Effects of Intracranial Interventional Embolization and Intracranial Clipping on the Cognitive and Neurologic Function of Patients with Intracranial Aneurysms
Bibliographic record
Abstract
BACKGROUND: Intracranial interventional embolization and intracranial clipping have been two typical therapies for the emergent rescue of intracranial aneurysm. However, there are still controversies over the impact of these two surgical treatments of aneurysms on cognitive and neurological functions of patients. METHODS: A total of 144 patients with intracranial aneurysms were enrolled as the test subjects, who were randomly and evenly divided into the Intracranial Clipping group and the Interventional Embolization group. Cognitive and neurologic functions were evaluated by Glasgow Outcome Scale, Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE) scales, National Institutes of Health Stroke Scale (NIHSS) and Activities of Daily Living (ADL) scale. Enzyme-linked immunosorbent assay was used to analyze the serum levels of neuron-specific enolase (NSE) and S100β. RESULTS: There were no significant differences in the preoperative MMSE, MoCA, NIHSS or ADL scale between two groups (p > 0.05). However, after operation, the MMSE and MoCA scores of the interventional embolization group were significantly higher, whereas the NIHSS and ADL scales were significantly lower than those of the intracranial clipping group (p < 0.05). The levels of NSE and S100β in the intracranial clipping group were significantly higher than in the interventional embolization group. CONCLUSION: Intracranial interventional embolization exerts better effects on the cognitive and neurologic functions than intracranial clipping.
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) | 0.000 | 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".