Serum Level of Brain-Derived Neurotrophic Factor and Thrombotic Type Are Predictive of Cognitive Impairment in the Acute Period of Ischemic Strokes Patients
Bibliographic record
Abstract
40-70% of patients after a stroke, including a mild one, may experience cognitive impairment. Brain-derived neurotrophic factor (BDNF) plays a significant role in the pathogenesis and rehabilitation of ischemic stroke and also affects the patients' recovery prognosis. An association between cognitive impairment in the poststroke period and lower peripheral BDNF levels is known, but the prognostic significance of serum BDNF levels and clinical characteristics for the risk of developing cognitive impairment in the acute period remains uncertain. We conducted a prospective cohort study of patients in the acute phase of ischemic stroke. Clinical examination, assessment of neurological status, neuropsychological testing, and laboratory analyzes were performed on patients at 1 and 14 days after ischemic stroke. The state of cognitive functions was assessed by the Mini-Mental State Examination scale. Quantification of BDNF in blood serum was performed by solid-phaseenzyme-linked immunosorbent assay (ELISA). We found that within 14 days after an acute ischemic stroke, we found a decrease in the clinical severity of patients compared to 1 day of the onset of the disease before the start of treatment and a significant decrease in the level of BDNF in the blood serum of patients with ischemic stroke both on the first and on the 14th day. However, during the 2 weeks of the acute period, no significant changes were detected, despite the general improvement of the clinical condition. In our study, cognitive impairment was found in almost half of the patients on the first day of ischemic stroke, and there was no significant reduction in this prevalence over 2 weeks. We found that a low level of BDNF and a thrombotic subtype of ischemic stroke can be risk factors for cognitive impairment in the acute period, which can be useful in planning treatment and rehabilitation measures.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| 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".