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BACKGROUND: Recently, a group of hepatologists proposed to rename non-alcoholic fatty liver disease (NAFLD) as metabolic associated fatty liver disease (MAFLD) with modified diagnostic criteria. It is important to note, however, that there are some differences between the diagnostic criteria used for NAFLD and MAFLD. Since the research on MAFLD is just beginning, however, evidence on its incidence and prevalence in the general population and in speciï¬c subpopulations remains limited. AIM: To assess epidemiology of fatty liver in new definition and compare MAFLD with NAFLD. Exploring risk factors of MAFLD individuals. METHODS: This was a retrospective, cross-sectional study. A total of 85242 adults were selected from the Chinese health management database in 2017-2022. The data of general information, laboratory indicators, lifestyle management and psychological status were obtained. MAFLD was diagnosed as ultrasound diagnosis of fatty liver and at least one between these three conditions: Overweight/obesity, type 2 diabetes mellitus (T2DM) or metabolic dysregulation. Metabolic factors were not considered in NAFLD diagnosis standard. The clinical characteristics of MAFLD and NAFLD were analysed using descriptive statistics. Continuous variables normally distributed were expressed as means ± SD. Categorical variables were expressed as frequencies and proportions. Binary logistic regression was used to determine risk factors of the MAFLD. RESULTS: The prevalence of MAFLD and NAFLD was 40.5% and 31.0%, respectively. The MAFLD or NAFLD population is more likely to be older (M: 47.19 ± 10.82 vs 43.43 ± 11.96; N: 47.72 ± 11.17 vs 43.71 ± 11.66), male (M: 77.21% vs 44.43%; N: 67.90% vs 53.12%) and high body mass index (M: 26.79 ± 2.69 vs 22.44 ± 2.48; N: 26.29 ± 2.84 vs 23.29 ± 3.12) than the non-MAFLD or non-MAFLD population. In multivariate analysis, general information (e.g., ≥ 2 metabolic abnormalities OR = 3.38, (95%CI: 2.99-3.81), P < 0.001; diastolic blood pressure OR = 1.01, (95%CI: 1.00-1.01), P = 0.002), laboratory results [e.g.,total bilirubin (TBIL) OR = 0.98, (95%CI: 0.98-0.99), P < 0.001; serum uric acid(SUA) OR = 1.01, (95%CI: 1.01-1.01), P < 0.001], and lifestyle factors [e.g., drink beverage OR = 0.32, (95%CI: 0.17-0.63), P = 0.001] were influence factors for MAFLD. Our study results offer new insight into potential risk factors associated with fatty liver disease, including SUA, TBIL and creatinine, all of which are related to chronic renal disease (CKD). CONCLUSION: MAFLD is more prevalent than NAFLD, with two-fifths of individuals meeting the diagnosis criteria. MAFLD and NAFLD populations have different clinical characteristics. CKD may be related with MAFLD.
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Chemotherapy-induced nausea and vomiting (CINV) is a common side effect of cancer treatment. The factors influencing CINV in breast cancer patients remain unclear. In this study, we developed a nomogram for predicting the occurrence of CINV in this group using prospective clinical data. We pooled data from multiple studies which focused on the emetogenic chemotherapy. Then, we collected 334 breast cancer patients at Hunan Cancer Hospital (training set) to analyze the demographic and clinical variables. Using multivariate logistic regression, we identified the five significant factors that were associated with CINV: history of CINV, chemotherapy regimen, chemotherapy cycle, metastasis, and symptoms of distress. Then, we construct a prediction nomogram. The external validation set comprised an additional 66 patients. The reliability of the nomogram was assessed by bootstrap resampling. The C-index was 0.78 (95% confidence interval [CI], 0.73-0.85) for the training set and 0.74 (95% CI, 0.62-0.85) for the validation set. Calibration curves showed good concordance between predicted and actual occurrence of CINV. In conclusions, our nomogram model can reliably predict the occurrence of CINV in breast cancer patients based on five significant variables, which might be useful in clinical decision-making.