A preliminary study on the changes of cerebral hemodynamic in patients with carotid artery stenosis combined cognitive impairment after stent implantation
Bibliographic record
Abstract
Objective To explore the changes of cerebral hemodynamic in patients with carotid artery stenosis(CAS) combined cognitive impairment(CI) after stent implantation, and the relationship between CI improvement and cognitive function improvement. Methods Twenty-six patients with CAS combined CI in the first District of Department of Neurology in Central Hospital of Jiangmen from January 2012 to June 2013 were selected, all of which underwent carotid stent implantation. Montreal Cognitive Assessment(MoCA) and mini-mental state examination(MMSE) were used to evaluate patients' cognitive function at preoperative and postoperative, respectively, while64-slice spiral CT was used to do Computed Tomography Perfusion(CTP). CHD indicators, such as relative cerebral blood vessels flow(rCBF), relative cerebral blood volume(rCBV) and relative time to peak(rTTP) at supply and non-supply area in narrow vessels, were recorded. Results MoCA and MMSE score were(15.3±3.9) and(21.0±3.4),respectively, before the operation, which were(20.6±3.4) and(25.2±3.0), respectively, 3 months after operation. In patients, there were statistically significant differences in MoCA and MMSE score before and after surgery(P0.05).The rCBF, rCBV and rTTP at narrow vessels area were(0.98±0.15),(0.98±0.15) and(1.05±0.11), respectively, before the operation, while which were(0.96±0.11),(0.97±0.14) and(1.00±0.06), respectively, 3 months after operation. There were statistically significant differences in rCBF and rTTP between before and after surgery(P0.05).Conclusion Stent implantation surgery could significantly improve CHD in patients with CAS combined CI, which could also improve cognitive function in patient
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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 | 0.001 |
| 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".