The following is a summary of “Advanced waveform analysis of diaphragm surface EMG allows for continuous non-invasive assessment of respiratory effort in critically ill patients at different PEEP levels,” published in the June 2024 issue of Critical Care by Warnaar et al.
Monitoring breathing effort in critical illness or ventilator-dependent patients is crucial to avoid over- and under-assistance. While Surface electromyography of the diaphragm (sEMGdi) offers a continuous and noninvasive way to assess this through neuromuscular coupling (NMCdi), its usefulness is hampered by signal distortion from other muscles.
Researchers conducted a retrospective study establishing advanced analysis methods and quality criteria for sEAdi signals and further investigated the impact of clinically relevant PEEP levels on non-invasive NMCdi.
They obtained the NMCdi by dividing end-expiratory occlusion pressure (Pocc) by sEAdi. Based on three consecutive Pocc measurements performed at increasing PEEP levels during pressure support ventilation. However, a novel automated signal analysis method was employed, which consists of both tolerant and strict criteria and inadequate waveforms were excluded to ensure data quality. The coefficient of variation (CoV) of NMCdi was assessed after the manual and automated quality assessments, and the impact of incremental PEEP changes on NMCdi was also observed.
The result showed 593 maneuvers conducted during 42 PEEP trials involving 17 patients in ICU, waveform exclusion was primarily guided by specific criteria, low sEAdi signal-to-noise ratio(Ntolerant = 155, 37%, Nstrict = 241, 51% waveforms excluded), irregular cessation of Pocc (Ntolerant = 145, 35%, Nstrict= 145, 31%), and high sEAdi area under the baseline (Ntolerant = 94, 23%, Nstrict = 79, 17%). The implementation of strict automated assessment resulted in a notable reduction in the CoV of NMCdi, dropping from 37% to 15% with basic quality assessment .Furthermore, a significant decrease was observed with an increase in PEEP in NMCdi by 4.9 percentage points per cmH2O.
Investigators concluded that advanced analysis of Pocc and sEAdi signals led to improved automated detection of reliable waveforms. The findings emphasized the importance of considering PEEP when evaluating respiratory effort using sEAdi, paving the way for a more comprehensive assessment approach.
Source: ccforum.biomedcentral.com/articles/10.1186/s13054-024-04978-0