To the Editor: Prone position ventilation has been shown to improve oxygenation and survival in patients with severe acute respiratory distress syndrome (ARDS) [1]. Facing the coronavirus disease 2019 (COVID-19) pandemic, prone positioning (PP) is of crucial importance to treat severe ARDS patients [2]. Nevertheless, the high number of ICU admissions quickly overwhelmed the ability of the daily ICU team to place patients in PP, a complex and time-consuming maneuver. Thus, we created a dedicated medical team with reassigned volunteers to cope with the large number of patients requiring PP. PP Team consisted of five volunteers: a senior medical non-intensivist physician placed at the patient's head to secure the endotracheal tube and four medical fellows or medical students placed at each side of the bed. For patients treated with VV-ECMO, a supplementary physician was added to secure the lines. Since PP is a complex procedure and has many potential adverse events requiring adequate and well-trained staff, volunteers received previously a theoretical training and a hands-on ad hoc training session. PP teams followed the guidelines for PP placement [1]. This retrospective observational study was performed in our extended ICU (from 22 to 46 beds), from the first day of deployment of PPT (March 23 to April 23, 2020). The main characteristics and outcomes of prone positioned patients (n = 63) are presented in Table 1.

During the past decade, several studies have identified electroencephalographic (EEG) correlates of selective auditory attention to speech. In these studies, typically, listeners are instructed to focus on one of two concurrent speech streams (the “target”), while ignoring the other (the “masker”). EEG signals are recorded while participants are performing this task, and subsequently analyzed to recover the attended stream. An assumption often made in these studies is that the participant’s attention can remain focused on the target throughout the test. To check this assumption, and assess when a participant’s attention in a concurrent speech listening task was directed toward the target, the masker, or neither, we designed a behavioral listen-then-recall task (the Long-SWoRD test). After listening to two simultaneous short stories, participants had to identify keywords from the target story, randomly interspersed among words from the masker story and words from neither story, on a computer screen. To modulate task difficulty, and hence, the likelihood of attentional switches, masker stories were originally uttered by the same talker as the target stories. The masker voice parameters were then manipulated to parametrically control the similarity of the two streams, from clearly dissimilar to almost identical. While participants listened to the stories, EEG signals were measured and subsequently, analyzed using a temporal response function (TRF) model to reconstruct the speech stimuli. Responses in the behavioral recall task were used to infer, retrospectively, when attention was directed toward the target, the masker, or neither. During the model-training phase, the results of these behavioral-data-driven inferences were used as inputs to the model in addition to the EEG signals, to determine if this additional information would improve stimulus reconstruction accuracy, relative to performance of models trained under the assumption that the listener’s attention was unwaveringly focused on the target. Results from 21 participants show that information regarding the actual – as opposed to, assumed – attentional focus can be used advantageously during model training, to enhance subsequent (test phase) accuracy of auditory stimulus-reconstruction based on EEG signals. This is the case, especially, in challenging listening situations, where the participants’ attention is less likely to remain focused entirely on the target talker. In situations where the two competing voices are clearly distinct and easily separated perceptually, the assumption that listeners are able to stay focused on the target is reasonable. The behavioral recall protocol introduced here provides experimenters with a means to behaviorally track fluctuations in auditory selective attention, including, in combined behavioral/neurophysiological studies.