A136 PREDICTIVE FACTORS OF CIRRHOSIS IN HCV PATIENTS WITH LOW PRE-TREATMENT APRI AND/OR FIB-4 SCORES
Bibliographic record
Abstract
Abstract Background It is essential to evaluate the stage of hepatic fibrosis prior to the initiation of HCV therapy. In addition to being a major prognostic factor, the presence of cirrhosis requires monitoring for hepatocellular carcinoma (HCC), esophageal varices, and decompensated liver disease. In some cases the presence of cirrhosis may affect the choice of therapy. In tertiary hepatology clinics, transient elastography (TE) is routinely used to assess fibrosis; however access to TE is limited. Fibrosis-4 (FIB4) and AST-to-platelet ratio index (APRI) are simple, easily available non-invasive methods of fibrosis measurement based on routine serum biomarkers. Studies evaluating HCV treatment pathways have reported that the use of FIB4 and APRI are cost-effective strategies for excluding cirrhosis thereby reducing the need for TE prior to treatment. Although the NPV of these tests are well described, a minority of patients will have advanced fibrosis despite low APRI and/or FIB4 scores. Aims To investigate predictive factors of cirrhosis in HCV patients with low pre-treatment APRI and/or FIB-4 scores. Methods Retrospective observational study with data obtained from the Pacific Gastroenterology Associates (PGA), a tertiary care outpatient Gastroenterology clinic located in Vancouver, British Columbia. Inclusions: Chronic HCV patients treated between Jan 2015 to 2019, pre-treatment TE values ≥12.5 kPa, FIB-4 <1.45 and/or APRI <0.7. Exclusions: those without cirrhosis, or incomplete evaluation prior to HCV treatment. Cirrhosis was defined as those with TE ≥12.5 kPa with clinical, radiographic, or pathologic features of cirrhosis. Results 52 patients were identified. 11 patients did not have clinical, radiographic, or pathologic features of cirrhosis and 3 patients were excluded for insufficient data. Thus, 39 patients were included in multivariate analysis. The mean age was 59 years and 66% (25/38) were male gender. 10% (4/38) were Genotype 3 (G3). Presence of G3 was not included in the multivariate analysis due to low number of observations. Conclusions Generally, an APRI <0.7 and FIB-4 <1.45 have good test characteristics for excluding fibrosis. Our study demonstrates that patients with obesity, dyslipidemia, excessive alcohol use, or known steatosis on ultrasound may have cirrhosis despite low serum biomarker scores. Co-existence of other liver diseases such as alcohol related or non-alcoholic fatty liver disease (NAFLD) should prompt further evaluation for fibrosis assessment beyond biomarkers as these persons may have more advanced liver disease. Funding Agencies None
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".