Predicting harmful alcohol relapse after liver transplant: The HALT score.

BACKGROUND: Alcohol-associated liver disease (AALD) is a rapidly growing indication for liver transplantation (LT). We aimed to examine various clinical, demographic, and behavioral factors to predict post-LT alcohol relapse and graft survival. METHODS: Retrospective analysis was performed on 241 LT recipients with AALD as either a primary or secondary indication for LT (2006-2015). RESULTS: Patients with <6 months of alcohol abstinence had significantly increased cumulative incidence for alcohol relapse compared to those with >6 months of abstinence (P = .0041, Log-Rank). We identified four variables to predict harmful alcohol relapse post-LT: age at LT, non-alcohol-related criminal history, pre-LT abstinence period (Ref >6 months of alcohol abstinence), and drinks per day (Ref <10 drinks/day). Area under the curve (AUC) for the final model was 0.79 (95% CI: 0.68-0.91). Our multivariable model was evaluated with internal cross-validation; random sampling of the study subjects 100 times yielded a median C statistic of 75 (±SD 0.097) and accuracy of 91 (±SD 0.026). The four-variable model served to form the harmful alcohol use post-LT (HALT) score. Graft survival remained significantly lower in patients with <6 months of pre-LT alcohol abstinence and those with blue-collar jobs. CONCLUSION: The HALT score identifies LT candidates with AALD at significant risk for alcohol relapse, potentially guiding transplant centers for pre- and post-LT interventions for improved patient outcomes.

Concordance of the Resting State Networks in Typically Developing, 6-to 7-Year-Old Children and Healthy Adults.

Though fairly well-studied in adults, less is known about the manifestation of resting state networks (RSN) in children. We examined the validity of RSN derived in an ethnically diverse group of typically developing 6- to 7-year-old children. We hypothesized that the RSNs in young children would be robust and would reliably show significant concordance with previously published RSN in adults. Additionally, we hypothesized that a smaller sample size using this robust technique would be comparable in quality to pediatric RSNs found in a larger cohort study. Furthermore, we posited that compared to the adult RSNs, the primary sensorimotor and the default mode networks (DMNs) in this pediatric group would demonstrate the greatest correspondence, while the executive function networks would exhibit a lesser degree of spatial overlap. Resting state functional magnetic resonance images (rs-fMRI) were acquired in 18 children between 6 and 7 years recruited from an ethnically diverse population in the Mid-South region of the United States. Twenty RSNs were derived using group independent component analysis and their spatial correspondence with previously published adult RSNs was examined. We demonstrate that the rs-fMRI in this group can be deconstructed into the fundamental RSN as all the major RSNs previously described in adults and in a large sample that included older children can be observed in our sample of young children. Further, the primary visual, auditory, and somatosensory networks, as well as the default mode, and frontoparietal networks derived in this group exhibited a greater spatial concordance with those seen in adults. The motor, temporoparietal, executive control, dorsal attention, and cerebellar networks in children had less spatial overlap with the corresponding RSNs in adults. Our findings suggest that several salient RSNs can be mapped reliably in small and diverse pediatric cohort within a narrow age range and the evolution of these RSNs can be studied reliably in such groups during early childhood and adolescence.