Utilization of psychotropic medications in children with FASD: a retrospective review
Bibliographic record
Abstract
BACKGROUND: Fetal Alcohol Spectrum Disorder (FASD) is a neurodevelopmental condition resulting from pre-natal alcohol exposure. In Canada, an estimated 1.4-4% of newborns are affected by FASD. FASD is often associated with behavioural comorbidities and many individuals require psychotropic medication. However, to date there are no FASD specific guidelines for prescribing medication. Recently, Mela and colleagues described four behavioural symptom clusters commonly seen in FASD with suggested pharmacologic treatment for each cluster within an algorithm. The primary objective was to compare the proposed treatment algorithm retrospectively to actual treatment in a real-world FASD pediatric practice. The secondary objective was to refine the description of symptom clusters which will be targeted with treatment. METHODS: We collected the diagnostic and medication history from all patient visits of a Regina Developmental Pediatrician who specializes in FASD diagnosis and medication treatment. Three hundred fifty-four FASD patients were identified between 2005 to 2020. The medications that would be predicted from the algorithm were compared to the real-world historical data. A positive case was defined as all algorithm-predicted medications matching the historical data; a negative case had one or more medications failing to match. RESULTS: Of the 354 patients, 36 were removed for insufficient information. Of the remaining 318 cases, 172 (54.1%) were positive compared to 146 (45.9%) negatives. In single prescription cases (n=147), the incidence of positives was 67.3%; in multi-prescriptions (n=72) it was 27.8%; and in cases where no prescription was needed (n=99), the positive incidence was 53.5%. CONCLUSIONS: The prescription algorithm is promising but requires further refinement to accommodate the range of presentations in children with FASD. With respect to unclassified symptoms, we propose the following: sleep onset difficulty as hyperarousal; gender dysphoria and obsessive compulsive disorder as cognitive inflexibility; grief as emotional regulation; and autism spectrum disorder as hyperactive/neurocognitive.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".