Systematic review of long-acting injectables versus oral atypical antipsychotics on hospitalization in schizophrenia
Bibliographic record
Abstract
OBJECTIVE: To assess the impact of long-acting injectables (LAIs) versus oral antipsychotics (OAs) on hospitalizations among patients with schizophrenia by conducting a systematic literature review of studies with different study designs and performing a meta-analysis. METHODS: Using the PubMed database and major psychiatric conference proceedings, a systematic literature review for January 2000 to July 2013 was performed to identify English-language studies evaluating schizophrenia patients treated with atypical antipsychotics. Studies reporting hospitalization rates as a percentage of patients hospitalized or as the number of hospitalizations per person per year were selected. The primary meta-analysis assessed the percentage decrease in hospitalization rates before and after treatment initiation for matched time periods. The secondary meta-analysis assessed the absolute rate of hospitalization during follow-up. Pooled treatment-effect estimates were calculated using random-effects models. To account for differences in patient and study-level characteristics between studies, meta-regression analyses were used. Subset analyses further explored the heterogeneity across study designs. RESULTS: Fifty-eight studies evaluating 25 arms (LAIs: 13 arms, 4516 patients; OAs: 12 arms, 23,516 patients) in the primary meta-analysis and 78 arms (LAIs: 12 arms, 4481 patients; OAs: 66 arms, 96,230 patients) in the secondary meta-analysis were identified. Reduction in hospitalization rates for LAIs was 20.7 percentage points higher than that of OAs (random-effects estimates: LAIs = 56.2% vs. OAs = 35.5%, P = 0.023). Controlling for patient and study characteristics, the adjusted percentage reduction in hospitalization rates for LAIs was 26.4 percentage points higher than for OAs (95% CI: 3.3-49.5, P = 0.027). As for the secondary meta-analysis, no significant difference between LAIs and OAs was observed (random-effects estimate: -8.6, 95% CI: -18.1-1.0, P = 0.077). Subset analyses across type of study yielded consistent results. Limitations of this analysis include the long observation period, which may not reflect current treatment patterns, the use of all-cause hospitalization, which may not be solely related to schizophrenia, and the fact that most studies in the LAI cohort evaluated risperidone. CONCLUSION: The primary results of this meta-analysis, including studies with both interventional and non-interventional designs and using meta-regressions, suggest that LAIs are associated with higher reductions in hospitalization rates for schizophrenia patients compared to OAs.
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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 | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.023 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".