Facial expression associates with longitudinal multi-organ failure: an ICU cohort study

Author:

Cox Eline G.M.1,Bussel Bas C.T. van2,Llamazares Nerea Campillo1,Sels Jan-Willem E.M.2,Onrust Marisa1,Horst Iwan C.C. van der2,Koeze Jacqueline1,Group SICS Study1

Affiliation:

1. University of Groningen, University Medical Center Groningen

2. Maastricht University Medical Center+, University Maastricht

Abstract

Abstract Background Facial expression, at least unconsciously, may affect clinical decisions and treatments in the ICU. However, the association between objective clinical measurement of facial expression and multi-organ failure remains unknown. The aim of this study was to examine whether facial expression at admission is associated with longitudinal measurement of multi-organ failure. Methods This was a sub-study of the Simple Intensive Care Studies-II, a prospective observational cohort study. All adult patients acutely admitted to the ICU between March 26, 2019, and July 10, 2019, were included. Facial expression was assessed within three hours of ICU admission using predefined pictograms. The SOFA score was serially measured each day for the first seven days after ICU admission. The association between eye opening and facial color with longitudinal Sequential Organ Failure Assessment (SOFA) scores were investigated using generalized estimation equations. Results SOFA scores were measured in 228 patients. Clinical gestalt scored by the degree of eye opening was associated with a higher SOFA score at admission and follow-up (unadjusted 0.7 points per step (95%CI 0.5 to 0.9)). Facial color was not associated with worse SOFA score over time. However, patients with slinked or closed eyes combined with blushed skin had a lower SOFA score than patients with a pale or normal skin color (P-interaction < 0.1). Conclusions The patient's face revealed integrated cues regarding the disease state of critically ill patients, as scored by the degree of eye opening and facial color. Incorporating clinical gestalt using more advanced facial recognition techniques is promising to support future intensive care.

Publisher

Research Square Platform LLC

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