Liver Imaging in Fontan Patients
Bibliographic record
Abstract
Background: Fontan patients frequently develop liver cirrhosis (LC); however, the diagnostic accuracy of ultrasound (US) for detecting LC and the clinical implications of such diagnoses have not been clearly established. Objectives: This study aims to evaluate the diagnostic performance of US for detecting LC in an adult population with Fontan circulation and to determine the correlation between LC and mortality/transplantation. Methods: This was a retrospective study. Data on cross-sectional imaging, liver USs, and clinical visits that occurred within 12 months of the cross-sectional imaging were collected. Liver US diagnostic accuracy was evaluated against cross-sectional imaging. Kappa agreement between methods was assessed. Univariate Cox proportional hazards regression analysis was employed to compare mortality and transplant outcomes. Results: Overall, 131 patients were included. Liver US and cross-sectional imaging (computed tomography 74, magnetic resonance imaging 57) was performed in all patients. Liver US reported heterogeneous parenchyma, lobar redistribution, and surface nodularity in 85.4%, 72.5%, and 65.6% of cases. Cross-sectional imaging reported these features in 60.3%, 87.0%, and 84.9% of cases, respectively. US sensitivity was greater than 0.75 for all variables, while specificity was 0.21, 0.58, and 0.85, respectively. LC was diagnosed in 78% of cases by US and in 90% by cross-sectional imaging, with a kappa agreement of 0.21 between techniques. There was no significant correlation between the presence of hepatic parenchymal changes or cirrhosis and mortality/transplantation. Conclusions: Liver US is effective for screening and monitoring liver cirrhotic features in the adult Fontan population. In a univariate analysis, there was no association between LC and mortality or transplantation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".