Cognitive and cerebral perfusion outcomes following interventional revascularization in individuals with chronic middle cerebral artery occlusion
Bibliographic record
Abstract
Background: Chronic occlusion of the middle cerebral artery (MCAO) is frequently underdiagnosed due to mild or insidious clinical manifestations. Despite this, individuals with chronic MCAO are at an increased risk of cerebral infarction and progressive cognitive impairment. This study aimed to assess the efficacy of interventional revascularization therapy in comparison to standard medical treatment, with a focus on neurological and cognitive outcomes. Methods: Fifty-five patients diagnosed with chronic MCAO were allocated to either a medication group or an interventional surgery group. Neurological status and cerebral perfusion parameters, including cerebral blood flow (CBF), time-to-maximum (Tmax), mean transit time (MTT), and cerebral blood volume (CBV) were assessed. Cognitive performance was assessed using the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). Post-treatment and follow-up data were collected and analyzed. Results: Among the 29 participants in the interventional surgery group, successful recanalization was achieved in 26 cases, while three procedures were unsuccessful. Improvements in neurological deficits were observed in both groups. However, significant enhancements in cerebral perfusion parameters (CBF, Tmax, and MTT) and cognitive scores (MoCA and MMSE) were identified only in the interventional group. No statistically significant changes in cerebral perfusion or cognitive performance were observed in the medical therapy group. Conclusion: Interventional revascularization therapy was associated with improved cerebral perfusion and enhanced cognitive outcomes compared to medical management in individuals with chronic MCAO.
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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 | 0.001 | 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 | 0.000 |
| 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".