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Una estrategia guiada por inteligencia artificial para reducir la mala preparación intestinal: un estudio

Antonio Z Gimeno-García1,2, Federica Benítez-Zafra1, Ignacio Redondo-Zaera3

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Una nueva aplicación de software que utiliza inteligencia artificial mejoró significativamente la calidad de la limpieza del colon para colonoscopias. Este enfoque impulsado por IA mejora la preparación intestinal, lo que conduce a mejores resultados en procedimientos ambulatorios.

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Área de la Ciencia:

  • Gastroenterología y Endoscopia; Inteligencia Artificial en Medicina; Análisis de Imágenes Médicas

Sus antecedentes:

  • La preparación intestinal de alta calidad es esencial para la detección precisa de adenomas durante las colonoscopias.; Los métodos estándar actuales para la evaluación de la preparación intestinal pueden ser subjetivos e inconsistentes.; Se necesitan soluciones tecnológicas novedosas para mejorar objetivamente la calidad de la limpieza del colon.

Objetivo del estudio:

  • Evaluar la eficacia de una aplicación de software que utiliza una red neuronal convolucional (CNN) para mejorar la calidad de la limpieza del colon.; Comparar un enfoque de preparación intestinal impulsado por software con la atención estándar en un ensayo controlado aleatorizado multicéntrico.; Evaluar si la retroalimentación basada en IA sobre imágenes de efluentes rectales mejora la preparación de la colonoscopia.

Principales métodos:

  • Un ensayo controlado aleatorizado multicéntrico que involucró a 774 pacientes.; Los pacientes fueron asignados al grupo de atención estándar o al grupo de intervención que utilizaba una aplicación web con retroalimentación basada en CNN.; El grupo de intervención envió imágenes de efluentes rectales para análisis de CNN y recibió orientación sobre la adecuación de la preparación.

Principales resultados:

  • El grupo de intervención mostró mejoras estadísticamente significativas en la calidad general de la limpieza del colon (91 % frente al 84,2 %, P = 0,005).; Se observó una limpieza superior tanto en los segmentos del colon derecho como del izquierdo para el grupo de intervención.; El análisis por protocolo confirmó una preparación intestinal significativamente mejor en el grupo de intervención, incluso para lograr una preparación excelente (BBPS >7).

Conclusiones:

  • Una aplicación de software que utiliza el análisis de CNN de imágenes de efluentes rectales mejora significativamente la calidad de la limpieza del colon en pacientes ambulatorios.; Este enfoque impulsado por IA ofrece una herramienta prometedora para optimizar la preparación intestinal antes de las colonoscopias.; El estudio demuestra la utilidad clínica de integrar la IA en los protocolos de preparación guiados por el paciente.