Positive and negative symptoms in methamphetamine-induced psychosis compared to schizophrenia: A systematic review and meta-analysis
Bibliographic record
Abstract
The clinical profiles of methamphetamine-induced psychosis (MIP) and schizophrenia are largely overlapping making differentiation challenging. In this systematic review and meta-analysis, we aim to compare the positive and negative symptoms of MIP and schizophrenia to better understand the differences between them. In accordance with our pre-registered protocol (CRD42021286619), we conducted a search of English-language studies up to December 16th, 2022, in PubMed, EMBASE, and PsycINFO, including stable outpatients with MIP and schizophrenia. We used the Newcastle-Ottawa Scale to measure the quality of cross-sectional, case-control, and cohort studies. Of the 2052 articles retrieved, we included 12 studies (6 cross-sectional, 3 case-control, and 2 cohort studies) in our meta-analysis, involving 624 individuals with MIP and 524 individuals with schizophrenia. Our analysis found no significant difference in positive symptoms between the two groups (SMD, −0.01; 95%CI, −0.13 to +0.11; p = 1). However, individuals with MIP showed significantly less negative symptoms compared to those with schizophrenia (SMD, −0.35; 95CI%, −0.54 to −0.16; p = 0.01; I2 = 54 %). Our sensitivity analysis, which included only studies with a low risk of bias, did not change the results. However, our meta-analysis is limited by its cross-sectional approach, which limits the interpretation of causal associations. Furthermore, differences in population, inclusion criteria, methodology, and drug exposure impact our findings. Negative symptoms are less prominent in individuals with MIP. While both groups do not differ regarding positive symptoms, raises the possibility of shared and partly different underlying neurobiological mechanisms related to MIP and schizophrenia.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.045 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 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".