Combination of Long-Acting Injectable Antipsychotics in the Treatment of Psychiatric Disorders—A Systematic Review of the Literature and Case Series
Bibliographic record
Abstract
BACKGROUND: The treatment of refractory schizophrenia is complex, and compliance with oral treatment, including clozapine, can be challenging at times. The purpose of this case series and literature review article is to evaluate the efficacy of the combined use of 2 different long-acting injectable antipsychotics (LAIAs) on the number of psychiatric hospitalizations and emergency department visits. There are currently few data to support this treatment option, despite the frequent use of combinations of oral antipsychotics. METHODS: We extracted the data from 8 different patients who received combination LAIAs from 1 hospital setting. We evaluated the frequency of hospitalization and emergency department visits before and after treatment with a mirror-image study design. A systematic review of existing literature was included to find all previously reported cases of combination LAIAs. RESULTS: The frequency of hospitalizations was greatly reduced after the initiation of combination LAIA treatment in the majority of the cases at study site, as well as in the literature review. The number of ED visits was not as clearly affected. In the literature review, combinations of 2 LAIAs with different mechanisms of action were often documented. Symptom scores were also reduced in most reviewed cases. CONCLUSIONS: Combinations of LAIAs seem to be promising as a treatment option for refractory psychotic disorders. This combination could be a treatment option for patients with limited alternatives, such as clozapine resistant or not eligible. The higher risk of adverse effects and long-term risks are not well documented.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".