Cirrhosis is an increasingly prevalent medical condition in the United States that impacts health-related quality of life, healthcare resource utilization and survival. Patients with decompensated cirrhosis occasionally suffer from hepatic encephalopathy which is a serious complication that results from portosystemic shunting of blood leading to a spectrum of neuropsychiatric changes and alteration in consciousness levels when it becomes overt (overt hepatic encephalopathy, OHE).~Hepatic encephalopathy affects 30-45% of patients with cirrhosis and its occurrence and progression is associated with higher mortality.~In particular, Hepatic encephalopathy (HE) is an independent predictor of hospital readmissions in patients with cirrhosis. Encephalopathy could be overt with obvious deterioration in the level of consciousness leading to hospitalizations, but could also be covert and less obvious to the patient and healthcare provider.~Covert hepatic encephalopathy (CHE) is often unrecognized by healthcare providers leading to falls, motor vehicular accidents, and potential progression to overt confusion. Progression of CHE to OHE makes recognition of this condition important as early identification and treatment can potentially improve quality of life, reduce hospital readmissions and healthcare costs. Existing diagnostic tools are not only tedious and time consuming, but also impacted by factors such as level of education, reducing their utility in clinical practice. The ideal test would be easy to use, quantifiable, quick, cheap, reliable, and able to predict outcomes.~The exploratory study will utilize a noninvasive computer application (Neurofit) that performs oculometric assessment of dynamic visual processing. Eye movements are short latency, voluntary motor behaviors that consist of various aspects including visual motion, pursuit initiation, steady-state tracking, direction tuning, and speed tuning. The computer application is based on an eye movement methodology that can quantify many aspects of human dynamic visual processing using a noninvasive video-based eye tracking technology with validated oculometric analysis techniques.~Prior studies have demonstrated sensorimotor dysfunction in patients with diffuse brain injury which leads to derangement in information processing throughout the brain. This computer application has been utilized in patients with traumatic brain injury (TBI). Liston et al, in a study of 34 TBI patients, demonstrated that TBI patients had several individual oculometrics that were significantly deranged including pursuit latency, initial pursuit acceleration, pursuit gain, catch-up saccade amplitude, proportion smooth tracking, and speed responsiveness as compared to a separate control group. The application was able to discriminate TBI subjects from controls with an 81% probability that increased with self-reported TBI severity.~Rationale Hepatic encephalopathy is believed to occur as a consequence of portosystemic shunting leading to toxins, octapamines, free fatty acids amongst others accumulating in the brain, causing impairment in neurocognitive functioning. The extent of brain dysfunction associated with hepatic encephalopathy has not been fully characterized. Hepatic encephalopathy could potentially impair global brain function leading to oculomotor discoordination that can be detected with this computer software. By comparing individual and composite oculometric data between patients with cirrhosis and those without cirrhosis this study may identify any significant differences or distinct patterns that may exist as a result of hepatic encephalopathy. For this study, covert hepatic encephalopathy will be determined by paper-based psychometric testing. Any data obtained from this feasibility/exploratory study, will serve as preliminary data for larger studies and future validation.
This study involves utilizing a noninvasive computer application (Neurofit) that performs oculometric assessment of dynamic visual processing in patients with liver cirrhosis to see if the presence of advance liver disease influences eye movement metrics.