The relationship between the development of post-stroke cognitive impairment and changes in the coagulation component of hemostasis
Bibliographic record
Abstract
Objective. To evaluate the relationship between the severity of post-stroke cognitive impairment (PSCI) and coagulation parameters assessed using the dynamic thrombophotometry. Material and methods. Thirty-five patients with hemispheric ischemic stroke (IS) with moderate neurological deficit at admission were included. All patients underwent a comprehensive clinical and instrumental assessment according to the current guidelines. On days 10—14, the cognitive status of patients was assessed using the Montreal Cognitive Assessment (MoCA). Coagulation parameters were assessed using the dynamic thrombophotometry at admission, on 6—8th days and 13—15th days from the onset of the disease. A database of laboratory studies of 30 apparently healthy volunteers was used as a comparison group. Results. Data analysis revealed that a number of spatial and temporal parameters were within the reference values, and there were no significant changes over time. Nevertheless, though the optical density of the fibrin clot (D) was within the reference values, it showed a steady increase from the admission by the end of the 1st week of the disease (p=0.007) and by 13—15th days (p=0.009). Correlation and multivariate linear regression, including baseline stroke symptom severity, showed significant associations (p<0.01 in all tests) between the higher optical density of the fibrin clot (D) on days 6—8 and 13—15 and lower MoCA score, confirming the negative effect of altered hemostatic parameters on cognitive function in IS patients. Conclusion. The increase of optical density of the fibrin clot (D) by 6—8th and 13—15th days is a potential prognostic biomarker for the early development of 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 | 0.001 | 0.003 |
| 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 | 0.000 |
| 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".