Serum Sphingosine 1-Phosphate as a Biomarker for Post-Stroke Cognitive Impairment
Bibliographic record
Abstract
Background: Stroke is a main cause of disability. Impaired cognition is an important aspect for stroke survivors. The discovery of laboratory biomarkers for post stroke cognitive impairment (PSCI) may help identification of those who are at risk of cognitive impairment and application of suitable therapeutic regimens.Objective: This study aimed to measure S1P serum levels in a group of patients with severe ischemic stroke at admission and to determine if they are associated with post stroke cognitive state.Patients and Methods: The study has been applied on sixty patients who had acute ischemic stroke in addition to 40 apparently healthy. The mean of age and gender in subjects and controls were matched. Serum sphingosine -1 phosphate (S1P) levels were analyzed by ELISA technique for all patients within 72 hours of admission and for healthy controls. The severity of the stroke has been evaluated based on the scale of the National Institute of Health Stroke (NIHSS). Patients also underwent cognitive assessment using Montreal Cognitive Assessment (MoCA) at admission and after 3 months.Results: The level of serum S1P was apparently reduced in acute stroke patients by comparing with the healthy controls (p < 0.001). Furthermore, the decreased levels of the S1P serum were obviously with more disease severity as measured by high NIHSS score at admission and with more post stroke cognitive impairment as assessed by MoCA scale three months later after stroke onset.Conclusions: The study came up with key findings that reported a clear step-down in the levels of serum S1P in the patients with acute stroke as compared to the healthy control and the same obvious reduction in S1P levels in cognitive impairment patients as compared to those with non-cognitive impairment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".