Bifidobacterium bifidum supplementation improves ischemic stroke outcomes in elderly patients: A retrospective study
Bibliographic record
Abstract
This retrospective study aimed to explore the therapeutic potential of Bifidobacterium bifidum supplementation on elderly ischemic stroke patients. We retrospectively analyzed electronic medical records from 153 elderly ischemic stroke patients. Patients were stratified into 2 groups: those receiving B bifidum supplementation (Intervention group, n = 73) and those receiving standard treatment without any additional supplementation (Control group, n = 80). Outcomes were assessed using the National Institutes of Health Stroke Scale (NIHSS), Montreal Cognitive Assessment (MoCA), Self-Rating Depression Scale (SDS), and Self-Rating Anxiety Scale (SAS). Inflammatory markers, immunological indicators, neurotrophic factor, and gut-brain axis (GBA)-related markers were also evaluated at baseline and during 4-week follow-up. Compared to the control group, the intervention group exhibited significant improvements in the NIHSS, MoCA, SDS and SAS scores (P < .001). Enhanced levels of brain-derived neurotrophic factor (BDNF) and reduced levels of NPY were observed in the intervention group. Additionally, inflammatory markers, including IL-6, IL-8, IL-1β, and TNF-α, were significantly reduced in the intervention group, as well as significant increases in immunoglobulin levels (Ig A, Ig G, and Ig M) (P < .001). Besides, lower incidences of diarrhea and constipation were observed in the intervention group (P < .001), while the incidence of abdominal pain was no significant changed. B bifidum supplementation offers promising therapeutic benefits in improving neurological, cognitive, and psychological outcomes in elderly ischemic stroke patients, which may be achieved by regulating the GBA, reducing inflammation and promoting immune function. These findings highlight the importance of integrating gut health strategies in stroke management.
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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) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".