Cognitive impairment and C-reactive protein in clinically stable schizophrenia outpatients: a focus on sex differences
Bibliographic record
Abstract
Although previous findings identified an association between C-reactive protein (CRP) levels, and impaired cognitive functions in patients with schizophrenia (SZ), little is currently known about the relationship between inflammation, cognition, and sex in SZ. The current study aimed to explore the association between peripheral inflammation and cognitive impairment in SZ as a function of sex. The sample included 132 clinically stable patients with SZ, of whom 82 were males (62.1%) and 50 females (37.9%). Sociodemographic data were collected, an accurate assessment was performed using the Positive and Negative Syndrome (PANSS), Clinical Assessment Interview for Negative Symptoms (CAINS), and Calgary Depression (CDS) scales, and the MATRICS Consensus Cognitive Battery (MCCB), and CRP levels were tested. A Pearson correlation and multiple regression analyses, including potential confounding factors, were performed. We found an inverse association between CRP levels and performance on visual learning (r = - 0.386, p = 0.006) domain in female patients only, whereas no correlations were found in males. The regression model for women retained age (β = - 0.319, p = 0.017), the CAINS-MAP score (β = - 0.247, p = 0.070), and the CRP (β = - 0.321, p = 0.013) as predictors of visual learning. Our results suggest the possible existence of sex-specific modulation of the association between systemic inflammation and the cognitive features of the illness.
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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".