The Performance of Serum Biomarkers for Predicting Fibrosis in Patients with Chronic Viral Hepatitis

Machine Learning Approaches for the Prediction of Hepatitis B and C Seropositivity

(1) Background: The identification of patients at risk for hepatitis B and C viral infection is a challenge for the clinicians and public health specialists. The aim of this study was to evaluate and compare the predictive performances of four machine learning-based models for the prediction of HBV and HCV status. (2) Methods: This prospective cohort screening study evaluated adults from the North-Eastern and South-Eastern regions of Romania between January 2022 and November 2022 who underwent viral hepatitis screening in their family physician's offices. The patients' clinical characteristics were extracted from a structured survey and were included in four machine learning-based models: support vector machine (SVM), random forest (RF), naïve Bayes (NB), and K nearest neighbors (KNN), and their predictive performance was assessed. (3) Results: All evaluated models performed better when used to predict HCV status. The highest predictive performance was achieved by KNN algorithm (accuracy: 98.1%), followed by SVM and RF with equal accuracies (97.6%) and NB (95.7%). The predictive performance of these models was modest for HBV status, with accuracies ranging from 78.2% to 97.6%. (4) Conclusions: The machine learning-based models could be useful tools for HCV infection prediction and for the risk stratification process of adult patients who undergo a viral hepatitis screening program.

A Novel Prediction Model for Significant Liver Fibrosis in Patients with Chronic Hepatitis B

Background

Preventing liver fibrosis from progressing to cirrhosis and even liver cancer is a key step in the treatment of chronic hepatitis B (CHB). This study is aimed at constructing and validating a new nomogram for predicting significant liver fibrosis (S ≥ 2) in CHB patients.

Methods

The nomogram was based on a retrospective study of 252 CHB patients. The predictive accuracy and discriminative ability of the nomogram were evaluated by the area under receiver operating characteristic curve (AUROC), decision curves, and calibration curve compared with the fibrosis 4 score (FIB-4) and aspartate aminotransferase-to-platelet ratio index (APRI). The results were validated using bootstrap resampling and an external set of 168 CHB patients.

Results

A total of 420 CHB patients were enrolled based on liver biopsy results. Independent factors predicting significant liver fibrosis were laminin (LN), procollagen type III N-terminal peptide (PIIINP), and blood platelet count (PLT) in a multivariate analysis, and these factors were selected to construct the nomogram. The calibration curve for the probability of significant liver fibrosis showed optimal agreement between the prediction from the nomogram and actual observation. The prediction from the nomogram was more consistent with the results of liver biopsy than FIB-4 and APRI. The AUROC of the nomogram was higher than that of FIB-4 and APRI for predicting significant liver fibrosis. These results were confirmed in the validation set. Furthermore, the decision curve analysis suggested that the most net benefits were provided by the nomogram.

Conclusions

We found the proposed nomogram resulted in a more accurate prediction of significant liver fibrosis in CHB patients and could provide the most net benefits. We recommend this noninvasive assessment for patients with liver fibrosis to avoid the risk of liver biopsy and earlier intervention to prevent the development of cirrhosis or liver cancer.

Predictive value of the aspartate aminotransferase to platelet ratio index for parenteral nutrition associated cholestasis in extremely low birth weight infants

Background

Parenteral nutrition (PN) improves the survival of premature infants. However, prolonged PN increases the risk of PN-associated cholestasis (PNAC).

Objective

We aimed to evaluate the predictive value of aspartate aminotransferase (AST)-to-platelet ratio index (APRI) for PNAC in infants with extremely low birth weight (ELBW, birth weight < 1000 g) infants.

Methods

We retrospectively reviewed the medical records of ELBW infants from March 2010 to February 2017. Clinical data and the serial APRI, AST, alanine aminotransferase (ALT), AST-to-ALT ratio, and direct bilirubin (DB) were analyzed. PNAC was diagnosed in infants with a history of PN for at least 2 weeks and direct bilirubin concentrations > 2 mg/dL after other causes of neonatal cholestasis were excluded.

Results

Among the 179 eligible ELBW infants, 56 (31.3%) were diagnosed with PNAC. APRI significantly differed between infants with PNAC and those without PNAC. The best APRI cut-off point was 0.410 at 2 weeks after the start of PN (area under the receiver operating characteristic curve = 0.752, p < 0.05; positive predictive value, 50.6%; negative predictive value, 84.1%).

Conclusion

APRI at 2 weeks after PN could be a reliable predictor of PNAC development in ELBW infants on PN.

Liver histology in asymptomatic Hepatitis-C virus positive blood donors

Objective:

To assess the Histological alteration of liver in asymptomatic HCV PCR positive family blood donors.

Methods:

This is a prospective cross sectional study carried out at Blood Transfusion Services, Clinical & Molecular Laboratory and Pakistan Health Research Council, Jinnah Postgraduate Medical Centre, Karachi from January 2011 to December 2016. One hundred thirteen (113) Anti HCV and HCV RNA positive family blood donors with normal or slightly raised ALT during three consecutive bimonthly visits were included. After taking consent liver biopsy was done to see the histopathological changes in these study participants. The software program SPSS for windows (Ver.19) was utilized for all statistical analysis.

Results:

One hundred thirteen blood donors who were Anti HCV and HCV RNA positive were included. Ninety eight were male and 15 Female with a mean age of 32.3±6.94 years. Nineteen (16.8%) had significant inflammation of grade 2-3. Nine (8.0%) had significant fibrosis and steatosis was seen in 65 (57.5%) cases. Cirrhosis or advanced liver disease was not found in this series.

Conclusion:

HCV infected individual with normal ALT level having good physical health, without any sign of advanced liver disease on ultrasonography and routine laboratory investigation like AST, Gamma GT, Alkaline Phosphatase, serum albumin, A/G ratio, platelet count and PT, INR might be highly helpful to predict mild or progressive liver disease. Ultimately it reduces the need of liver biopsy, an invasive procedure having significant complications.