Association between post-stroke cognitive impairment and gut microbiota in patients with ischemic stroke
Bibliographic record
Abstract
More than half of stroke survivors have post-stroke cognitive impairment (PSCI). The role of gut microbiota, which can communicate with the brain through the gut-brain axis and affect inflammation, has been receiving increased attention. This cross-sectional study aimed to investigate the association of PSCI, gut microbiota, and inflammatory markers. Patients with first ischemic stroke and complete 3-month and 1-year follow-up data were included and divided into PSCI and non-PSCI groups according to the Montreal Cognitive Assessment (MoCA) score at the above time points. PSCI was defined as having a MoCA less than 23 at either 3 months or 1 year, or a decrease of more than 2 points at both time points. Gut microbiota was assessed by 16 S rRNA gene sequencing and Next Generation Sequencing analysis. The inflammatory markers included interleukins (ILs), eotaxin, G-CSF, TNF-α, IFNγ, sCD40L, and MCP-1. There were 95 ischemic stroke patients (mean age, 60.5 ± 12.1 years; male, 68.4%), including 30 with PSCI and 65 with non-PSCI. In gut microbiota analysis, the PSCI group had a higher abundance of Bacteroidaceae and Clostridiaceae, and the non-PSCI group had a higher abundance of Prevotellaceae, Ruminococcaceae, Oscillibacter, and Faecalibacterium. Ruminococcaceae family under the Oscillospirales order remains significantly different in the two groups in logistic regression model adjusting confounding variables (p = 0.044). In an analysis of inflammatory markers, the plasma levels of eotaxin (p = 0.041) and IL-12p40 (p = 0.031) were significantly higher in the PSCI group than those in the non-PSCI group, and the plasma level of eotaxin was significantly positively correlated with the amount of Clostridiaceae (rho = 0.389, p = 0.045). The study found that PSCI was associated with certain gut microbiota, and these gut microbiotas correlated with the pro-inflammatory marker eotaxin. This suggests that gut microbiota might play a role in the development of cognitive impairment after ischemic stroke.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".