This month’s Editor’s Choice by Liu et al evaluated the ability of clinicians to interpret ventilator waveforms using an online survey with images of waveforms. The survey was completed anonymously by respiratory therapists (RTs), physicians, and nurses with at least one year of ICU experience. 1,832 professionals from 31 countries responded, and half answered at least 60% of the questions accurately. Greater success was related to ICU work experience, being an RT, the highest degree earned, and prior ventilator waveform training. They concluded that many discordances were poorly recognized by all clinicians. Notó and colleagues provide commentary suggesting that more sophisticated ventilator algorithms and technologies to better detect and manage discordance are forthcoming. They point to use of sophisticated algorithms wherein ventilator settings can be dynamically adjusted, enhancing patient-ventilator synchronization and reducing discomfort. They predict that artificial intelligence and machine learning may enable ventilators to perform customized adjustments according to patient-specific respiratory patterns, improving comfort and outcomes.
Christianson and others studied a new interface to improve pulse-dose oxygen delivery. They studied traditional interfaces and a new interface using 8 RTs as volunteers using a cylinder oxygen conserving device and portable O2 concentrators. Subjects breathed both orally and nasally. Successful triggering was recorded and subjects rated …
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