METHODS: We performed a retrospective analysis of data from 759 patients with biopsy-proven NAFLD (24% with advanced fibrosis), seen at 10 centers in 9 countries in Asia, from 2006 through 2018. By using liver biopsies as the reference standard, we calculated percentages of misclassifications and indeterminate or discordant results from assessments made based on fibrosis scores (NAFLD fibrosis score [NFS] or Fibrosis-4 score) and liver stiffness measurements (LSMs), alone or in combination. The analysis was repeated using randomly selected subgroups with a different prevalence of advanced fibrosis (histologic fibrosis stage ≥F3).
RESULTS: In groups in which 3.7% and 10% of patients had advanced fibrosis, a 2-step approach (using the NFS followed by LSM only for patients with indeterminate or high NFS) and using a gray zone of 10 to 15 kPa for LSM, produced indeterminate or discordant results for 6.9% of patients and misclassified 2.7% of patients; only 25.6% of patients required LSM. In the group in which 10% of patients had advanced fibrosis, the same approach produced indeterminate or discordant results for 7.9% of patients and misclassified 6.6% of patients; only 27.4% of patients required LSM. In groups in which 24% and 50% of patients had advanced fibrosis, using LSM ≥10 kPa alone for the diagnosis of advanced fibrosis had the highest accuracy and misclassified 18.1% and 18.3% of patients, respectively. These results were similar when the Fibrosis-4 score was used in place of NFS.
CONCLUSIONS: In a retrospective analysis, we found that a 2-step approach using fibrosis scores followed by LSM most accurately detects advanced fibrosis in populations with a low prevalence of advanced fibrosis. However, LSM ≥10 kPa identifies patients with advanced fibrosis with the highest level of accuracy in populations with a high prevalence of advanced fibrosis.
AIM: To study factors associated with nonalcoholic steatohepatitis (NASH) and advanced fibrosis, and medical treatment of biopsy-proven nonalcoholic fatty liver disease (NAFLD) patients.
METHODS: Retrospective study of biopsy-proven NAFLD patients from centres in the GO ASIA Workgroup. Independent factors associated with NASH and with advanced fibrosis on binary logistic regression analyses in a training cohort were used for the development of their corresponding risk score, which were validated in a validation cohort.
RESULTS: We included 1008 patients from nine centres across eight countries (NASH 62.9%, advanced fibrosis 17.2%). Independent predictors of NASH were body mass index ≥30 kg/m2 , diabetes mellitus, dyslipidaemia, alanine aminotransferase ≥88 U/L and aspartate aminotransferase ≥38 U/L, constituting the Asia Pacific NASH risk score. A high score has a positive predictive value of 80%-83% for NASH. Independent predictors of advanced fibrosis were age ≥55 years, diabetes mellitus and platelet count <150 × 109 /L, constituting the Asia-Pacific NAFLD advanced fibrosis risk score. A low score has a negative predictive value of 95%-96% for advanced fibrosis. Only 1.7% of patients were referred for structured lifestyle program, 4.2% were on vitamin E, and 2.4% were on pioglitazone.
CONCLUSIONS: More severe liver disease can be suspected or ruled out based on factors identified in this study. Utilisation of structured lifestyle program, vitamin E and pioglitazone was limited despite this being a cohort of biopsy-proven NAFLD patients with majority of patients having NASH.
METHODS: We abstracted the data of 1008 patients with NAFLD from nine centers across eight countries. Characteristics of elderly and non-elderly patients with NAFLD were compared using 1:3 sex-matched analysis.
RESULTS: Of the 1008 patients, 175 were elderly [age 64 (62-67) years], who were matched with 525 non-elderly patients [46 (36-54) years]. Elderly patients were more likely to have advanced fibrosis (35.4% vs. 13.3%; p
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: 1812 biopsy-proven NAFLD patients across nine countries in Asia assessed between 2006 and 2019 were pooled into a curated clinical registry. Demographic, metabolic and histological differences between non-obese and obese NAFLD patients were evaluated. The performance of Fibrosis-4 index for liver fibrosis (FIB-4) and NAFLD fibrosis score (NFS) to identify advanced liver disease across the varying obesity subgroups was compared. A random forest analysis was performed to identify novel predictors of fibrosis and steatohepatitis in non-obese patients.
