Identification and management of gastrointestinal manifestations of hereditary transthyretin amyloidosis: Recommendations from an Italian group of experts
Bibliographic record
Abstract
Gastrointestinal manifestations are common across all hereditary transthyretin amyloidosis (ATTRv) genotypes. However, they are poorly specific, and their recognition as part of ATTRv is difficult, resulting in misdiagnosis with more common conditions. Moreover, delays in diagnosis occur because of fragmented knowledge, a shortage of centers of excellence and specialists dedicated to ATTRv management, and the scarce involvement of gastroenterologists in multidisciplinary teams. A group of Italian gastroenterologists with experience in the management of ATTRv took part in a project aimed at assessing the awareness of ATTRv among the community of Italian gastroenterologists through an online survey and providing education about practical aspects of ATTRv management. Survey results reported low participation, and very few patients with ATTRv were cared for by gastroenterologists. This highlights the need for greater attention to rare diseases in gastroenterology and emphasizes increasing awareness of ATTRv and diagnostic suspicion. Based on the experts' recommendations, a diagnosis of ATTRv should be suspected when at least one of the 'red flags' is detected. Subsequently, it is suggested to promptly ask for genetic testing and exclude a serum and urinary monoclonal protein, even before the detection of amyloid in biopsy samples, particularly in non-endemic areas.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".