Long-Acting Injectable Antipsychotics: Evidence of Effectiveness and Use
Bibliographic record
Abstract
OBJECTIVE: To review the evidence for the role of long-acting injectable (LAI) antipsychotics (APs), especially the second-generation AP (SGA) LAIs, in the treatment of schizophrenia and to discuss the use rates of LAIs in Canada. METHOD: A search of online medical databases was conducted of the published literature (1995-2012) of the effects of LAIs on the domains of remission, adherence, relapse, and hospitalization. Results obtained from randomized controlled trials (RCTs), systematic reviews, meta-analyses, and large-scale observational studies were included. Expert consensus data were also solicited on LAI use within a Canadian context. RESULTS: While the efficacy of LAIs, compared with placebo, is well established, the evidence from RCTs is equivocal for any specific advantage for SGA LAIs, compared with oral medications, probably owing to challenges in conducting such RCTs. Evidence from methodologically less rigorous studies and from clinical practice suggests some advantages in achieving and maintaining remission, risk of relapse, and hospitalization. The rate of LAI (first-generation AP and SGA) use from published outpatient studies is low at 6.3% in Canada, compared with 15% to 80% worldwide. However, there is a relatively high rate of use in specific early psychosis programs and in conjunction with community treatment orders in Canada. CONCLUSIONS: LAIs are at least as effective as oral APs in the treatment of psychotic disorders. The former may have specific advantages for patients who demonstrate covert nonadherence. The underuse of LAIs in Canada needs to be better understood and addressed.
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 | 0.011 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| 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".