Serum Periostin and Cognitive Impairment in Ischemic Stroke Patients: a Prospective Cohort Study
Bibliographic record
Abstract
Abstract Background. Recent evidence suggest elevated periostin is associated with cardiovascular diseases. The aim of this study was to investigate the relationship between serum periostin and post-stroke cognitive impairment (PSCI) at 3 months. Methods. In this prospective cohort study, we enrolled patients with ischemic stroke and hospitalized within 7 days of symptoms onset from January 2019 to January 2020. Serum periostin levels were measured using enzyme-linked immunosorbent assay after admission. Cognitive function assessment was performed at 3-month follow-up visit using the Montreal Cognitive Assessment (MoCA). We defined the PSCI as total MoCA score < 25. Results. A total of 315 ischemic stroke patients were enrolled for the study. PSCI was observed in 173 patients, which accounted for 54.9% (95% confidence interval [CI] 52.1%–57.7%) of the cohort. Serum periostin levels were higher in patients with PSCI than in those without PSCI (median 19.6 vs 14.8 ng/mL; P = 0.001). In logistic regression analysis, the highest quartile of periostin levels were significantly correlated to PSCI (odds ratio [OR], 9.69; 95% CI, 5.06–25.61; P = 0.001), as compared with the lowest quartile. This association remained significant after adjustment for age, gender, educational years, stroke severity, and vascular risk factors. Subgroup analyses further confirmed these results. Furthermore, restricted cubic spline regression demonstrated a linear association between periostin levels and PSCI ( P = 0.001 for linearity). Conclusions. This study found that higher serum periostin levels are associated with an increased risk of PSCI at 3 months after ischemic stroke onset.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| 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".