FINDINGS: One-fifth (21.6%) of NAFLD patients were non-obese. Non-obese NAFLD patients had lower proportions of NASH (50.5% vs 56.5%, p = 0.033) and advanced fibrosis (14.0% vs 18.7%, p = 0.033). Metabolic syndrome in non-obese individuals was associated with NASH (OR 1.59, 95% CI 1.01-2.54, p = 0.047) and advanced fibrosis (OR 1.88, 95% CI 0.99-3.54, p = 0.051). FIB-4 performed better than the NFS score (AUROC 81.5% vs 73.7%, p
METHODS: We recruited ACLF patients between 2009 and 2020 from APASL-ACLF Research Consortium (AARC). Their clinical data, investigations and organ involvement were serially noted for 90-days and utilized for AI modelling. Data were split randomly into train and validation sets. Multiple AI models, MELD and AARC-Model, were created/optimized on train set. Outcome prediction abilities were evaluated on validation sets through area under the curve (AUC), accuracy, sensitivity, specificity and class precision.
RESULTS: Among 2481 ACLF patients, 1501 in train set and 980 in validation set, the extreme gradient boost-cross-validated model (XGB-CV) demonstrated the highest AUC in train (0.999), validation (0.907) and overall sets (0.976) for predicting 30-day outcomes. The AUC and accuracy of the XGB-CV model (%Δ) were 7.0% and 6.9% higher than the standard day-7 AARC model (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.
METHODS: ACLF patients recruited from the APASL-ACLF Research Consortium (AARC) were followed up till 30 days, death or transplantation, whichever earlier. Clinical details, including dynamic grades of HE and laboratory data, including ammonia levels, were serially noted.
RESULTS: Of the 3009 ACLF patients, 1315 (43.7%) had HE at presentation; grades I-II in 981 (74.6%) and grades III-IV in 334 (25.4%) patients. The independent predictors of HE at baseline were higher age, systemic inflammatory response, elevated ammonia levels, serum protein, sepsis and MELD score (p
METHODS: Patients with AIH-ACLF without baseline infection/hepatic encephalopathy were identified from APASL ACLF research consortium (AARC) database. Diagnosis of AIH-ACLF was based mainly on histology. Those treated with steroids were assessed for non-response (defined as death or liver transplant at 90 days for present study). Laboratory parameters, AARC, and model for end-stage liver disease (MELD) scores were assessed at baseline and day 3 to identify early non-response. Utility of dynamic SURFASA score [- 6.80 + 1.92*(D0-INR) + 1.94*(∆%3-INR) + 1.64*(∆%3-bilirubin)] was also evaluated. The performance of early predictors was compared with changes in MELD score at 2 weeks.
RESULTS: Fifty-five out of one hundred and sixty-five patients (age-38.2 ± 15.0 years, 67.2% females) with AIH-ACLF [median MELD 24 (IQR: 22-27); median AARC score 7 (6-9)] given oral prednisolone 40 (20-40) mg per day were analyzed. The 90 day transplant-free survival in this cohort was 45.7% with worse outcomes in those with incident infections (56% vs 28.0%, p = 0.03). The AUROC of pre-therapy AARC score [0.842 (95% CI 0.754-0.93)], MELD [0.837 (95% CI 0.733-0.94)] score and SURFASA score [0.795 (95% CI 0.678-0.911)] were as accurate as ∆MELD at 2 weeks [0.770 (95% CI 0.687-0.845), p = 0.526] and better than ∆MELD at 3 days [0.541 (95% CI 0.395, 0.687), p 6, MELD score > 24 with SURFASA score ≥ - 1.2, could identify non-responders at day 3 (concomitant- 75% vs either - 42%, p
METHODS: Altogether 1021 patients were analyzed for the severity and organ failure at admission to determine transplant eligibility and 28 day survival with or without transplant.
RESULTS: The ACLF cohort [mean age 44 ± 12.2 years, males 81%) was of sick patients; 55% willing for LT at admission, though 63% of them were ineligible due to sepsis or organ failure. On day 4, recovery in sepsis and/or organ failure led to an improvement in transplant eligibility from 37% at baseline to 63.7%. Delay in LT up to 7 days led to a higher incidence of multiorgan failure (p
METHODS: Prospectively collected data of ACLF patients from APASL-ACLF Research Consortium (AARC) was analyzed for 30-day outcomes. The models evaluated at days 0, 4, and 7 of presentation for 30-day mortality were: AARC (model and score), CLIF-C (ACLF score, and OF score), NACSELD-ACLF (model and binary), SOFA, APACHE-II, MELD, MELD-Lactate, and CTP. Evaluation parameters were discrimination (c-indices), calibration [accuracy, sensitivity, specificity, and positive/negative predictive values (PPV/NPV)], Akaike/Bayesian Information Criteria (AIC/BIC), Nagelkerke-R2, relative prediction errors, and odds ratios.
