New developmental syndromes: Understanding the family experience
Bibliographic record
Abstract
Increased application of next generation sequencing has led to the discovery of a multitude of new neurodevelopmental syndromes, contributing to an increased diagnostic rate for exome sequencing from 25% originally to 40% currently. Owing to the recent recognition of these syndromes, as well as the types of large-scale studies (with limited phenotype information) often making these discoveries, these disorders may be poorly characterized clinically. As a result there is very limited information and disorder-specific support available to patients and families. We used a qualitative approach to explore how families experience a diagnosis of a new syndrome. We conducted semi-structured telephone interviews with parents and adult siblings of children who received a diagnosis of a new syndrome after whole exome sequencing (WES) performed through a translational research study. The interviews were recorded, transcribed verbatim, and transcripts were analyzed using grounded theory methods. Analysis of the 12 interviews revealed that a lack of information about the child's condition continues to play a large role in these families' experiences even after diagnosis. Almost all (92%) participants expressed ongoing uncertainty about their child's health and future. Most (83%) participants were interested in identifying other families with the same syndrome, which was related to both social support and seeking of information. Interestingly, 33% of participants worried about the child's risk for cancer due to their syndrome. Our results highlight some of the needs of families of children with new syndromes, and emphasize important issues care providers should address in pre- and post-test genetic counseling for WES and whole genome sequencing.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".