Pharmacological Treatment of Autism Spectrum Disorder: A Systematic Review of Treatment Guidelines
Bibliographic record
Abstract
Currently available systematic reviews on the pharmacological treatment of autism spectrum disorder (ASD) do not encompass all the evidence, as they exclude guidelines issued by national or local authorities that are not indexed in search engines such as PubMed.A systematic literature search was conducted to identify clinical guidelines on this topic using EMBASE, Medline, and PsycINFO. A manual search was also performed to identify guidelines by national or local authorities not included in the aforementioned databases.Thirty-eight guidelines were identified through manual search, including 27 items through search engines, 2 general guidelines, and 9 government agency guidelines. Many guidelines recommended risperidone (N=16) for the characteristic behaviors of ASD core features. For attention-deficit/hyperactivity disorder (ADHD) features, methylphenidate was most frequently recommended (N=23) for both inattention (N=6) and hyperactivity/impulsivity (N=16). Risperidone was also frequently recommended for maladaptive behaviors (N=33).A comprehensive literature search identified treatment guidelines for ASD issued by local or national administrative bodies that were not captured through search engines alone. There was some consensus among the guidelines on the use of psychotropics in alleviating specific features of ASD. However, physicians need to be aware of the lack of high-quality evidence supporting these recommendations.
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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".