ObjectiveTo investigate the clinical features and outcomes of recompensation in patients with autoimmune hepatitis （AIH）-related decompensated cirrhosis， to identify independent predictive factors， and to construct a nomogram prediction model for the probability of recompensation. MethodsA retrospective cohort study was conducted among the adult patients with AIH-related decompensated cirrhosis who were admitted to The Fifth Medical Center of PLA General Hospital from January 2015 to August 2023 （n=211）. The primary endpoint was achievement of recompensation， and the secondary endpoint was liver-related death or liver transplantation. According to the outcome of the patients at the end of the follow-up， the patients were divided into the recompensation group （n=16） and the persistent decompensation group（n=150）.The independent-samples t test was used for comparison of normally distributed continuous data with homogeneity of variance， and the Mann-Whitney U rank sum test was used for comparison of non-normally distributed continuous data with heterogeneity of variance； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups； the Kaplan-Meier method was used for survival analysis； the Cox proportional-hazards regression model was used to identify independent predictive factors， and a nomogram model was constructed and validated. ResultsA total of 211 patients were enrolled， with a median age of 55.0 years and a median follow-up time of 44.0 months， and female patients accounted for 87.2%. Among the 211 patients， 61 （with a cumulative proportion of 35.5%） achieved recompensation. Compared with the persistent decompensation group， the recompensation group had significantly higher white blood cell count， platelet count （PLT）， total bilirubin （TBil）， alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， total bile acid， prothrombin time， international normalized ratio （INR）， SMA positive rate， Model for End-Stage Liver Disease （MELD） score， Child-Pugh score， and rate of use of glucocorticoids （all P0.05）， as well as significantly lower age at baseline， number of complications， and death/liver transplantation rate （all P0.05）. At 3 and 12 months after treatment， the recompensation group had continuous improvements in AST， TBil， INR， IgG， MELD score， and Child-Pugh score， which were significantly lower than the values in the persistent decompensation group （all P0.05）， alongside with continuous increases in PLT and albumin， which were significantly higher than the values in the persistent decompensation group （P0.05）. The multivariate Cox regression analysis showed that baseline ALT （hazard ratio ［HR］=1.067， 95% confidence interval ［CI］： 1.010 — 1.127， P=0.021）， IgG （HR=0.463，95%CI：0.258 — 0.833， P=0.010）， SMA positivity （HR=3.122，95%CI：1.768 — 5.515， P0.001）， and glucocorticoid therapy （HR=20.651，95%CI：8.744 — 48.770， P0.001） were independent predictive factors for recompensation， and the nomogram model based on these predictive factors showed excellent predictive performance （C-index=0.87，95%CI：0.84 — 0.90）. ConclusionAchieving recompensation significantly improves clinical outcomes in patients with AIH-related decompensated cirrhosis. Baseline SMA positivity， a high level of ALT， a low level of IgG， and corticosteroid therapy are independent predictive factors for recompensation. The predictive model constructed based on these factors can provide a basis for decision-making in individualized clinical management.

Cognitive impairment is one of the important clinical manifestations in depression. The particularly vulnerable cognition domains included executive function, attention, memory, and processing speed. Depression with cognitive impairment is not only a predictor of poor efficacy, but also closely related to dementia. Previous studies have suggested that multiple physiological mechanisms may be altered between depression and cognitive impairment. With the rapid development of neuroimaging technology, resting state functional magnetic resonance imaging has been widely used to explore the neurobiological mechanisms of depression and cognitive impairment. After reviewing the resting-state functional MRI manifestations of the comorbidity, it was found that the default mode network, cognitive control network, and salience network were activated or weakened in the brain. In addition, the inter-network functional connectivity was altered with the co-existence of impairment and compensation. The aforementioned changes of brain function are expected to be the therapeutic targets for depression with cognitive dysfunction.

Objective:To study the relationship between somatization symptoms and body mass index (BMI), sleep and cognitive function in patients with depression.Methods:A total of 119 patients with depression were selected from January to December in 2019.According to the score of patient health questionnaire-15(PHQ15), they were divided into mild somatization group ( n=75) and moderate severe somatization group ( n=44). Hamilton depression scale-24(HAMD-24), patient health questionnaire-15, Pittsburgh sleep quality index(PSQI) and Montreal cognitive assessment(MoCA) were used to evaluate all subjects.SPSS 23.0 software was used for data analysis.Independent sample t-test was used to compare BMI, sleep and cognitive function scores between the two groups.Pearson correlation analysis was used to study the correlation between somatization symptoms and sleep quality and cognitive function. Results:There were significant differences in BMI((21.70±3.09)kg/m 2, (23.31±3.51)kg/m 2), PSQI((12.56±4.37), (14.37±3.72)), sleep quality(1.87±0.86), (2.21±0.80)), sleep disorder ((1.24±0.59), (1.65±0.53))and daytime dysfunction((2.45±0.81), (2.77±0.48)) between the two groups ( t=-3.783--2.133, all P<0.05), but no difference was found in cognition ( P>0.05). Correlation analysis showed that after controlling HAMD, PHQ-15 was positively correlated with PSQI, sleep quality, sleep disorder, daytime dysfunction and language score in MoCA ( r=0.205-0.298, all P<0.05). Conclusion:The severity of somatization in patients with depression is related to BMI, sleep quality, sleep disorder, daytime dysfunction and language function, suggesting that they may play an important role in the pathogenesis of depression with somatization.