Emergence of the natural history of Myhre syndrome: 47 patients evaluated in the Massachusetts General Hospital Myhre Syndrome Clinic (2016–2023)
Bibliographic record
Abstract
Myhre syndrome is an increasingly diagnosed ultrarare condition caused by recurrent germline autosomal dominant de novo variants in SMAD4. Detailed multispecialty evaluations performed at the Massachusetts General Hospital (MGH) Myhre Syndrome Clinic (2016-2023) and by collaborating specialists have facilitated deep phenotyping, genotyping and natural history analysis. Of 47 patients (four previously reported), most (81%) patients returned to MGH at least once. For patients followed for at least 5 years, symptom progression was observed in all. 55% were female and 9% were older than 18 years at diagnosis. Pathogenic variants in SMAD4 involved protein residues p.Ile500Val (49%), p.Ile500Thr (11%), p.Ile500Leu (2%), and p.Arg496Cys (38%). Individuals with the SMAD4 variant p.Arg496Cys were less likely to have hearing loss, growth restriction, and aortic hypoplasia than the other variant groups. Those with the p.Ile500Thr variant had moderate/severe aortic hypoplasia in three patients (60%), however, the small number (n = 5) prevented statistical comparison with the other variants. Two deaths reported in this cohort involved complex cardiovascular disease and airway stenosis, respectively. We provide a foundation for ongoing natural history studies and emphasize the need for evidence-based guidelines in anticipation of disease-specific therapies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".