AIM: To identify the association of baseline GGT level and QRISK2 score among patients with biopsy-proven nonalcoholic fatty liver disease (NAFLD).
METHODS: This was a retrospective study involving 1535 biopsy-proven NAFLD patients from 10 Asian centers in 8 countries using data collected by the Gut and Obesity in Asia (referred to as "GO ASIA") workgroup. All patients with available baseline GGT levels and all 16 variables for the QRISK2 calculation (QRISK2-2017; developed by researchers at the United Kingdom National Health Service; https://qrisk.org/2017/; 10-year cardiovascular risk estimation) were included and compared to healthy controls with the same age, sex, and ethnicity. Relative risk was reported. QRISK2 score > 10% was defined as the high-CVD-risk group. Fibrosis stages 3 and 4 (F3 and F4) were considered advanced fibrosis.
RESULTS: A total of 1122 patients (73%) had complete data and were included in the final analysis; 314 (28%) had advanced fibrosis. The median age (interquartile range [IQR]) of the study population was 53 (44-60) years, 532 (47.4%) were females, and 492 (43.9%) were of Chinese ethnicity. The median 10-year CVD risk (IQR) was 5.9% (2.6-10.9), and the median relative risk of CVD over 10 years (IQR) was 1.65 (1.13-2.2) compared to healthy individuals with the same age, sex, and ethnicity. The high-CVD-risk group was significantly older than the low-risk group (median [IQR]: 63 [59-67] vs 49 [41-55] years; P < 0.001). Higher fibrosis stages in biopsy-proven NAFLD patients brought a significantly higher CVD risk (P < 0.001). Median GGT level was not different between the two groups (GGT [U/L]: Median [IQR], high risk 60 [37-113] vs low risk 66 [38-103], P = 0.56). There was no correlation between baseline GGT level and 10-year CVD risk based on the QRISK2 score (r = 0.02).
CONCLUSION: The CVD risk of NAFLD patients is higher than that of healthy individuals. Baseline GGT level cannot predict CVD risk in NAFLD patients. However, advanced fibrosis is a predictor of a high CVD risk.
METHODS: In a cross-sectional study of 379 hemodialysis patients, FibroTouch transient elastography was performed on all patients. Erythropoeitin resistance index (ERI) was used to measure the responsiveness to ESA. Patients in the highest tertile of ERI were considered as having ESA hypo-responsiveness.
RESULTS: The percentage of patients with ESA hypo-responsiveness who had MAFLD was lower than patients without ESA hypo-responsiveness. FIB-4 index was significantly higher in ESA hypo-responsive patients. In multivariate analysis, female gender (aOR = 3.4, 95% CI = 1.9-6.2, p < 0.001), dialysis duration ≥50 months (aOR = 1.8, 95% CI = 1.1-2.9, p < 0.05), elevated waist circumference (aOR = 0.4, 95% CI = 0.2-0.8, p = 0.005), low platelet (aOR = 2.6, 95% CI 1.3-5.1, p < 0.01), elevated total cholesterol (aOR = 0.5, 95% CI 0.3-0.9, p < 0.05) and low serum iron (aOR = 3.8, 95% CI = 2.3-6.5, p < 0.001) were found to be independent factors associated with ESA hypo-responsiveness. Neither MAFLD nor advanced liver fibrosis was independently associated with ESA hypo-responsiveness. However, every 1 kPA increase in LSM increased the chance of ESA-hyporesponsiveness by 13% (aOR = 1.1, 95% CI = 1.0-1.2, p = 0.002) when UAP and LSM were used instead of presence of MAFLD and advanced liver fibrosis, respectively.
CONCLUSION: MAFLD and advanced liver fibrosis were not independently associated with ESA hypo-responsiveness. Nevertheless, higher FIB-4 score in ESA hypo-responsive group and significant association between LSM and ESA hypo-responsiveness suggest that liver fibrosis may be a potential clinical marker of ESA hypo-responsiveness.
METHODS: This is a single-centre prospective study of a well-characterized cohort of MAFLD patients who underwent liver biopsy and followed every 6-12 months for adverse clinical outcomes.
RESULTS: The data for 202 patients were analyzed [median age 55.0 (48.0-61.3) years old; male, 47.5%; obese, 88.6%; diabetes mellitus, 71.3%; steatohepatitis, 76.7%; advanced fibrosis, 27.2%]. The median follow-up interval was 7 (4-8) years. The cumulative incidence of liver-related events, cardiovascular events, malignancy and mortality was 0.43, 2.03, 0.60 and 0.60 per 100 person-years of follow-up, respectively. Liver-related events were only seen in patient with advanced fibrosis at 9.1% vs 0% in patient without advanced liver fibrosis (p liver-related events among patients with advanced fibrosis was 1.67 per 100 person-years of follow-up. When further stratified to bridging fibrosis and cirrhosis, the cumulative incidence of liver-related events was 1.47 and 3.85 per 100 person-years of follow-up, respectively. Advanced fibrosis was not significantly associated with cardiovascular events, malignancy or mortality. The cumulative incidence of liver-related events, cardiovascular events, malignancy and mortality were not significantly different between patients with and without steatohepatitis and between obese and non-obese patients. However, liver-related events were only seen among obese patients.
