Severe tortuosity and stenosis of the systemic, pulmonary and coronary vessels in 12 patients with similar phenotypic features: a new syndrome?
Bibliographic record
Abstract
We describe what is, to the best of our knowledge, a previously unreported association in patients with similar facial features, skin and joint laxity, of lengthening and tortuosity of systemic, pulmonary and coronary vessels. We evaluated 12 patients with similar phenotypes, from eight different families. Detailed echocardiographic and angiographic evaluations were performed in all, and biopsies of the skin in seven. All patients have elongated facies, prominent ears, micrognathia and laxity of their joints. Angiographic pictures showed a varying degree of lengthening and tortuosity of systemic, pulmonary, and coronary arteries. Pulsatile carotid arteries formed cervical masses in 2 patients, and three had severe renal arterial stenoses. All showed varying degrees of branch and peripheral pulmonary arterial stenosis, necessitating placement of stents in six. Biopsy of the skin proved normal in all seven patients studied, thus excluding cutis laxa, Ehlers-Danlos and Marfan syndromes. The constellation of abnormalities suggests a genetic syndrome of connective tissue etiology. Further genetic studies, and gene mapping, are underway.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".