, and dimension. The empirical study helped identify the challenges in imbalanced data problems in medicine, and highlighted the strengths and limitations of the relevant sampling approaches. Performance of the model driven approach is shown to be comparable with existing approaches; potential improvements could be achieved by incorporating domain knowledge.


Asunto(s)
Toma de Decisiones Asistida por Computador , Algoritmos , Bases de Datos Factuales , Humanos , Modelos Estadísticos , Reconocimiento de Normas Patrones Automatizadas
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA
...