Diagnosis of Van den Ende–Gupta syndrome: Approach to the Marden–Walker‐like spectrum of disorders
Bibliographic record
Abstract
Marden-Walker syndrome is challenging to diagnose, as there is significant overlap with other multi-system congenital contracture syndromes including Beals congenital contractural arachnodactyly, D4ST1-Deficient Ehlers-Danlos syndrome (adducted thumb-clubfoot syndrome), Schwartz-Jampel syndrome, Freeman-Sheldon syndrome, Cerebro-oculo-facio-skeletal syndrome, and Van den Ende-Gupta syndrome. We discuss this differential diagnosis in the context of a boy from a consanguineous union with Van den Ende-Gupta syndrome, a diagnosis initially confused by the atypical presence of intellectual disability. SNP microarray and whole exome sequencing identified a homozygous frameshift mutation (p.L870V) in SCARF2 and predicted damaging mutations in several genes, most notably DGCR2 (p.P75L) and NCAM2 (p.S147G), both possible candidates for this child's intellectual disability. We review distinguishing features for each Marden-Walker-like syndrome and propose a clinical algorithm for diagnosis among this spectrum of disorders. © 2016 Wiley Periodicals, Inc.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".