CONCLUSION: Overall, the cumulative incidence of liver-related event is low in patients with MAFLD, but it is much higher among those with advanced fibrosis. However, there is a relatively high cumulative incidence of cardiovascular event among patients with MAFLD.
AIMS: We developed and validated MAFLD fibrosis score (MFS) for identifying advanced fibrosis (≥F3) among MAFLD patients.
METHODS: This cross-sectional, multicentre study consecutively recruited MAFLD patients receiving tertiary care (Malaysia as training cohort [n = 276] and Hong Kong and Wenzhou as validation cohort [n = 431]). Patients completed liver biopsy, vibration-controlled transient elastography (VCTE), and clinical and laboratory assessment within 1 week. We used machine learning to select 'highly important' predictors of advanced fibrosis, followed by backward stepwise regression to construct MFS formula.
RESULTS: MFS was composed of seven variables: age, body mass index, international normalised ratio, aspartate aminotransferase, gamma-glutamyl transpeptidase, platelet count, and history of type 2 diabetes. MFS demonstrated an area under the receiver-operating characteristic curve of 0.848 [95% CI 0.800-898] and 0.823 [0.760-0.886] in training and validation cohorts, significantly higher than aminotransferase-to-platelet ratio index (0.684 [0.603-0.765], 0.663 [0.588-0.738]), Fibrosis-4 index (0.793 [0.735-0.854], 0.737 [0.660-0.814]), and non-alcoholic fatty liver disease fibrosis score (0.785 [0.731-0.844], 0.750 [0.674-0.827]) (DeLong's test p
AIMS: We evaluated the performance of machine learning (ML) and non-patented scores for ruling out SF among NAFLD/MASLD patients.
METHODS: Twenty-one ML models were trained (N = 1153), tested (N = 283), and validated (N = 220) on clinical and biochemical parameters of histologically-proven NAFLD/MASLD patients (N = 1656) collected across 14 centres in 8 Asian countries. Their performance for detecting histological-SF (≥F2fibrosis) were evaluated with APRI, FIB4, NFS, BARD, and SAFE (NPV/F1-score as model-selection criteria).
RESULTS: Patients aged 47 years (median), 54.6% males, 73.7% with metabolic syndrome, and 32.9% with histological-SF were included in the study. Patients with SFvs.no-SF had higher age, aminotransferases, fasting plasma glucose, metabolic syndrome, uncontrolled diabetes, and NAFLD activity score (p 140) was next best in ruling out SF (NPV of 0.757, 0.724 and 0.827 in overall, test and validation set).
CONCLUSIONS: ML with clinical, anthropometric data and simple blood investigations perform better than FIB-4 for ruling out SF in biopsy-proven Asian NAFLD/MASLD patients.
OBJECTIVES: To determine the prevalence and characteristics of NAFLD in individuals with metabolically healthy obesity.
SETTING: A tertiary, academic, referral hospital.
METHODS: All patients who underwent bariatric surgery with intraoperative liver biopsy from 2008 to 2015 were identified. Patients with preoperative hypertension, dyslipidemia, or prediabetes/diabetes were excluded to identify a cohort of metabolically healthy obesity patients. Liver biopsy reports were reviewed to determine the prevalence of NAFLD.
RESULTS: A total of 270 patients (7.0% of the total bariatric surgery patients) met the strict inclusion criteria for metabolically healthy obesity. The average age was 38 ± 10 years and the average body mass index was 47 ± 7 kg/m2. Abnormal alanine aminotransferase (>45 U/L) and asparate aminotransferase levels (>40 U/L) were observed in 28 (10.4%) and 18 (6.7%) patients, respectively. A total of 96 (35.5%) patients had NAFLD with NALFD Activity Scores 0 to 2 (n = 61), 3 to 4 (n = 25), and 5 to 8 (n = 10). A total of 62 (23%) patients had lobular inflammation, 23 (8.5%) had hepatocyte ballooning, 22 (8.2%) had steatohepatitis, and 12 (4.4%) had liver fibrosis.
CONCLUSION: Even with the use of strict criteria to eliminate all patients with any metabolic problems, a significant proportion of metabolically healthy patients had unsuspected NAFLD. The need and clinical utility of routine screening of obese patients for fatty liver disease and the role of bariatric surgery in the management of NAFLD warrants further investigation.