The Stroop smartphone application is a short and valid method to screen for minimal hepatic encephalopathy

Abstract

Minimal hepatic encephalopathy (MHE) detection is difficult because of the unavailability of short screening tools. Therefore, MHE patients can remain undiagnosed and untreated. The aim of this study was to use a Stroop smartphone application (app) (EncephalApp_Stroop) to screen for MHE. The app and standard psychometric tests (SPTs; 2 of 4 abnormal is MHE, gold standard), psychometric hepatic encephalopathy score (PHES), and inhibitory control tests (ICTs) were administered to patients with cirrhosis (with or without previous overt hepatic encephalopathy; OHE) and age-matched controls from two centers; a subset underwent retesting. A separate validation cohort was also recruited. Stroop has an "off" state with neutral stimuli and an "on" state with incongruent stimuli. Outcomes included time to complete five correct runs as well as number of trials needed in on (Ontime) and off (Offtime) states. Stroop results were compared between controls and patients with cirrhosis with or without OHE and those with or without MHE (using SPTs, ICTs, and PHES). Receiver operating characteristic analysis was performed to diagnose MHE in patients with cirrhosis with or without previous OHE. One hundred and twenty-five patients with cirrhosis (43 previous OHE) and 134 controls were included in the original cohort. App times were correlated with Model for End-Stage Liver Disease (Offtime: r = 0.57; Ontime: r = 0.61; P < 0.0001) and were worst in previous OHE patients, compared to the rest and controls. Stroop performance was also significantly impaired in those with MHE, compared to those without MHE, according to SPTs, ICTs, and PHES (all P < 0.0001). A cutoff of >274.9 seconds (Ontime plus Offtime) had an area under the curve of 0.89 in all patients and 0.84 in patients without previous OHE for MHE diagnosis using SPT as the gold standard. The validation cohort showed 78% sensitivity and 90% specificity with the >274.9-seconds Ontime plus Offtime cutoff. App result patterns were similar between the centers. Test-retest reliability in controls and those without previous OHE was good; a learning effect on Ontime in patients with cirrhosis without previous OHE was noted.

Conclusion: The Stroop smartphone app is a short, valid, and reliable tool for screening of MHE.

Figure 1

Median and IQR of time required to complete the App in the “Off” and “On” states. Figure 1A shows the distribution of values in the entire group in which control values are compared to cirrhotics without prior OHE and those with prior OHE. Figure 1B shows the comparison between controls and cirrhotics with MHE and no MHE based on standard tests. No_OHE: no prior overt hepatic encephalopathy, OHE: prior overt HE, No_MHE: no MHE and MHE: minimal hepatic encephalopathy. All comparisons were highly statistically significant

Figure 1

Median and IQR of time required to complete the App in the “Off” and “On” states. Figure 1A shows the distribution of values in the entire group in which control values are compared to cirrhotics without prior OHE and those with prior OHE. Figure 1B shows the comparison between controls and cirrhotics with MHE and no MHE based on standard tests. No_OHE: no prior overt hepatic encephalopathy, OHE: prior overt HE, No_MHE: no MHE and MHE: minimal hepatic encephalopathy. All comparisons were highly statistically significant

Figure 2

ROC curve of OnTime+OffTime for all cirrhotic patients (2A) and in those without prior OHE (2B) showing a high AUC for diagnosis when standard tests are used as gold standard. The cut-off was a 274.9 seconds for both populations.

Figure 2

ROC curve of OnTime+OffTime for all cirrhotic patients (2A) and in those without prior OHE (2B) showing a high AUC for diagnosis when standard tests are used as gold standard. The cut-off was a 274.9 seconds for both populations.

Figure 3

Individual plots of OnTime+OffTime in the original and prospective validation cohort; the open circles are individual patients while the bars represent 95% confidence interval for the mean. Figure 3A shows the cut-off generated by ROC analysis dividing the original 125 cirrhotic patients, Figure 3B shows similar values in the 82 cirrhotics of the original cohort without prior OHE, and Figure 3C shows the performance of this cut-off in prospective cirrhotic validation cohort.

Figure 3

Individual plots of OnTime+OffTime in the original and prospective validation cohort; the open circles are individual patients while the bars represent 95% confidence interval for the mean. Figure 3A shows the cut-off generated by ROC analysis dividing the original 125 cirrhotic patients, Figure 3B shows similar values in the 82 cirrhotics of the original cohort without prior OHE, and Figure 3C shows the performance of this cut-off in prospective cirrhotic validation cohort.

Figure 3

Individual plots of OnTime+OffTime in the original and prospective validation cohort; the open circles are individual patients while the bars represent 95% confidence interval for the mean. Figure 3A shows the cut-off generated by ROC analysis dividing the original 125 cirrhotic patients, Figure 3B shows similar values in the 82 cirrhotics of the original cohort without prior OHE, and Figure 3C shows the performance of this cut-off in prospective cirrhotic validation cohort.