Background: The triglyceride–glucose index (TyG) and a combination of body mass index (BMI) and waist circumference (WC) have been proposed as predictive scores for liver steatosis (LS). The aim of this study was to determine the diagnostic accuracy of these indices compared with controlled attenuation parameters (CAPs) and other predictive scores of LS. Methods: A retrospective analysis of patients who attended a check-up unit in 2021 was performed. LS was determined by CAP. Anthropometric and biochemical parameters for calculating TyG, TyG-BMI, TyG-WC, fatty liver index, and hepatic steatosis index were obtained. ROC curve was used to establish the best cut-off point of each TyG index for LS detection. The accuracy was determined for all patients, as well as for overweight and diabetic patients. Results: Medical records of 855 patients with a median age of 48 [IQR, 44–54] years and a BMI of 25.7 [IQR 23.4–28.1] kg/m² were included. According to CAP, LS prevalence was 31.8% (n = 272). TyG-BMI and TyG-WC show better AUCs compared with CAP (0.82, 0.81), FLI (0.96, both), and HSI (0.93, 0.85). For diabetic patients, TyG-WC shows an AUC of 0.70. Meanwhile, TyG-BMI shows better accuracy (0.75) compared with CAP. Conclusions: TyG-BMI and TyG-WC showed a superior predictive accuracy for detecting LS compared with the TyG index.

Background: Metabolic dysfunction–associated steatotic liver disease currently represents the leading cause of chronic liver disease worldwide. FibroScan and iLivTouch are 2 devices that employ similar principles to estimate liver steatosis and fibrosis, although few studies have directly compared their results. Aim: To evaluate the concordance of 2 transient elastography devices for the estimation of liver steatosis and fibrosis. Methods: A prospective study was conducted. Each participant underwent liver elastography with both devices consecutively under standardized conditions. Clinical, anthropometric, and biochemical variables were collected. The diagnostic accuracy of iLivTouch was calculated using FibroScan and noninvasive scores as references. Results: A total of 1004 patients were enrolled, with a median body mass index of 25.7 kg/m ² [IQR=23.6–28.7]. Median of attenuation values was 250 dB/m [IQR=214–291] with FibroScan, 262 dB/m [IQR=239–310] with iLivTouch. Median liver stiffness measurements were 4.1 kPa [IQR=3.4–4.8] for FibroScan and 6.2 kPa [IQR=5.5–7.1] for iLivTouch. Bland–Altman analysis revealed mean differences of −19.45±49.62 dB/m for steatosis and −2.43±2.51 kPa for stiffness. Using FibroScan (>269 dB/m) as the reference, iLivTouch ≥244 dB/m demonstrated 90% sensitivity for detecting liver steatosis. The correlation between the FAST scores of the 2 devices was very strong (rho=0.90, p ≤0.0001). Conclusion: iLivTouch serves as an effective alternative to assess liver fibrosis and steatosis in the general population, including overweight and obese individuals.

Background/Objectives: In the last decade, the prevalence of metabolic-associated fatty liver disease (17–46%) and non-alcoholic fatty pancreas disease (NAFPD) (16–33%) has increased due to their association with obesity, both predictors of early atherosclerosis and metabolic risk. Computed tomography (CT) has been proposed as a diagnostic method. Currently, the factors associated with NAFPD have not been fully described. The aim of this study is to describe the prevalence and association of NAFPD and liver steatosis in patients with very high cardiovascular risk. Methods: A retrospective evaluation was conducted on the medical records of patients classified as very high cardiovascular risk who had undergone a CT scan. NAFPD was determined by the difference in pancreatic and splenic attenuation (−1.9), while liver steatosis was identified by hepatic attenuation <40. Bivariate and multivariate analyses were performed to determine the independent factors associated with NAFPD. Results: 169 medical records were collected; 68.6% (n = 116) were men, with a median age of 70 [IQR 61–78] years and 25.8 [IQR 23.7–28.7] kg/m² of body mass index. According to the CT scans, 80.5% (n = 136) presented NAFPD, 24.3% (n = 41) had liver steatosis, and 21.3% (n = 36) had both. In the multivariate analysis, liver steatosis, abnormal levels of aspartate aminotransferase, and being overweight were independent factors associated with NAFPD. Conclusions: In a very high cardiovascular-risk population, the prevalence of NAFPD is high, and it is independently associated with the presence of liver steatosis.