Fagan, Andrew

Lactulose-based hepatic encephalopathy treatment requires bowel movements/day titration, which is improved with Bristol stool scale (BSS) incorporation. Dieta app evaluates artificial intelligence (AI)-based BSS (AI-BSS) with stool images. Initially, controls (N = 13) and cirrhosis patients on lactulose/not on lactulose (n = 33) were trained on the app. They entered self-reported BSS (self-BSS) with AI-BSS communicated. Lactulose dose changes were tracked. A subset (n = 12) was retested with AI communication blocked. Most subjects were comfortable with the app. Self/AI-BSS and lactulose dose/AI-BSS correlation increased with app use. AI-BSS communications improved insight into self-BSS over time. Dieta app to gauge stool AI characteristics was acceptable and increased insight into lactulose dose and BSS in cirrhosis.

Background: App-based technologies could enhance patient and caregiver communication and provide alerts that potentially reducing readmissions. However, the burden of App alerts needs to be optimized to reduce provider burnout. Aim: The purpose of this study was to determine subjective and objective burden of using the Patient Buddy App, a health information technology (HIT) on providers in a randomized multicenter trial, who completed a semi-quantitative Likert scale survey regarding training procedures, data and privacy concerns, follow-up details, and technical support. This randomized multicenter trial recruits cirrhosis inpatients and their caregivers, and randomizes them into standard-of-care, HIT (communication only via App) and HIT+visits (App+phone calls/visits) for 30 days after discharge. The alerts are monitored by providers through a central iPad. The reason(s) and number of alerts were recorded as the objective burden. A total of 1442 messages were sent as alerts from the 103 dyads (patient + caregiver) (n=206) randomized to HIT arms. The most common messages related to Hepatic Encephalopathy (HE) (high or low bowel movement=50% or orientation tests=37%). Twelve providers completed the surveys reflecting the following themes—92% and 100%, felt adequately trained and confident about educating the patients and caregivers before roll out of App and had no concerns related to data and privacy; 70%, felt that appropriate time was spent on pursuing reason for data not being logged; 60% each, had issues with availability of adequate technical support and connectivity. Conclusion: The Patient Buddy App randomized multicenter trial till date shows an overall favorable rating regarding training procedures/education, privacy concerns, and ease of message follow-up, from providers. However, it is important to gauge and address subjective and objective burdens of monitoring human resources in current and future HIT studies to avoid burnout and to ensure successful study completion.

Background and Aims Acute kidney injury (AKI) has a poor prognosis in cirrhosis. Given the variability of creatinine, the prediction of AKI and dialysis by other markers is needed. The aim of this study is to determine the role of serum and urine metabolomics in the prediction of AKI and dialysis in an inpatient cirrhosis cohort. Approach and Results Inpatients with cirrhosis from 11 North American Consortium of End‐stage Liver Disease centers who provided admission serum/urine when they were AKI and dialysis‐free were included. Analysis of covariance adjusted for demographics, infection, and cirrhosis severity was performed to identify metabolites that differed among patients (1) who developed AKI or not; (2) required dialysis or not; and/pr (3) within AKI subgroups who needed dialysis or not. We performed random forest and AUC analyses to identify specific metabolite(s) associated with outcomes. Logistic regression with clinical variables with/without metabolites was performed. A total of 602 patients gave serum (218 developed AKI, 80 needed dialysis) and 435 gave urine (164 developed AKI, 61 needed dialysis). For AKI prediction, clinical factor–adjusted AUC was 0.91 for serum and 0.88 for urine. Major metabolites such as uremic toxins (2,3‐dihydroxy‐5‐methylthio‐4‐pentenoic acid [DMTPA], N2N2dimethylguanosine, uridine/pseudouridine) and tryptophan/tyrosine metabolites (kynunerate, 8‐methoxykyunerate, quinolinate) were higher in patients who developed AKI. For dialysis prediction, clinical factor–adjusted AUC was 0.93 for serum and 0.91 for urine. Similar metabolites as AKI were altered here. For dialysis prediction in those with AKI, the AUC was 0.81 and 0.79 for serum/urine. Lower branched‐chain amino‐acid (BCAA) metabolites but higher cysteine, tryptophan, glutamate, and DMTPA were seen in patients with AKI needing dialysis. Serum/urine metabolites were additive to clinical variables for all outcomes. Conclusions Specific admission urinary and serum metabolites were significantly additive to clinical variables to predict AKI development and dialysis initiation in inpatients with cirrhosis. These observations can potentially facilitate earlier initiation of renoprotective measures.

BACKGROUND: Patients with cirrhosis are growing older and the overlap between hepatic encephalopathy (HE) & pre-dementia mild cognitive impairment (MCI) is unclear. HE affects visuospatial/psychomotor speed while MCI affects memory. Aim: Determine the performance of elderly cirrhotics on tests for HE and dementia and their impact on quality of life (QOL). METHODS: Outpatient cirrhotics and controls ages 65–95 years were recruited at 4 centers. Subjects had to have MMSE > 25, no current HE or dementia to be eligible. All subjects got tests for HE (psychometric hepatic encephalopathy score, PHES: 5 tests & low score = poor, EncephalApp, OffTime + OnTime, high score = poor) and QOL: Sickness Impact profile (SIP, high score = poor QOL). Cirrhotics also got tests for MCI; RBANS (tests immediate memory, delayed memory, language, visuo-spatial & attention). A neuro-psychologist evaluated results and divided cirrhotics into (A) unimpaired (B) MCI only (C) HE only & (D) (MCI/HE overlap). Demographics, MELD, alcohol etiology, and SIP were compared. Finally, age, gender and education-adjusted norms were created for PHES and EncephalApp based on the controls. Presence of MHE and sensitivity of EncephalApp for MHE diagnosis were evaluated. RESULTS: 109 cirrhotics and 100 non-cirrhotic subjects were included. Demographics/education levels were statistically similar between centers. Controls were older than cirrhotics (74.9 ± 6.6 vs 70.5 ± 4.4, P < 0.05) and had similar education/gender distribution. Despite this, controls performed better than cirrhotics on all tests (PHES 2.9 ± 12.4 vs −4.5 ± +4.5, P < 0.001, EncephalApp Off+On 181.4 ± +71.9 vs 218.2 ± +80.0, P = 0.03) and had a better QOL (SIP total 3.8 ± +7.1 vs 7.9 ± +9.5, Psych 3.3 ± +8.4 vs 7.2 ± +11.1, Phys 3.0 ± +6.2 vs 6.7 ± +9.5, all P < 0.001). Within cirrhosis subgroups (Table 1), demographics, MELD/alc & MMSE were similar. Pts with both MCI/HE had worse cognition on all tests, which translated into a worse QOL compared to other groups. Presence of HE, with/without MCI, contributed towards poor QOL. Norms for PHES/EncephalApp: Adjusting for age, gender & education, 17% (n = 17) patients were positive for MHE on PHES compared to controls. On EncephalApp, 49% (n = 47) patients were positive. AUC for EncephalApp using PHES as the gold standard was 0.86 (0.78-0.95 CI). CONCLUSIONS: In this multi-center study, adjusted norms defining the high sensitivity of EncephalApp to diagnose HE in older individuals were created. Presence of HE regardless of MCI contributed towards poor cognition and QOL in patients >65 years.