Acoustic Radiation Force Impulse and Conventional Ultrasound in the Prediction of Cirrhosis Complicating Fatty Liver: Does Body Mass Index Independently Alter the Results?
Bibliographic record
Abstract
We investigated whether ultrasound (US) could quantify steatosis and fibrosis in non-alcoholic fatty liver disease (NAFLD). Estimates of fat by gray-scale, hepatorenal index (HRI) and fibrosis by acoustic radiation force impulse (ARFI) were made using the interquartile range (IQR)/median for ARFI quality. Biopsy was the gold standard. US fat assessment correlated with histologic grade and predicted steatosis. HRI predicted steatosis but did not improve accuracy. ARFI of good quality was highly sensitive toward severe fibrosis. The median ARFI value depended linearly on body mass index (BMI). Poor quality ARFI data had higher histologic steatosis, leading to higher mean steatosis grades in rejected data (p = 0.018). The ARFI quality cut with IQR/median >0.15 or >0.3 excluded many more patients with severe steatosis versus normal, influenced by increasing BMI. By combining the baseline US with ARFI, patients can be concurrently diagnosed for steatosis and fibrosis, two of the key pathologies of NAFLD and non-alcoholic steatohepatitis (NASH). However, severe steatosis and high BMI may falsely alter ARFI results.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".