Feasibility and Interest of Continuous Diaphragmatic Fatigue Monitoring Using Wavelet Denoising in ICU and Anesthesia

摘要

Measures of diaphragmatic electromyography (Edi), and respiratory mechanics, have demonstrated earlychanges before clinical complications. However, automatic Edi data collection is not adequate today due mainly to severeartefacts as well as to loss of signal. We thus intended to develop a new device with embedded artificial intelligence tooptimize automatic Edi recordings independantly of artefacts and of probe displacement.We first chose the best mathematical tool to denoise Edi, using an established database, giving multiresolution waveletsas the best, resulting in the permanent availability of the H/L spectral index, a recognized representative of diaphragmaticfatigue. Fatigue was simultaneously measured using the classical mechanical f/Vt index (Rapid Shallow Breathing Index,RSBI), as well as the transdiaphragmatic pressure.We then performed a comparison of real-time H/L and RSBI in a group of seven healthy volunteers, before and duringmidazolam sedation infusion 0.1 mg.kg-1, with a parallel CPAP administration (2.5, 5.0, and 10 cm H2O) intended tocompensate for airways resistance due to midazolam. Procedure was ended by delivering the antagonistic flumazenil 0.2to 0.5 mg.kg-1. Progressive fatigue due to midazolam, the relief due to CPAP, as well as the answer to the anatgonist flumazenil,were shown earlier by the H/L index than by the RSBI change.Our new H/L monitoring device may greatly improve clinical follow-up of anesthetized patients as well as help to determinethe optimal period for ventilatory weaning in ICU (Clinical Trials NCT00133939).