Bibliographic record
Abstract
Cognitive impairments (CIs) are common in poststroke patients. The basis for this condition is frequently a neurodegenerative process and most often Alzheimer's disease (AD). Stroke may promote the manifestation of clinically asymptomatic AD, worsen prestroke cognitive deficit or merely manifest prestroke CIs. The paper discusses the epidemiology, risk factors, and pathogenesis of poststroke CIs, current methods for its diagnosis, as well as symptomatic and pathogenetic treatment. The most informative method for the diagnosis of poststroke CIs is neuropsychological examination that should be made in the early poststroke period (if the patient's consciousness is clear). The most common screening tests include mini-mental state examination (the most sensitive to evaluate cognitive dysfunction in Alzheimer type dementias) and the Montreal cognitive assessment. Magnetic resonance imaging of the brain, positron emission tomography, cerebrospinal fluid examination, and genetic testing are used to reveal AD at its preclinical stages. Preventive measures include regular physical activity, a balanced diet, and sufficient mental workload. The prevention of stroke and other cardiovascular diseases are also important. The major groups of drugs used to treat AD and vascular CIs are acetylcholinesterase inhibitors and N-methyl-D-aspartate receptor antagonists. It is expedient to use glutamatergic and acetylcholinergic therapy earlier in patients with obvious CIs that are unassociated with emotional problems and disturbance of consciousness. Akatinol memantine is a drug that can be regarded not only as a symptomatic but also pathogenetic agent.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".