Psychotropic Medication Usage in Individuals with Fetal Alcohol Spectrum Disorders (FASD) and Psychiatric Co-morbidities in Canada
Bibliographic record
Abstract
Background and objective Individuals with Fetal Alcohol Spectrum Disorder (FASD) tend to be prescribed a high number of psycho-tropic medications to treat high rates of comorbid psychiatric disorders. A lack of guidance regarding best practices for prescribing psychotropic medications to individuals with FASD probably accounts for this reliance on polypharmacy. The objective of this study is to describe the types of medications prescribed to individuals with prenatal alcohol exposure, comparing rates between individuals diagnosed with FASD and individuals without FASD as well as how medications are prescribed based on age, sex, and comorbid psychiatric disorders. Material and methods Data were drawn from Canada's national FASD database. This database includes information collected during an FASD assessment related to diagnostic outcomes, secondary challenges, and medical and mental health information. Descriptive statistics were calculated for four diagnostic groups (FASD with sentinel facial features [FASD + SFF], FASD without sentinel facial features [FASD - SFF], at risk for FASD [“at risk”], and no FASD). Group demographics were compared using Chi-Square, Fisher's Exact Test, and ANOVA, as appropriate. Differences in the proportion of individuals between these four diagnostic groups were calculated using each of the following six classes of psychotropic medications—antipsychotics, antidepressants/anxiolytic, anticonvulsants/mood stabilizers, stimulants, melatonin, and others—using ANOVA. Considering just the individuals with FASD by combining the FASD + SFF and FASD - SFF groups, independent sample tests were used to compare differences in the proportion of males and females prescribed different medications. Chi-Square and Fisher's Exact Test were used to compare the proportion of individuals using psychotropic medications, according to category, within the FASD group based on the presence or absence of 13 comorbid psychiatric disorders. Results The overall sample included 2349 participants (mean value = 18.1 years, SD = 10.3). The sample included 1453 participants with an FASD diagnosis (n = 218, FASD + SFF, mean = 23.7 years, SD = 15.8, and n = 1235, FASD - SFF, mean = 19.5 years, SD = 10.0 years) and 896 participants who were assessed but did not receive an FASD diagnosis (n = 653, no FASD, mean = 16.1 years and n = 261, “at risk” for FASD, mean = 12.2 years). The FASD groups had a significantly higher rates of anxiety disorders, depressive disorders, and the presence of at least one comorbid psychiatric disorder compared to the no FASD and the “at risk” groups. Both FASD groups had a higher proportion of individuals taking antipsychotic and antidepressant/anxiolytic medications compared to the no FASD and “at risk” groups. Females with FASD were more often prescribed antidepressants/anxiolytics compared to males with FASD, while males with FASD were more often prescribed stimulants than females with FASD. The prevalence of antidepressants/anxiolytics, stimulants, and melatonin use by individuals with FASD differed across the lifespan. The prevalence of the prescription of six medication categories was found to differ according to psychiatric disorder. Conclusion Compared to individuals assessed as not fulfilling criteria for FASD, those with FASD had higher rates of psychiatric disorders and were prescribed significantly more antidepressants/anxiolytics and antipsychotics. The class and rate of prescriptions may support efforts in devising treatment guidelines for a complex disorder with known high comorbidity such as FASD.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| 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".