Challenges of diagnosis in fetal alcohol syndrome and fetal alcohol spectrum disorder in the adult
Bibliographic record
Abstract
Adults with fetal alcohol syndrome (FAS) and the subsets of individuals with attenuated phenotype subsumed under the umbrella term of fetal alcohol spectrum disorder (FASD) provide clinicians with a challenge. Compounding this, FASD is different from most genetic syndromes since a specific diagnostic biological test is not available. The diagnosis first needs to be suspected and confirmation requires a diagnostic assessment that is best carried out in the context of a multi-disciplinary team approach. There is surprisingly little research published on the prevalence, natural history, medical, and social complications relevant to adults with FASD. The evidence that is emerging suggests that this disorder is common, and that services to diagnose and treat these individuals are limited. Adults with FASD have a higher incidence of impairments in social adaptive and executive function, and a higher degree of psychopathology when compared to the general population. The impact of FASD has significant and serious effects on those affected with FASD, their families, and our communities. There is a need for improved access to diagnosis, and more research and evaluation of interventions currently in use. In this paper, we describe the current diagnostic criteria, the differential diagnosis, the prevalence, natural history, the behavioral and mental health consequences, medical and social management issues, and interventions for adults affected with this disorder.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".