Background Recent studies have demonstrated the presence of associations between metabolic syndrome and the onset of nonalcoholic fatty liver disease (NAFLD). Metabolic syndrome, in turn, has been found to be linked to high serum uric acid to HDL-cholesterol ratios (UHR). However, the relationship between UHR values and the occurrence of NAFLD in non-obese individuals remains unknown. The present study aimed to examine the possible correlation between UHR values and NAFLD onset among a non-obese Chinese population without dyslipidemia, as well as comparing the predictive value of UHR versus other NAFLD onset predictors. Methods A total of 9837 non-obese patients, with normal blood lipid levels, were included in a 5-year retrospective cohort study, and the onset of NAFLD in these patients was diagnosed by liver ultrasound. Results Out of the 9837 patients, 855 were diagnosed with NAFLD during the 5-year follow-up period, for an overall total prevalence of 8.7% at the end of the study period. Across quintiles 1, 2, 3, 4 and 5 of UHR (respectively, ratios of ≤ 120.88, 120.89–154.01, 154.02–189.91, 189.92–240.46, and ≥ 240.47), the prevalence of NAFLD among the patients increased from 2.4%, 5%, 7.9%, 10.3%, and 17.8%, respectively. After adjustments for age, gender, liver and kidney functional markers, as well as metabolic indicators, multivariate Cox proportional hazard regression analysis demonstrated that the hazard ratio (HR) was the highest in quintile 5, at 1.76 (1.12–2.75), and the lowest in quintile 1. The area under the curve (AUC) for UHR (0.690) was higher than that for serum uric acid (UA, 0.666) and HDL-C (0.636), suggesting the predictive ability of UHR for NAFLD onset was better than either alone. This finding was further supported by the presence of an independent association between UHR and NAFLD, even within the normal range of UA and HDL-C; the HR (95% confidence interval, CI) for NAFLD was 1.002 (1.000–1.004). Compared with other significant predictors, AUC for UHR (0.67) was similar to that of low-density lipoprotein cholesterol (LDL-C)/high-density lipoprotein cholesterol (HDL-C, 0.68), non-high-density lipoprotein cholesterol (NHDL-C)/HDL-C (0.68) and alanine aminotransferase (ALT)/aspartate aminotransferase (AST) ratios (0.7), and was higher than that of LDL-C (0.63), remnant cholesterol (RC,0.59), and albumin (ALB)/alkaline phosphatase (ALP) ratio (0.61). The sensitivity of UHR (71%) was the highest among all indicators. In the subgroup with ALT < 40U/L, the AUC for UHR was 0.70, which was the highest among all predictors; among ALT > 40U/L, UHR was able to predict the occurrence of NAFLD (AUC = 0.61, p = 0.007), which was not the case for RC (P = 0.441), ALB/ALP (P = 0.419), and ALT/AST (P = 0.159). Conclusions UHR serve as an inexpensive and reliable predictor of NAFLD onset in non-obese Chinese people with normal blood lipid levels, allowing for identification of individuals at high risk for NAFLD.

Background: To evaluate the accuracy of two-dimensional (2D) shear wave elastography (SWE), develop and validate a novel prognostic model in predicting acute-on-chronic liver failure (ACLF) development in patients with acutely decompensated hepatitis B cirrhosis. Methods: This prospective cohort study enrolled 221 patients in the First Affiliated Hospital of Nanchang University from September 2019 to January 2021, and randomly assigned them to the derivation and validation cohorts (7:3 ratio). Ultrasound, 2D SWE, clinical and laboratory data were collected, and outcome (ACLF developed) was recorded during a 90-day follow-up period. We evaluated the ability of 2D SWE to predict the outcome, developed a model for predicting ACLF development in the derivation cohort, and assessed the model in the validation cohort. Results: 2D SWE values were significantly higher in patients with ACLF development (P<0.05). The accuracy of 2D SWE in predicting the outcome was better than that of serum parameters of liver fibrosis (all P<0.05). The SWE model for ACLF development had good calibration and discrimination [concordance index (C-index): 0.855 and 0.840 respectively] in derivation and validation cohorts, outperforming serum prognostic scores (all P<0.05). Conclusions: The SWE model, superior to serum prognostic scores in predicting ACLF development, could be a noninvasive tool to guide the individual management of patients with acutely decompensated hepatitis B cirrhosis.

Background Non-alcoholic fatty liver disease (NAFLD) has been associated with type 2 diabetes, but its relationship with pre-diabetes is still unknown. This study aims to determine whether pre-diabetes is associated with NAFLD, followed by establishing a NAFLD predictive nomogram for lean Chinese pre-diabetics with normal blood lipids. Methods Datasets from 3 previous studies, 1 (2774 pre-diabetics with normal blood lipids for training, 925 for validation), 2 (546 for longitudinal internal validation, post-5-year follow-up), and 3 (501 from another institution for external validation), were used. Kaplan-Meier determined cumulative NAFLD hazard, and least absolute shrinkage and selection operator regression analysis uncovered its risk factors. Multivariate logistic regression analysis constructed the nomogram, followed by validation with receiver operating characteristic curve, calibration plot, and decision curve analyses. Results NAFLD incidence increased with diabetes progression, and pre-diabetics had higher cumulative risk versus non-diabetics, even for lean individuals with normal blood lipids. Six risk factors were identified: body mass index, total cholesterol, alanine aminotransferase:aspartate aminotransferase, triglyceride:high density lipoprotein cholesterol, fasting blood glucose and γ-glutamyl-transferase. The nomogram yielded areas under the curve of 0.808, 0.785, 0.796 and 0.832, for respectively, training, validation, longitudinal internal validation, and external validation, which, along with calibration curve values of p = 0.794, 0.875, 0.854 and 0.810 for those 4 datasets and decision curve analyses, validated its clinical utility. Conclusions Lean pre-diabetic Chinese with normal blood lipids have higher NAFLD risk versus non-diabetics. The nomogram is able to predict NAFLD among such individuals, with high discrimination, enabling its use for early detection and intervention.

Background This study was designed to study the serum metabolites of patients with liver failure. Material/Methods The study included 50 patients with liver failure, 30 patients with chronic hepatitis B treated with an artificial liver, 11 patients with an artificial liver, and 32 healthy controls. Clinical data were recorded, and blood samples were analyzed by gas chromatography–mass spectrometry (GC-MS). The random forest algorithm was used to construct a multidimensional scale map to preliminarily reflect the differences between samples. The data were then analyzed to obtain the correlation of different variables among samples, from which the differential metabolites were screened. Results Thirty-five metabolites were identified by GC-MS. There were significant differences in serum metabolites levels before and after treatment in the liver failure group and in the chronic hepatitis group, healthy control group, and artificial liver group. Different metabolites were screened according to the importance of different variables among samples. Significant differences were found between the liver failure group, the chronic hepatitis group, and the healthy control group. In addition, there were significant differences in the liver group before and after treatment with an artificial liver, including differences in boric acid, 2-(methoxyamino)-propionic acid, glycine, l-methionine, aminopropionic acid, glyceryl monostearate, cholesterol, and other substances. Conclusions A variety of differences in metabolites were found in each group, some of which revealed possible metabolic pathways leading to differences between groups. Blood metabolomics analysis has great potential in real-time dynamic monitoring of liver failure and evaluation of artificial liver therapy.