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Mejorar la gestión de la ventilación mecánica con IA: visión por computadora para la detección automatizada de los
Diego de Carvalho1, Kleyton Hoffmann2, João Rogério Nunes Filho3
1Programa de Pós-Graduação em Biociências e Saúde (PPGBS), Universidade do Oeste de Santa Catarina, Joaçaba, SC, Brazil.
Journal of critical care
|August 23, 2025
Resumen
Una plataforma de IA, NexoVent, detecta con precisión la configuración del ventilador y la asíncronia paciente-ventilador (PVA) a partir de las imágenes de pantalla. Esta tecnología ofrece apoyo a la toma de decisiones en tiempo real para la gestión de la ventilación mecánica en las UCI.
Área de la Ciencia:
- Medicina de cuidados intensivos
- Ingeniería biomédica
- Inteligencia artificial en el cuidado de la salud
Sus antecedentes:
- La ventilación mecánica es crucial en las unidades de cuidados intensivos (UCI).
- La asíncronia paciente-ventilador (AVP) puede tener un impacto negativo en los resultados del paciente.
- El monitoreo en tiempo real de los parámetros del ventilador y el PVA es esencial para una atención óptima del paciente.
Objetivo del estudio:
- Para evaluar el rendimiento de la plataforma NexoVent AI.
- Evaluar su capacidad para detectar los modos de ventilación, los parámetros y el PVA a partir de las imágenes de la pantalla del ventilador.
- Para determinar la precisión de la extracción de datos basada en imágenes impulsada por IA en tiempo real.
Principales métodos:
- Estudio de observación en una UCI de cuidados terciarios.
- Ventiladores Servo-i y Servo-s usados en modo PCV.
- Empleó visión por computadora, OCR y análisis de formas de onda en imágenes de la pantalla del ventilador a través de dispositivos móviles.
- Comparación de la detección por IA de seis tipos de PVA con el consenso de los expertos.
Principales resultados:
- NexoVent logró una precisión del 95,4% para los parámetros del ventilador y del 94,0% para los modos del ventilador.
- La precisión de detección de la asíncronia osciló entre el 81,6% (ciclo retrasado) y el 97,8% (esfuerzo ineficaz).
- Todos los análisis se basaron en imágenes, no requiriendo una interfaz directa con el ventilador.
Conclusiones:
- NexoVent detecta con precisión los datos de ventilación y PVA utilizando visión por computadora no invasiva.
- La plataforma muestra potencial para mejorar la gestión de la ventilación mecánica.
- Puede proporcionar apoyo a la toma de decisiones clínicas en tiempo real, especialmente cuando los conocimientos especializados o la interoperabilidad de los dispositivos son limitados.
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