Detection of Minimal Hepatic Encephalopathy in Iranian Patients with Cirrhosis

Psychometric methods for diagnosing and monitoring minimal hepatic encephalopathy -current validation level and practical use

Hepatic encephalopathy (HE) is cerebral dysfunction caused by liver failure and inflicts 30-40% of patients with liver cirrhosis during their disease course. Clinically manifest HE is often preceded by minimal HE (MHE) - a clinically undetectable cognitive disturbance closely associated with loss of quality of life. Accordingly, detecting and treating MHE improve the patients' daily functioning and prevent HE-related hospital admissions. The scope of this review article is to create an overview of the validation level and usage of psychometric tests used to detect MHE: Portosystemic hepatic encephalopathy test, continuous reaction time test, Stroop EncephalApp, animal naming test, critical flicker frequency test, and inhibitory control test. Our work is aimed at the clinician or scientist who is about to decide on which psychometric test would fit best in their clinic, cohort, or study. First, we outline psychometric test validation obstacles and requirements. Then, we systematically approach the literature on each test and select well-conducted studies to answer the following questions:• Which percentage of patients with cirrhosis does the test deem as having MHE?• Is the test able to predict clinically manifest HE?• Is there a well-known test-retest variation and inter-observer variation?• Is the test able to detect a treatment response?• Is the test result affected by age, educational level, gender, or comorbidities?

Artificial Intelligence and Its Application to Minimal Hepatic Encephalopathy Diagnosis

Hepatic encephalopathy (HE) is a brain dysfunction caused by liver insufficiency and/or portosystemic shunting. HE manifests as a spectrum of neurological or psychiatric abnormalities. Diagnosis of overt HE (OHE) is based on the typical clinical manifestation, but covert HE (CHE) has only very subtle clinical signs and minimal HE (MHE) is detected only by specialized time-consuming psychometric tests, for which there is still no universally accepted gold standard. Significant progress has been made in artificial intelligence and its application to medicine. In this review, we introduce how artificial intelligence has been used to diagnose minimal hepatic encephalopathy thus far, and we discuss its further potential in analyzing speech and handwriting data, which are probably the most accessible data for evaluating the cognitive state of the patient.