An umbrella review on the use of antipsychotics in anxiety disorders: A registered report protocol
Bibliographic record
Abstract
Anxiety disorders, including panic disorder (PD), generalized anxiety disorder (GAD), social anxiety disorder (SAD), agoraphobia, and specific phobia, are among the most common psychiatric disorders. Although the traditional pharmacologic treatments for anxiety included barbiturates and then benzodiazepines, the introduction of tricyclic antidepressants, followed by the selective serotonin reuptake inhibitors (SSRIs), marked a tidal shift in the treatment of anxiety. Although not approved for treatment of anxiety disorders (with the exception of trifluoperazine) there is ongoing off-label, unapproved use of both first-generation "typical" antipsychotics (FGAs) and second-generation or "atypical" antipsychotics (SGAs) for anxiety. Although there have been systematic reviews and meta-analyses on the use of antipsychotics in anxiety disorders, most of these reviews focused on SGAs, primarily the use of quetiapine in GAD. Given that there is little known about the potential benefits and short-and long-term risks of using antipsychotics in anxiety, there is a need for an umbrella review of systematic reviews and meta-analyses of the use of both FGAs and SGAs in anxiety disorders. The specific aims of this study are as follows: (1) Evaluate the evidence of efficacy of FGAs and SGAs in anxiety disorders as an adjunctive treatment to SSRIs, serotonin norepinephrine reuptake inhibitors (SNRIs) and other non-antipsychotic medications; (2) Compare monotherapy with antipsychotics to first-line treatments for anxiety disorders in terms of effectiveness, risks, and side effects; and (3) Evaluate the short- and long-term risks and side effects of prescribing antipsychotics in anxiety disorders. The review is registered on PROSPERO (CRD42021237436). Since data extraction has not begun, there is not preliminary data to share.
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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 | 0.027 | 0.047 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.143 | 0.018 |
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".