Higher soluble TREM-1 levels are associated with cognitive impairment after acute ischemic stroke
Bibliographic record
Abstract
Background and purpose Triggering receptor expressed on myeloid cells-1 (TREM-1) was reported to be critical for mediating the neurological function after stroke, while the impact of soluble TREM-1 (sTREM-1) on cognitive impairment after ischemic stroke is unclear. We aimed to explore the association between sTREM-1 and post-stroke cognitive impairment (PSCI). Methods We prospectively recruited consecutive ischemic stroke patients who admitted hospital within 7 days of onset. Serum sTREM-1 concentrations were measured after admission. Cognitive function was assessed at 90 days follow-up using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). PSCI was defined as a MMSE score of <27 or a MoCA score < 26. Results A total of 291 patients (mean age, 66.6 years; 46.0% female) were enrolled for this study. Among these participants, the median sTREM-1 concentrations were 289.4 pg/mL. According to the MoCA score, 153 (52.6%) patients experienced PSCI at 3 months. After adjustment for confounding risk factors by multivariate regression analysis, patients with sTREM-1 levels in the fourth quartile were more likely to have increased risk 3-month PSCI (as compared with the first quartile, odds ratio 12.22, 95% confidence intervals, 5.20–28.71, P = 0.001). Restricted cubic spline further confirmed a dose-dependent relationship between sTREM-1 levels and PSCI (P = 0.003 for linearity). Similar significant findings were observed when the cognitive impairment was diagnosed according to the MMSE criterion. Conclusion Our study revealed that higher serum sTREM-1 levels at admission were associated with increased risk of 3-month PSCI.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".