Comparing diagnostic classification of neurobehavioral disorder associated with prenatal alcohol exposure with the Canadian fetal alcohol spectrum disorder guidelines: a cohort study
Bibliographic record
Abstract
BACKGROUND: Diagnostic criteria have recently been introduced in the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5), for neurobehavioral disorder associated with prenatal alcohol exposure (ND-PAE). The purpose of this study is to assess the classification of this condition using the Canadian fetal alcohol spectrum disorder (FASD) multidisciplinary diagnostic guidelines as the standard of comparison. First, classification of ND-PAE was compared with Canadian FASD diagnoses of fetal alcohol syndrome (FAS), partial FAS and alcohol-related neurodevelopmental disorder. Second, classification of ND-PAE was compared with FAS and pFAS only, a criterion for which includes facial features highly predictive of prenatal alcohol exposure and effects. METHODS: Eighty-two patients underwent multidisciplinary clinical evaluations using the Canadian FASD diagnostic guidelines between 2011 and 2015. Two clinicians independently reviewed patient files for evidence of diagnostic criteria for ND-PAE when applying an impairment cut-off level of 2 or more standard deviations below the mean, or clinically significant impairment in the absence of standardized norm-referenced measures. RESULTS: > 0.05). INTERPRETATION: Although there is considerable overlap between both sets of criteria, ND-PAE was less likely to identify patients with FASD. Although the neurobehavioral domains assessed by ND-PAE are supported in research, its diagnostic structure restricts the identification of FASD at the impairment threshold of 2 or more standard deviations. A disconnect remains with regard to impairment thresholds between FASD, which relies on neurodevelopmental data, and ND-PAE, which relies on clinical judgment.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".