Long-acting injectable antipsychotics for early psychosis: A comprehensive systematic review
Bibliographic record
Abstract
AIM: Long acting injectable (LAI) antipsychotics are an alternative to oral antipsychotic (OAP) treatment and may be beneficial for patients in the early stages of schizophrenia. This study aims to provide a comprehensive review on the efficacy of first-generation and second-generation LAI antipsychotics in recent-onset, first-episode, and early psychosis patients. METHODS: MEDLINE, EMBASE, PsycINFO, and Web of Science Core databases were used to search for studies that used LAIs in early psychosis patients. Studies published up to 06 Jun 2019 were included with no language restrictions applied. Inclusion criteria were a diagnosis of schizophrenia or related disorder, where patients were in their first episode or had a duration of illness ≤5 years. RESULTS: 33 studies were included: 8 RCTs, 4 post-hoc analyses, 2 case reports, and 19 naturalistic studies. The majority of studies evaluated risperidone LAIs (N = 14) and paliperidone palmitate (N = 10), while the remainder investigated fluphenazine decanoate (N = 3), flupentixol decanoate (N = 2), and aripiprazole (N = 1). Two studies did not specify the LAI formulation used, and one cohort study compared the efficacy of multiple different LAI formulations. CONCLUSIONS: While the majority of data is based on naturalistic studies investigating risperidone LAIs or paliperidone palmitate, LAIs may be an effective treatment for early psychosis patients in terms of adherence, relapse reduction, and symptom improvements. There is still a need to conduct more high quality RCTs that investigate the efficacy of different LAI formulations in early psychosis patients.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".