SU84. Neurometabolite Levels in Antipsychotic Naive/Free Patients With Schizophrenia: A Meta-Analysis of 1H-MRS Studies
Bibliographic record
Abstract
Background: Studies using proton magnetic resonance spectroscopy (1H-MRS) have reported altered neurometabolite levels in patients with schizophrenia. However, results are inconsistent and confounded by the influence of antipsychotic (AP) administration. Thus, the aim of the present study was to examine neurometabolite levels in AP-naive/free patients with schizophrenia through a meta-analysis. Methods: A literature search was conducted using Embase, Medline, and PsycINFO to identify studies that compared neurometabolite levels in AP-naive/free patients with schizophrenia to healthy controls (last search: August 2016). Eight neurometabolites (glutamate, glutamine, glutamate + glutamine, N-acetylaspartate [NAA], choline, creatine, myo-inositol, and γ-aminobutyric acid) and 7 regions of interest (ROI; medial prefrontal cortex, dorsolateral prefrontal cortex, frontal white matter, occipital lobe, basal ganglia, hippocampus/medial temporal lobe, and thalamus) were examined. Standardized mean differences (SMDs) were calculated to assess neurometabolite-level differences between groups. Results: Twenty-two studies (N = 1142) were included in the analysis. The results showed lower thalamic NAA levels in the patient group (SMD = −0.56, P = .0005). No differences were identified for other neurometabolites. Conclusion: This study extends previously reported findings demonstrating a decrease of NAA levels in patients with chronic schizophrenia. On the other hand, previously reported alterations of glutamatergic neurometabolite levels were not replicated. Further studies are required to detect the influence of AP on these neurometabolites levels.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.034 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 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".