Feasibility and Variability of Automated Pupillometry Among Stroke Patients and Healthy Participants: Potential Implications for Clinical Practice.

Background: Early neurological deterioration (END) is common after stroke and represents a poor prognostic marker. Manual pupillary assessment to detect END is subjective and has poor interrater reliability. Novel methods of automated pupillometry may be more reliable and accurate.