Liver dysfunction in adults with COVID-19 infection: A longitudinal study with transient elastography evaluation.

Background and Aim: Abnormal liver biochemistry (ALB) is common among patients with COVID-19 infection due to various factors. It is uncertain if it persists after the acute infection. We aimed to investigate this. Methods: A multicenter study of adult patients hospitalized for COVID-19 infection, with at least a single abnormal liver function test, was conducted. Detailed laboratory and imaging tests, including transabdominal ultrasound and FibroScan, were performed at assessment and at 6-month follow-up after hospital discharge. Results: From an initial cohort of 1246 patients who were hospitalized, 731 (58.7%) had ALB. A total of 174/731 patients fulfilled the inclusion criteria with the following characteristics: 48.9% patients had severe COVID-19; 62.1% had chronic liver disease (CLD); and 56.9% had metabolic-associated fatty liver disease (MAFLD). ALB was predominantly of a mixed pattern (67.8%). Among those (55.2%) who had liver injury (aspartate aminotransferase/alanine aminotransferase >3 times the upper limit of normal, or alkaline phosphatase/γ-glutamyl transferase/bilirubin >2 times the upper limit of normal), a mixed pattern was similarly predominant. Approximately 52.3% had normalization of the liver lunction test in the 6-month period post discharge. Patients with persistent ALB had significantly higher mean body mass index (BMI) and serum low-density lipoprotein (LDL), higher rates of MAFLD and CLD, higher mean liver stiffness measurement and continuous attenuated parameter score on FibroScan, and higher rates of liver injury on univariate analysis. Multivariate analysis was not statistically significant. Conclusions: Approximately 47.7% of COVID-19 patients were found to have persistent ALB up to 6 months following the acute infection, and it was associated with raised BMI, elevated serum LDL, increased rates of MAFLD and CLD, and higher rates of liver injury on univariate analysis, but not on multivariate analysis.

LIVERSTAT for risk stratification for patients with metabolic dysfunction-associated fatty liver disease.

BACKGROUND AND AIM: LIVERSTAT is an artificial intelligence-based noninvasive test devised to screen for and provide risk stratification for metabolic dysfunction-associated fatty liver disease (MAFLD) by using simple blood biomarkers and anthropometric measurements. We aimed to study LIVERSTAT in patients with MAFLD and to explore its role for the diagnosis of advanced fibrosis. METHODS: This is a retrospective study of data from MAFLD patients who underwent a liver biopsy. Patients with type 2 diabetes who underwent transient elastography and had liver stiffness measurement (LSM) < 5 kPa were included as patients with no fibrosis. Among these patients, controlled attenuation parameter <248 dB/m was considered as no steatosis. The LIVERSTAT results were generated based on a proprietary algorithm, blinded to the histological and LSM data. RESULTS: The data for 350 patients were analyzed (mean age 53 years, 45% male, advanced fibrosis 22%). The sensitivity, specificity, positive predictive value, negative predictive value, and misclassification rate of LIVERSTAT to diagnose advanced fibrosis were 90%, 50%, 30%, 95%, and 42%, respectively. The corresponding rates for Fibrosis-4 score (FIB4) were 56%, 83%, 44%, 89%, and 22%, respectively. When LSM was used as a second test, the corresponding rates for LIVERSTAT were 60%, 97%, 76%, 94%, and 8%, respectively, while the corresponding rates for FIB4 were 38%, 99%, 83%, 89%, and 11%, respectively. CONCLUSION: LIVERSTAT had a higher negative predictive value compared with FIB4 and a lower misclassification rate compared with FIB4 when used in a two-step approach in combination with LSM for the diagnosis of advanced fibrosis.

Helicobacter pylori in gastrointestinal manifestation of systemic sclerosis.

Aim: To study the prevalence of Helicobacter pylori in systemic sclerosis patients and its gastrointestinal manifestations in comparison with Helicobacter pylori-negative systemic sclerosis patients. Systemic sclerosis gastrointestinal outcome post Helicobacter pylori eradication was evaluated. Method: In total, 70 systemic sclerosis patients and 70 age-, gender- and race-matched healthy controls had their urea breath test done. Gastrointestinal manifestations in systemic sclerosis were assessed using University of California at Los Angeles 2.0 and Leeds Dyspepsia Questionnaire questionnaires. Systemic sclerosis patients with confirmed Helicobacter pylori infection were given standard Helicobacter pylori eradication therapy. Urea breath test was repeated 6 weeks posteradication therapy with their gastrointestinal symptoms reassessed. Results: The prevalence of Helicobacter pylori was low in both systemic sclerosis patients (10%) and healthy controls (2.9%). There was no significant difference in gastrointestinal symptoms between Helicobacter pylori-positive and Helicobacter pylori-negative systemic sclerosis patients. However, the Helicobacter pylori-positive patients reported higher median severity scores for the gastrointestinal symptoms of reflux (0.5 vs 0.35), abdominal distension (1.5 vs 0.75) and social functioning impairment score (0.5 vs 0.16) using the University of California at Los Angeles 2.0 score. The Helicobacter pylori-positive patients also indicated increased upper abdominal pain (3.0 vs 0.0), regurgitation (2.0 vs 0.0) and burping (3.0 vs 0.0), observed from the Leeds Dyspepsia Questionnaire scores. Gastrointestinal outcomes post-Helicobacter pylori eradication showed either an improvement or complete resolution of symptoms. Conclusion: Gastrointestinal symptoms in systemic sclerosis patients are unlikely to be caused by Helicobacter pylori in the recent years in our cohort of patients. No significant difference in gastrointestinal symptoms was seen between Helicobacter pylori-positive and Helicobacter pylori-negative systemic sclerosis patients. Helicobacter pylori can be readily tested by urea breath test to look for present infection.