RESULTS: Thirty-day survival of the cohort (n = 2864) was 64.9% and was lowest for final-AARC-grade-III (32.8%) ACLF. Performance parameters of all models were best at day 7 than at day 4 or day 0 (p 12 had the lowest 30-day survival (5.7%).
CONCLUSIONS: APASL-ACLF is often a progressive disease, and models assessed up to day 7 of presentation reliably predict 30-day mortality. Day-7 AARC model is a statistically robust tool for classifying risk of death and accurately predicting 30-day outcomes with relatively lower prediction errors. Day-7 AARC score > 12 may be used as a futility criterion in APASL-ACLF patients.
METHODS: We identified drugs as precipitants of ACLF among prospective cohort of patients with ACLF from the Asian Pacific Association of Study of Liver (APASL) ACLF Research Consortium (AARC) database. Drugs were considered precipitants after exclusion of known causes together with a temporal association between exposure and decompensation. Outcome was defined as death from decompensation.
RESULTS: Of the 3,132 patients with ACLF, drugs were implicated as a cause in 329 (10.5%, mean age 47 years, 65% men) and other nondrug causes in 2,803 (89.5%) (group B). Complementary and alternative medications (71.7%) were the commonest insult, followed by combination antituberculosis therapy drugs (27.3%). Alcoholic liver disease (28.6%), cryptogenic liver disease (25.5%), and non-alcoholic steatohepatitis (NASH) (16.7%) were common causes of underlying liver diseases. Patients with drug-induced ACLF had jaundice (100%), ascites (88%), encephalopathy (46.5%), high Model for End-Stage Liver Disease (MELD) (30.2), and Child-Turcotte-Pugh score (12.1). The overall 90-day mortality was higher in drug-induced (46.5%) than in non-drug-induced ACLF (38.8%) (P = 0.007). The Cox regression model identified arterial lactate (P < 0.001) and total bilirubin (P = 0.008) as predictors of mortality.
DISCUSSION: Drugs are important identifiable causes of ACLF in Asia-Pacific countries, predominantly from complementary and alternative medications, followed by antituberculosis drugs. Encephalopathy, bilirubin, blood urea, lactate, and international normalized ratio (INR) predict mortality in drug-induced ACLF.
METHODS: Data was collected from 13 Asian countries on patients with CLD, known or newly diagnosed, with confirmed COVID-19.
RESULTS: Altogether, 228 patients [185 CLD without cirrhosis and 43 with cirrhosis] were enrolled, with comorbidities in nearly 80%. Metabolism associated fatty liver disease (113, 61%) and viral etiology (26, 60%) were common. In CLD without cirrhosis, diabetes [57.7% vs 39.7%, OR = 2.1 (1.1-3.7), p = 0.01] and in cirrhotics, obesity, [64.3% vs. 17.2%, OR = 8.1 (1.9-38.8), p = 0.002] predisposed more to liver injury than those without these. Forty three percent of CLD without cirrhosis presented as acute liver injury and 20% cirrhotics presented with either acute-on-chronic liver failure [5 (11.6%)] or acute decompensation [4 (9%)]. Liver related complications increased (p
METHODS AND RESULTS: A multidisciplinary panel of fifty-two international experts comprising Hepatologists, Endocrinologists, Diabetologists, Cardiologists and Family Physicians from six continents (Asia, Europe, North America, South America, Africa and Oceania) participated in a formal Delphi survey and developed consensus statements on the association between MAFLD and the risk of CVD. Statements were developed on different aspects of CVD risk, ranging from epidemiology to mechanisms, screening, and management.
CONCULSIONS: The expert panel identified important clinical associations between MAFLD and the risk of CVD that could serve to increase awareness of the adverse metabolic and cardiovascular outcomes of MAFLD. Finally, the expert panel also suggests potential areas for future research.