The utility of psychotropic drugs on patients with Fetal Alcohol Spectrum Disorder (FASD): a systematic review
Bibliographic record
Abstract
BACKGROUND: Treatment of the complications arising from Prenatal Alcohol Exposure (PAE) has largely been focused on psychosocial and environmental approaches. Research on the use of medications, especially psychotropic medications, has lagged behind.OBJECTIVES: This systematic review sought to investigate psychotropic medication related findings and outcomes in those diagnosed with Fetal Alcohol Spectrum Disorder (FASD).METHODS: Comprehensive searches were conducted in seven major databases (Medline/PubMed, Scopus, Web of Knowledge, Embase, PsycINFO, Cochrane Library, and PsycARTICLES) up to February 2017. Key search terms with synonyms were mapped on these databases. There were no timeline restrictions and no grey literature searches. Two reviewers independently assessed 25 studies that met the inclusion criteria. Most studies were reviews of treatment and retrospective case series.RESULTS: Two crossover randomized trials were reported, and the findings were not amenable to meta-analysis. Several conditions (depression, agitation, seizures, and outburst) combined with the most frequent presentation, ADHD, to represent the rationale for prescribing psychotropic medications. Second-generation antipsychotics were found to improve social skills, but the paucity of data limited the extent of clinical guidance necessary for the field.CONCLUSIONS: The systematic review showed that there are some clinical evidence displaying the validity of psychopharmacological interventions in people with FASD, which varies across the spectrum of disease severity, age, and gender. There is a need for more clinical evidence-based studies in addition to clinical expert opinions to substantiate an optimal ground for individualized management of FASD.The study protocol for this review was registered in PROSPERO with registration number CRD42016045703.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".