Associations Among Suicidal Ideation, White Matter Integrity and Cognitive Deficit in First-Episode Schizophrenia
Bibliographic record
Abstract
Objective: The study was aimed to investigate the possible associations among suicidal ideation, brain white matter (WM) integrity and cognitive deficit in first-episode schizophrenia (FES) using diffusion tensor imaging. Methods: The sample contained 18 FES patients with suicidal ideation (SI+), 45 FES patients without suicidal ideation (SI-) and 44 healthy controls. The Calgary Depression Scale for Schizophrenia was used to measure the suicidal ideation and depression symptoms. The whole brain WM integrity and three domains of cognitive function: working memory, verbal comprehension as well as processing speed were compared between the three groups. Results: Compared with SI-, SI+ showed preserved WM integrity as indicated by significantly higher factional anisotropy (FA) or lower mean diffusivity (MD) in multiple WM tracts, and higher FA coupled with lower MD in bilateral posterior corona radiata. Compared with SI-, SI+ were more depressed and had less cognitive deficit in working memory and verbal comprehension. The fiber tracts in bilateral posterior corona radiata connect to the precuneus as shown by probabilistic tractography, and their WM integrity disruptions were found to be positively associated with the cognitive deficits in the FES patients. Discussion: Preserved WM integrity may be a risk factor for suicidal ideation in FES patients. One possible explanation is that it contributes to preserved cognitive function, especially in working memory and verbal comprehension, which may be associated with greater insight and could lead to increased depression and suicidal ideation. The posterior corona radiata and the precuneus may be linked to the related biological processes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".