Author:
Bellal Mathieu,Lelandais Julien,Chabin Thomas,Heudron Aurélie,Gourmelon Thomas,Bauduin Pierrick,Cuchet Pierre,Daubin Cédric,De Carvalho Ribeiro Célia,Delcampe Augustin,Goursaud Suzanne,Joret Aurélie,Mombrun Martin,Valette Xavier,Cerasuolo Damiano,Morello Rémy,Mordel Patrick,Chaillot Fabien,Dutheil Jean Jacques,Vivien Denis,Du Cheyron Damien
Abstract
BackgroundPain management is an essential and complex issue for non-communicative patients undergoing sedation in the intensive care unit (ICU). The Behavioral Pain Scale (BPS), although not perfect for assessing behavioral pain, is the gold standard based partly on clinical facial expression. NEVVA©, an automatic pain assessment tool based on facial expressions in critically ill patients, is a much-needed innovative medical device.MethodsIn this prospective pilot study, we recorded the facial expressions of critically ill patients in the medical ICU of Caen University Hospital using the iPhone and Smart Motion Tracking System (SMTS) software with the Facial Action Coding System (FACS) to measure human facial expressions metrically during sedation weaning. Analyses were recorded continuously, and BPS scores were collected hourly over two 8 h periods per day for 3 consecutive days. For this first stage, calibration of the innovative NEVVA© medical device algorithm was obtained by comparison with the reference pain scale (BPS).ResultsThirty participants were enrolled between March and July 2022. To assess the acute severity of illness, the Sequential Organ Failure Assessment (SOFA) and the Simplified Acute Physiology Score (SAPS II) were recorded on ICU admission and were 9 and 47, respectively. All participants had deep sedation, assessed by a Richmond Agitation and Sedation scale (RASS) score of less than or equal to −4 at the time of inclusion. One thousand and six BPS recordings were obtained, and 130 recordings were retained for final calibration: 108 BPS recordings corresponding to the absence of pain and 22 BPS recordings corresponding to the presence of pain. Due to the small size of the dataset, a leave-one-subject-out cross-validation (LOSO-CV) strategy was performed, and the training results obtained the receiver operating characteristic (ROC) curve with an area under the curve (AUC) of 0.792. This model has a sensitivity of 81.8% and a specificity of 72.2%.ConclusionThis pilot study calibrated the NEVVA© medical device and showed the feasibility of continuous facial expression analysis for pain monitoring in ICU patients. The next step will be to correlate this device with the BPS scale.