QuickStroop, a Shortened Version of EncephalApp, Detects Covert Hepatic Encephalopathy With Similar Accuracy Within One Minute

Background & Aims: Covert hepatic encephalopathy (CHE) is associated with poor outcomes but is often not diagnosed because of the time requirement. Psychometric hepatic encephalopathy score (PHES) is the gold standard against which EncephalApp Stroop has been validated. However, EncephalApp (5 runs each in “Off” and “On” state) can take up to 10 minutes. This study sought to define the smallest number of EncephalApp runs needed for comparable accuracy to the total EncephalApp using CHE on PHES as gold standard. Methods: A derivation and a validation cohort of outpatients with cirrhosis who underwent PHES (gold standard) and total EncephalApp was recruited. Data were analyzed for individual runs versus total EncephalApp time versus PHES-CHE. The derivation cohort (n = 398) was split into training (n = 299) and test (n = 99) sets. From the training data set a regression model was created with age, gender, education, and various sums of the “Off” settings. After this, a K-fold cross-validation on the test dataset was performed for both total EncephalApp time and individual Off runs and for the validation cohort. Results: In both cohorts, Off runs 1 + 2 had statistically similar area under the receiver operating curve and P value to the total EncephalApp for PHES-CHE prediction. The adjusted (age, gender, education) regression formula from the derivation cohort showed an accuracy of 84% to diagnose PHES-CHE in the validation cohort. Time for CHE diagnosis decreased from 203.7 (67.82) to 36.8 (11.25) seconds in the derivation and from 178.2 (46.19) to 32.9 (9.94) seconds in the validation cohort. Conclusions: QuickStroop, which is completed within 1 minute, gives an equivalent ability to predict CHE on the gold standard compared with the entire EncephalApp time.