The clinical management of hepatic sarcoidosis: A systematic review.

Background: Hepatic sarcoidosis is an uncommon clinical condition in which clear recommendations are lacking in its treatment. We aimed to review systematically the literature on hepatic sarcoidosis treatment to guide clinicians. Methods: Using MEDLINE, PubMed, CINAHL, Cochrane Library, and Google Scholar databases, we searched original articles on clinical studies reporting the outcome of adult hepatic sarcoidosis patients following treatment with various pharmacological agents. The primary end point was focused on assessing symptomatic relief and biochemical improvement posttreatment. Results: Out of 614 retrieved references, 34 published studies were eligible, providing data for a total of 268 patients with hepatic sarcoidosis. First-line therapy with corticosteroids alone was reported in 187 patients, whilst ursodeoxycholic acid (UDCA) was used in 40 patients. Symptomatic and biochemical responses were reported among 113(60.4%) and 80(42.8%) cases of corticosteroids respectively, whereas UDCA showed a complete response in 23(57.5%) patients. Second-line therapy was used in steroid-refractory cases, with most cases being reported for azathioprine (n = 32) and methotrexate (n = 28). Notably, 15(46.9%) and 11(39.2%) patients showed both clinical and biochemical responses respectively. Biological therapy including anti-tumor necrosis factor (anti-TNF) was used as third line therapy in twelve cases with a 72.7% symptomatic and biochemical response rate each. Conclusion: The quality of evidence for the treatment of hepatic sarcoidosis was poor. Nevertheless, it appears that corticosteroid or UDCA may be utilized as first-line therapy. For cases that are refractory to corticosteroids, steroid-sparing immunosuppressive agents and anti-TNF have shown some promising results, but further high-quality studies are required.

Diagnostic accuracy of non-invasive tests to screen for at-risk MASH-An individual participant data meta-analysis.

BACKGROUND & AIMS: There is a need to reduce the screen failure rate (SFR) in metabolic dysfunction-associated steatohepatitis (MASH) clinical trials (MASH+F2-3; MASH+F4) and identify people with high-risk MASH (MASH+F2-4) in clinical practice. We aimed to evaluate non-invasive tests (NITs) screening approaches for these target conditions. METHODS: This was an individual participant data meta-analysis for the performance of NITs against liver biopsy for MASH+F2-4, MASH+F2-3 and MASH+F4. Index tests were the FibroScan-AST (FAST) score, liver stiffness measured using vibration-controlled transient elastography (LSM-VCTE), the fibrosis-4 score (FIB-4) and the NAFLD fibrosis score (NFS). Area under the receiver operating characteristics curve (AUROC) and thresholds including those that achieved 34% SFR were reported. RESULTS: We included 2281 unique cases. The prevalence of MASH+F2-4, MASH+F2-3 and MASH+F4 was 31%, 24% and 7%, respectively. Area under the receiver operating characteristics curves for MASH+F2-4 were .78, .75, .68 and .57 for FAST, LSM-VCTE, FIB-4 and NFS. Area under the receiver operating characteristics curves for MASH+F2-3 were .73, .67, .60, .58 for FAST, LSM-VCTE, FIB-4 and NFS. Area under the receiver operating characteristics curves for MASH+F4 were .79, .84, .81, .76 for FAST, LSM-VCTE, FIB-4 and NFS. The sequential combination of FIB-4 and LSM-VCTE for the detection of MASH+F2-3 with threshold of .7 and 3.48, and 5.9 and 20 kPa achieved SFR of 67% and sensitivity of 60%, detecting 15 true positive cases from a theoretical group of 100 participants at the prevalence of 24%. CONCLUSIONS: Sequential combinations of NITs do not compromise diagnostic performance and may reduce resource utilisation through the need of fewer LSM-VCTE examinations.

Machine learning improves the prediction of significant fibrosis in Asian patients with metabolic dysfunction-associated steatotic liver disease - The Gut and Obesity in Asia (GO-ASIA) Study.

BACKGROUND: The precise estimation of cases with significant fibrosis (SF) is an unmet goal in non-alcoholic fatty liver disease (NAFLD/MASLD). 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 < 0.001, each). ML models showed 7%-12% better discrimination than FIB-4 to detect SF. Optimised random forest (RF) yielded best NPV/F1 in overall set (0.947/0.754), test set (0.798/0.588) and validation set (0.852/0.559), as compared to FIB4 in overall set (0.744/0.499), test set (0.722/0.456), and validation set (0.806/0.507). Compared to FIB-4, RF could pick 10 times more patients with SF, reduce unnecessary referrals by 28%, and prevent missed referrals by 78%. Age, AST, ALT fasting plasma glucose, and platelet count were top features determining the SF. Sequential use of SAFE < 140 and FIB4 < 1.2 (when SAFE > 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.