Meta-analysis of cortical thickness reduction in adult schizophrenia
Bibliographic record
Abstract
BACKGROUND: Numerous neuroimaging studies using surface-based morphometry analyses have reported altered cortical thickness among patients with schizophrenia, but the results have been inconsistent. We sought to provide a whole-brain meta-analysis, which may help enhance the spatial accuracy of identification. METHODS: We conducted a meta-analysis of whole-brain studies that explored cortical thickness alteration among adult patients with schizophrenia, including first-episode patients with schizophrenia, and patients with chronic schizophrenia, compared with healthy controls by using the seed-based d mapping with permutation of subject images (SDM-PSI) software. RESULTS: A systematic literature search identified 25 studies (33 data sets) of cortical thickness, including 2008 patients with schizophrenia and 2004 healthy controls. Overall, patients with schizophrenia showed decreased cortical thickness in the right inferior frontal gyrus (IFG) and bilateral insula extending to the superior temporal gyrus (STG). Subgroup meta-analysis reported that patients with chronic schizophrenia showed decreased cortical thickness in the right insula extending to the right IFG. There was no significant cortical thickness difference between first-episode patients with schizophrenia and healthy controls. LIMITATIONS: The results of meta-regression analyses should be viewed cautiously since they were driven by a small number of studies or did not overlap with the between-group differences found in the primary analyses. CONCLUSION: The meta-analysis suggested robust cortical thickness reduction in the IFG, insula and STG among adult patients with schizophrenia, particularly in those with chronic schizophrenia. The results provide useful insights to understanding the underlying pathophysiology of 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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.029 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".