Effects of butylphthalide injection on cerebral blood flow perfusion and cognitive function in patients with acute cerebral infarction accompanied by cognitive disorder
Bibliographic record
Abstract
Objective To investigate the effects of butylphthalide injection on cerebral blood flow (CBF) perfusion and cognitive function in patients with acute cerebral infarction accompanied by cognitive disorder. Methods From September 2016 to September 2017, 80 patients with acute cerebral infarction and cognitive impairment were admitted to the Department of Neurology, Yan’an Hospital of Kunming Medical University. They were assigned to an observation group (n=40) and a control group (n=40). The control group received conventional treatment while the observation group received butylphthalide injection in addition to conventional treatment. The treatment lasted for 14 days for both groups. Before and after treatment, dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI) was used to measure the CBF parameters in the cerebral ischemic region, and Montreal Cognitive Assessment (MoCA) was used to evaluate the changes in cognitive function. Results After treatment, rCBF and rCBV increased significantly and rMTT and rTTP decreased significantly in the observation group (P<0.05). After treatment, there were significant improvements in MoCA subscores and total score in the observation group (P<0.05). In the observation group, the post-treatment increases in rCBV and rCBF were positively correlated with increased MoCA total score (r=0.474, P=0.013; r=0.282, P=0.027), and the post-treatment decreases in rMTT and rTTP were negatively correlated with increased MoCA total score (r=-0.294, P=0.021; r=-0.382, P=0.019). Conclusion Butylphthalide injection can safely improve CBF perfusion in the focal region and cognitive function in patients with acute cerebral infarction, with no obvious adverse reactions. Key words: Butylphthalide; Cerebral infarction; Acute stage; Cognitive dysfunction; Cerebral blood flow perfusion
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 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".