SciELO - Scientific Electronic Library Online

 
vol.15 issue2PCorteSoft - System for determination of optimal cut-off point in predictive scales and categorization of continuous variablesPictobana: A tool for Communication with AutisticChildren author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Article

Indicators

  • Have no cited articlesCited by SciELO

Related links

  • Have no similar articlesSimilars in SciELO

Share


Revista Cubana de Informática Médica

On-line version ISSN 1684-1859

Abstract

CABRALES FUENTES, José; MENDOZA CABALE, Alejandro Luis  and  VERDECIA BARBIE., Susana. UDC -COVID19: digital tool to predict the withdrawal of invasive mechanical ventilation in patients with COVID-19. RCIM [online]. 2023, vol.15, n.2  Epub Dec 01, 2023. ISSN 1684-1859.

In December 2019, the Authorities of the People's Republic of China reported to the WHO several cases of pneumonia of unknown etiology in Wuhan, a city located in the Chinese province of Hubei. A week later, they confirmed that it was a new coronavirus called SARS-CoV-2, which causes various clinical manifestations encompassed under the term COVID-19. The present work presents an application prototype with the name UDC-COVID19 that proposes a digital tool based on an updated review of the ultrasonographic evaluation of the diaphragm as a predictive element to withdraw invasive mechanical ventilation in patients with COVID-19, providing an excellent digital tool for the evaluation of the diaphragmatic structure and dynamic function since it is precise, reproducible, without ionizing radiation, easy to perform at the patient's bedside and cost effective in critically ill patients; mechanical ventilation.

Keywords : COVID-19; ultrasound; diaphragm; predictive.

        · abstract in Spanish     · text in Spanish     · Spanish ( pdf )