The essential role of growth deficiency in the diagnosis of fetal alcohol spectrum disorder
Bibliographic record
Abstract
BACKGROUND: Laboratory studies confirm prenatal alcohol exposure (PAE) causes growth deficiency (GD). GD has traditionally been a core diagnostic feature of fetal alcohol spectrum disorders (FASD), but was removed from the Canadian and Australian FASD diagnostic guidelines in 2016. This study aimed to empirically assess the clinical role and value of GD in FASD diagnosis. METHODS: Data from 1814 patients with FASD from the University of Washington Fetal Alcohol Syndrome Diagnostic & Prevention dataset were analyzed to answer the following questions: 1) Is there evidence of a causal association between PAE and GD in our clinical population? 2) Is GD sufficiently prevalent among individuals with PAE to warrant its inclusion as a diagnostic criterion? 3) Does GD aid the diagnostic team in identifying and/or predicting which individuals will be most impaired by their PAE? RESULTS: GD significantly correlated with PAE. GD was as prevalent as the other core diagnostic features (facial and CNS abnormalities). GD occurred in all FASD diagnoses and increased in prevalence with increasing severity of diagnosis. The most prevalent form of GD was postnatal short stature. GD was as highly correlated with, and predictive of, severe brain dysfunction as the FAS facial phenotype. Individuals with GD had a two to three-fold increased risk for severe brain dysfunction. Sixty percent of patients with severe GD had severe brain dysfunction. GD accurately predicted which infants presented with severe brain dysfunction later in childhood. CONCLUSIONS: GD is an essential diagnostic criterion for FASD and will remain in the FASD 4-Digit Code.
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".