Disease Outcome, Alexithymia and Depression are Differently Associated with Serum IL-18 Levels in Acute Stroke
Bibliographic record
Abstract
Stroke has been shown to lead to depressive disorders, anxiety disorders and other emotional consequences. Although the cause of these disorders is a subject of debate, stroke has clearly been shown to lead to the production of pro-inflammatory cytokines, which we hypothesized to play a role in the production of post-stroke emotional disorders. Thus we investigated here whether acute stroke might be associated with changes in the normal serum levels of IL-18 and if these changes were related to stroke severity, as well as to the presence and severity of alexithymia and depression. Thirty patients with a first-ever symptomatic ischemic stroke were included. Alexithymia (Toronto Alexithymia Scale; TAS-20), depression (Hamilton Depression Rating Scale; HDRS-17) and serum IL-18 were assessed. Stroke patients showed serum levels of IL-18 significantly related to stroke severity. Furthermore, a strong positive correlation was observed between IL-18 levels and severity of alexithymia, particularly among patients with right-hemisphere lesions. Specifically, circulating concentrations of IL-18 were significantly increased in patients with categorical alexithymia (TAS-20 score 61), as compared with both non alexithymic patients and control subjects. In addition, stroke was more severe in alexithymic patients, as compared to non alexithymic patients. Following multivariate regression, serum IL-18 levels appeared to be specifically associated with alexithymia rather than with stroke severity in patients with right-hemisphere lesions only. These results suggest that IL-18 might be specifically implicated in the pathogenesis of post-stroke alexithymia, ultimately contributing to impaired recovery from stroke.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".