Clinical Recovery Among Individuals With a First-Episode Schizophrenia an Updated Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND AND HYPOTHESIS: Through decades the clinical recovery outcomes among individuals diagnosed with schizophrenia have been highly inconsistent ranging from 13.5% to 57%. The primary objective of this updated examination was to report the pooled estimate and explore various moderators to improve the understanding of the course of schizophrenia. STUDY DESIGN: A systematic literature search was set up on PubMed, PsycInfo, and EMBASE until January 13th, 2022. Both observational and interventional studies among cohorts of individuals with the first episode of schizophrenia reporting on clinical recovery were included. The PRISMA 2020 statement was used and data was extracted for a random-effects meta-analysis, meta-regression, and sensitivity analyses. Risk of bias was assessed using The Newcastle-Ottawa Scale. STUDY RESULTS: A 20.8% (95% CI = 17.3 to 24.8) recovery rate was found among 26 unique study samples (mean trial duration, 9.5 years) including 3877 individuals (mean age, 26.4 years). In meta-regression none of the following study characteristics could uncover the diverse reported recovery rates; age at inclusion (P = .84), year of inclusion (P = .93), follow-up time (P = .99), drop-out rate (P = .07), or strictness of the recovery criteria (P = .35). Furthermore, no differences in recovery were found between early intervention services (EIS; 19.5%; 95% CI = 15.0 to 24.8) compared to other interventions (21%; 95% CI = 16.9 to 25.8), P = .65. CONCLUSIONS: A clinical recovery rate of approximately 21% was found with minimum impact from various moderators. The rate was not different comparing EIS with other interventions implying that new initiatives are needed to improve the rate of recovery.
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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 | 0.019 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.035 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".