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Software de inteligencia artificial para apoyar la decisión de transferencia de trombólisis mecánica en centros
Marcin Wiącek1,2, Katarzyna Koszarska3, Aleksandra Kotlińska3
1Department of Neurology, Faculty of Medicine, University of Rzeszow, Poland. mawiacek@ur.edu.pl.
Neurologia i neurochirurgia polska
|January 22, 2026
Resumen
El software de inteligencia artificial (IA) mejoró las decisiones de transferencia para la trombólisis mecánica (TM) de pacientes con ictus isquémico agudo (EIA) de centros primarios (CP). La IA mejoró la eficiencia y la precisión, lo que podría reducir los retrasos en la atención del ictus, que requiere mucho tiempo.
Área de la Ciencia:
- Neurología
- Imágenes médicas
- Inteligencia artificial
Sus antecedentes:
- Los centros primarios de ictus (CP) a menudo carecen de imágenes avanzadas y experiencia para las decisiones de trombólisis mecánica (TM) en el ictus isquémico agudo (EIA).
- Los sistemas eficientes de transferencia interhospitalaria son cruciales para los pacientes elegibles para TM tratados inicialmente en CP.
- Existen datos limitados sobre el rendimiento de las herramientas de IA en entornos de CP de bajo volumen.
Objetivo del estudio:
- Evaluar el beneficio del software de obtención de imágenes basado en IA para apoyar las decisiones de transferencia de TM para pacientes con EIA de CP de bajo volumen.
- Evaluar el impacto de la IA en la eficiencia del flujo de trabajo y la elegibilidad de la transferencia en un entorno del mundo real y de bajo volumen.
Principales métodos:
- Análisis retrospectivo multicéntrico de 109 pacientes con EIA transferidos para TM desde CP de bajo volumen.
- Evaluación retrospectiva de imágenes estándar utilizando el software Brainomix 360 para oclusiones de vasos grandes (OVG), cambios isquémicos y colaterales.
- Decisiones de transferencia simuladas por neurólogos cegados, comparando los tiempos de flujo de trabajo asistidos por IA con una cohorte de centro integral de ictus (CCI).
Principales resultados:
- La IA demostró una sensibilidad del 83,5% en la detección de oclusiones de la circulación anterior, mayor para las oclusiones M1.
- Se consideró que el 78,9% de los pacientes eran elegibles para la TM, lo que podría beneficiarse de la reducción de los tiempos de flujo de trabajo.
- La IA evitó potencialmente transferencias inútiles al identificar al 4,6% de los pacientes con cambios isquémicos extensos como no elegibles.
- La obtención de imágenes asistida por IA en los CSC redujo significativamente el tiempo de notificación de CTA a EVT (11 min frente a 48 min).
Conclusiones:
- La obtención de imágenes asistida por IA mejora significativamente las decisiones de transferencia y la eficiencia del flujo de trabajo en CP de bajo volumen, especialmente sin interpretación en tiempo real.
- La IA mejora la evaluación de la elegibilidad para la TM, fortaleciendo las redes regionales de ictus.
- La adopción más amplia de la IA puede optimizar las vías de los pacientes para el tratamiento del ictus agudo.
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