Symptomatic Liver Involvement in Neonatal Hereditary Hemorrhagic Telangiectasia
Bibliographic record
Abstract
High-flow hepatic vascular anomalies with arteriovenous shunting commonly manifest during the neonatal period with signs and symptoms of congestive heart failure, but to our knowledge, they have never been described in patients with hereditary hemorrhagic telangiectasia (HHT). We report here our experience with 3 patients with hepatic arteriovenous malformations (AVMs) who presented with symptoms of high-output congestive heart failure during the neonatal period and were subsequently diagnosed with HHT. Imaging showed large hypervascular lesions and multiple hepatic arteriovenous shunts that differentiated these lesions from liver hemangiomas. Transcatheter embolization was performed in all cases. One infant died of sepsis shortly after embolization; follow-up at the age of 2.5 years of the surviving infants revealed involution of the vascular lesions and no evidence of symptom recurrence. We conclude that severe symptoms related to hepatic AVMs in HHT can occur in the neonatal period and that HHT should therefore be included in the differential diagnosis of symptomatic neonatal hepatic vascular malformations. Imaging plays a key role in differentiating hepatic AVMs from hemangiomas, because the latter require additional pharmacologic treatments. Early transcatheter embolization seems to be effective, but long-term outcomes still need to be assessed.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".