Important Risk Factors of Liver Cirrhosis in HIV and Hepatitis C Coinfected Patients: A Systematic Review
Bibliographic record
Abstract
Introduction Hepatitis C virus (HCV) is the leading cause of chronic hepatitis and liver fibrosis. Due to shared modes of transmission with human immunodeficiency virus (HIV), HIV-HCV coinfection is also common worldwide. Multiple studies have shown that the rates of liver fibrosis and associated complications increase considerably in this sub-population compared to a single HCV infection. Thus, in this study, we aimed to conduct a systematic review of possible associated important risk factors of accelerated liver cirrhosis among HIV-HCV coinfected subjects. Methods A systematic review of published studies relevant to the main risk factors of liver cirrhosis progression in HIV and hepatitis C coinfected patients was performed using databases of PubMed, Web of Science, Scopus, and Embase were searched using keywords and their combinations. We retrieved all the relevant papers and reports published in English till 27 June 2022, which were examined by applying inclusion/exclusion criteria for data extraction after a two-step screening process. Results The long-term or chronic hepatitis C and HIV coinfection is a substantial risk factor for Cirrhosis. Primary etiologies identified causing fibrosis, and the rapid progression of Cirrhosis in HIV/HCV coinfected patients include high-risk alcohol consumption, chronic elevation of ALT, AST, Aspartate Aminotransferase to Platelet Ratio Index (APRI) and Gamma-glutamyl Transferase (GGT), Body Mass Index (BMI), older age, high HIV and HCV viral loads, lower CD4+ count (<250/mm3), and male gender. Comorbidities such as diabetes, hypertension, hyperlipidemia, and high visceral fat area are suggested etiologies of cirrhosis. Conclusion The results showed that HIV accelerates the progression of HCV-related liver disease independent of its effect on the immune system. This effect is somehow dependent on age, gender, BMI, duration of HIV infection, and CD4 count.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".