Assessment of liver fibrosis by Fibroscan as compared to liver biopsy in biliary atresia
Bibliographic record
Abstract
AIM: To evaluate liver stiffness measurement (LSM) using non-invasive transient elastography (Fibroscan) in comparison with liver biopsy for assessment of liver fibrosis in children with biliary atresia (BA). METHODS: Thirty-one children with BA admitted to the Department of Pediatric Surgery of Beijing Children's Hospital from March 2012 to February 2013 were included in this study. Their preoperative LSM, liver biopsy findings, and laboratory results were studied retrospectively. RESULTS: The grade of liver fibrosis in all 31 patients was evaluated according to the METAVIR scoring system, which showed that 4 cases were in group F2, 20 in group F3 and 7 in group F4. There were 24 non-cirrhosis cases (F2-F3) and 7 cirrhosis cases (F4). In groups F2, F3 and F4, the mean LSM was 9.10 ± 3.30 kPa, 11.02 ± 3.31 kPa and 22.86 ± 12.43 kPa, respectively. LSM was statistically different between groups F2 and F4 (P = 0.002), and between groups F3 and F4 (P = 0.000), however, there was no statistical difference between groups F2 and F3 (P = 0.593). The area under the receiver operating characteristic curve of LSM for ≥ F4 was 0.866. The cut-off value of LSM was 15.15 kPa for ≥ F4, with a sensitivity, specificity, positive predictive value and negative predictive value of 0.857, 0.917, 0.750 and 0.957, respectively. CONCLUSION: Fibroscan can be used as a non-invasive technique to assess liver fibrosis in children with BA. The cut-off value of LSM (15.15 kPa) can distinguish cirrhotic patients from non-cirrhotic patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".