Risk factors for metabolic syndrome in individuals with recent-onset psychosis at disease onset and after 1-year follow-up
Bibliographic record
Abstract
Metabolic syndrome (MetS) is a cluster of parameters encompassing the most dangerous heart attack risk factors, associated with increased morbidity and mortality. It is highly prevalent in recent-onset psychosis (ROP) patients. In this pilot study, we evaluated MetS parameters (fasting glucose, high-density lipoprotein (HDL) cholesterol (HDL-c), fasting triglycerides, waist circumference, and systolic and diastolic blood pressure), clinical symptoms, pharmacological treatment, lifestyle, and inflammatory markers in 69 patients with ROP and 61 healthy controls (HCs). At baseline, waist circumference (p = 0.005) and fasting triglycerides (p = 0.007) were higher in patients with ROP than in HCs. At the 1-year follow-up, patients showed clinical improvement, with a reduction in the positive and negative syndrome scale (PANSS) score (p < 0.001), dietary intake (p = 0.001), and antipsychotic medication dose (p < 0.001); however, fasting glucose (p = 0.011), HDL-c (p = 0.013) and waist circumference worsened (p < 0.001). We identified sex, age, BMI, dietary intake, physical activity, daily tobacco use, daily cannabis use, and antipsychotic doses as risk factors contributing to baseline MetS parameters. After 1-year follow-up, those factors plus the PANSS and Calgary Depression Scale for Schizophrenia (CDSS) scores were associated with MetS parameters. Further studies are needed to understand the contributions of the studied risk factors in patients with ROP at onset and during disease progression.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".