Inflammatory markers of symptomatic remission at 6 months in patients with first-episode schizophrenia
Bibliographic record
Abstract
Neuroinflammation contributes to the pathophysiology of various mental illnesses including schizophrenia. We investigated peripheral inflammatory cytokines as a biomarker for predicting symptomatic remission in patients with first-episode schizophrenia. The study included 224 patients aged 15-60 years who fulfilled the criteria for schizophrenia spectrum disorder with a treatment duration ≤6 months. Serum levels of tumor necrosis factor (TNF) -α, interferon-γ, interleukin (IL)-1α, IL-1β, IL-6, IL-8, IL-10, and IL-12 were measured. Psychotic symptoms, depressive symptoms, and general functioning were assessed using the Positive and Negative Syndrome Scale, Beck Depression Inventory (BDI), Calgary Depression Scale for Schizophrenia, and Personal and Social Performance scale, respectively. Duration of untreated psychosis (DUP) was also recorded. We investigated the factors associated with remission for each sex in logistic regression analysis. In total, 174 patients achieved remission at the 6-month follow-up (females, 83.5%; males, 70.9%). Remission was associated with older age and lower BDI scores in male patients and with lower TNF-α levels and shorter DUP in female patients. Our findings suggest that peripheral inflammatory cytokines may impede early symptomatic remission in female patients with schizophrenia. In addition, depressive symptoms in males and long DUP in females may be poor prognostic factors for early remission in patients with first-episode psychosis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".