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Introduction
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
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An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
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The electrical signals recorded on an electrocardiogram (ECG) occur before the mechanical processes of contraction and relaxation during the cardiac cycle.
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Evaluation of Left Ventricular Structure and Function using 3D Echocardiography
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Anomalías acumulativas en el electrocardiograma predicen la reducción de la fracción de eyección del ventrículo

Solomon Kim1, Beshoy Saad1, Gary Chu2

  • 1California Northstate University College of Medicine, Elk Grove, CA, USA.

Journal of electrocardiology
|January 9, 2026
PubMed
Resumen
Este resumen es generado por máquina.

La combinación de parámetros continuos de electrocardiograma (ECG), como la duración del QRS y el intervalo QT (QTc), mejora la predicción de la reducción de la fracción de eyección del ventrículo izquierdo (FEVI) en comparación con medidas únicas. Sin embargo, los datos faltantes pueden subestimar el poder predictivo real de estos marcadores de ECG.

Palabras clave:
Pruebas diagnósticasFracción de eyecciónElectrocardiogramaModelado predictivoDuración del QRSEvaluación de riesgosDisfunción sistólica

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Área de la Ciencia:

  • Cardiología
  • Informática médica
  • Bioestadística

Sus antecedentes:

  • Las anomalías electrocardiográficas (ECG) individuales están relacionadas con la reducción de la fracción de eyección del ventrículo izquierdo (FEVI).
  • El valor predictivo sinérgico de múltiples parámetros continuos de ECG frente a parámetros únicos o puntuación binaria para la FEVI no se comprende completamente.

Objetivo del estudio:

  • Evaluar el valor predictivo de los parámetros continuos combinados de ECG (duración del QRS, intervalo PR, intervalo QT corregido por frecuencia cardíaca - QTc) para la LVEF reducida.
  • Comparar el rendimiento predictivo de un modelo de ECG continuo multiparamétrico frente a parámetros de ECG individuales y métodos de puntuación binaria.

Principales métodos:

  • Análisis de 89.630 estudios pareados de ECG-ecocardiograma de la base de datos EchoNext.
  • Desarrollo y evaluación de siete modelos de regresión logística utilizando conjuntos de entrenamiento (70%) y validación (30%), ajustados por edad y sexo.
  • Los modelos se evaluaron utilizando intervalos de confianza de bootstrap y validación cruzada estratificada de 5 veces, con evaluación sistemática de los patrones de datos faltantes.

Principales resultados:

  • El modelo completo de ECG continuo mostró una discriminación aceptable (AUC 0,710) en comparación con el QTc solo (AUC 0,695).
  • El QTc tuvo la asociación individual más fuerte (AUC 0,695), seguido de la duración del QRS (AUC 0,673) y el intervalo PR (AUC 0,603).
  • La prevalencia de LVEF ≤45% aumentó significativamente con el número de anomalías en el ECG (p < 0,001).

Conclusiones:

  • Los parámetros continuos combinados de ECG ofrecen un valor predictivo mejorado para la LVEF reducida en comparación con parámetros individuales o clasificaciones binarias.
  • El sesgo de selección significativo debido a datos faltantes no aleatorios sugiere que las asociaciones observadas probablemente subestiman el poder predictivo real.