Defining Developmental Regression in Rare Neurodevelopmental Disorders of Genetic Etiology: A Scoping Review
Bibliographic record
Abstract
Background: Some genetic neurodevelopmental disorders (NDDs) are linked to a loss of acquired abilities. No universal term or severity measure exists for this phenomenon. This scoping review aims further to define developmental regression in NDDs of genetic etiology. Method: We used the PRISMA checklist and searched PubMed, medRxiv, and Google Scholar for developmental regression literature. After data extraction, qualitative (e.g., assessment methods) and quantitative (e.g., mentioned NDDs) data were analyzed. Results: A total of 59 relevant articles from 2074 unique records were identified, associating 18 NDDs of genetic etiology with developmental regression. Multiple terms (e.g., loss of skills, deterioration) and definitions were used across syndromes. Conclusions: A uniform definition of developmental regression was formulated based on literature diversity and NDD heterogeneity. The study also offers guidance on identifying and monitoring developmental regression and its underlying causes.
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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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.021 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".