Eye Movements as a Prognostic Indicator of Neurologic Outcomes in Cardiac Arrest Patients in the Intensive Care Unit
Cameron Hill1, Leigh Ann Malinger2, Abrar Al-Faraj1, Ika Noviawaty1, Charlene Ong1
1Boston University Chobanian and Avedisian School of Medicine/Boston Medical Center, 2Boston Medical Center
Objective:

To assess whether eye movements add prognostic value beyond malignant EEG features and characterize the relationship between eye movements, malignant EEG features, and discharge outcomes in cardiac arrest (CA) patients.

Background:

Neurological monitoring of CA patients is essential for evaluating recovery potential. Eye movement quantification via EEG may serve as a novel noninvasive biomarker indicating preservation of neural pathways for consciousness recovery. Characterizing eye movement relationships with other prognostic markers can clarify their contribution to comatose CA assessment.


Design/Methods:

We conducted a retrospective cohort study of 48 CA patients who underwent continuous EEG/EOG monitoring post-arrest at Boston Medical Center (2020-2023). Team members quantified eye movements (that were normalized per hour) and malignant EEG features, including absence of reactivity, burst suppression, periodic discharge, polyspike waves, or discontinuous patterns. Among discharged patients, outcomes included corneal reflex, spontaneous or stimulus-induced eye opening, and command following. Logistic regression models were adjusted for age and sex, with a likelihood ratio test assessing the impact of eye movements on model fit.


Results:

Among 48 patients (65% male, median age 60), 19% had malignant features, and 31% were deceased at discharge. Preliminary analyses reveal a statistically significant negative association between eye movements and death and statistically significant positive associations between eye movements and discharge outcomes. Including eye movements improved model fit for death (LR 11.44, p=0.022), pupillary reflex (LR 8.58, p=0.072), corneal reflex (LR 12.36, p=0.015), eye-opening to stimuli (LR 9.51, p=0.049), spontaneous eye opening (LR 12.22, p=0.016), and command following (LR 13.05, p=0.011).


Conclusions:

Incorporating eye movements in predictive models may enhance assessment of neurological outcomes in CA patients, positioning eye movements as a potential non-invasive biomarker for neuroprognostication in the ICU. 


10.1212/WNL.0000000000211806
Disclaimer: Abstracts were not reviewed by Neurology® and do not reflect the views of Neurology® editors or staff.