The relationship between cognitive impairment and cerebral blood flow changes after transient ischaemic attack
Bibliographic record
Abstract
OBJECTIVE: The associations between cognitive impairment following the initial onset of transient ischaemic attack (TIA) and the parameters of altered cerebral blood flow and high-sensitivity C-reactive protein (HsCRP) level are unclear. METHODS: A total of 97 first-time TIA patients aged 69.94 ± 4.02 years (38-75 years; M:F, 50:47) hospitalized between March 2010 and July 2011 were compared to 100 healthy control patients aged 66.56 ± 12.15 years (45-80 years; M:F, 60:40). Cognitive function was quantified by Montreal Cognitive Assessment (MoCA). Intracranial blood flow was measured using transcranial Doppler ultrasound, and HsCRP levels were assessed using the Spearman correlation coefficient. Relationships between both values and MoCA scores were examined. RESULTS: Transient ischaemic attack patients exhibited declined cognitive function manifested as impaired verbal fluency (97.93%), memory recall (91.75%), abstraction (84.53%), and visuospatial/executive abilities (79.38%). To a lesser degree, TIA patients also evidenced abnormalities in attention (50.52%), naming (20.62%), and orientation (20.62%). Furthermore, MoCA scores significantly correlated with high HsCRP levels and low vascular systolic peak velocities (P<0.001). Vascular systolic peak velocities were high in nine patients (9.23%) and low in 57 patients (58.76%). Thus, cognitive impairment was closely related to HsCRP levels and intracranial blood flow velocities. CONCLUSION: Post-TIA cognitive impairment may result from atherosclerosis and reduced blood flow to the brain. Cognitive impairment, transcranial Doppler-visualized changes, and elevated HsCRP levels are important diagnostic indicators of TIA. Markers provided by cognitive evaluation of TIA patients following the initial onset of TIA may allow clinicians to better predict and prevent adverse vascular events.
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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 | 0.002 |
| 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) | 0.001 | 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".