Microvascular dysfunction in schizophrenia: a case–control study
Bibliographic record
Abstract
BACKGROUND: Schizophrenia is a mental illness associated with cardiovascular disease at a younger age than in the general population. Endothelial dysfunction has predictive value for future cardiovascular events; however, the impact of a diagnosis of schizophrenia on this marker is unknown. AIMS: We tested the hypothesis that subjects with schizophrenia have impaired endothelial function. METHODS: A total of 102 subjects (34.5±7.5 years) participated in this study. This sample consisted of 51 subjects with a diagnosis of schizophrenia and 51 healthy subjects, who were matched for age (P=0.442), sex (P>0.999), and smoking status (P=0.842). Peripheral artery microvascular and conduit vessel endothelial function was measured using hyperemic velocity time integral (VTI), pulse arterial tonometry (PAT), and flow-mediated dilation (FMD). RESULTS: Significantly lower values of VTI were noted in subjects with schizophrenia (104.9±33.0 vs. 129.1±33.8 cm, P<0.001), whereas FMD (P=0.933) and PAT (P=0.862) did not differ between the two groups. A multivariable-linear-regression analysis, built on data from univariate and partial correlations, showed that only schizophrenia, sex, lipid-lowering medications, antihypertensive medications, and low-density lipoprotein (LDL)-cholesterol were predictive of attenuated VTI, whereas age, ethnicity, family history of cardiovascular disease, smoking status, systolic blood pressure, waist circumference, HDL-cholesterol, triglycerides, C-reactive protein, and homeostatic model assessment-insulin resistance (HOMA-IR), antidiabetic medications, antidepressant medications, mood stabilizers, benzodiazepines, and anticholinergic medications did not predict VTI in this model (adjusted R (2)=0.248). CONCLUSIONS: Our findings suggest that a diagnosis of schizophrenia is associated with impaired microvascular function as indicated by lower values of VTI, irrespective of many other clinical characteristics. It might be an early indicator of cardiovascular risk in schizophrenia, and might help to identify high-risk individuals.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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) | 0.003 | 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".