Cognitive outcomes after unruptured intracranial aneurysm treatment with endovascular coiling
Bibliographic record
Abstract
BACKGROUND: We aimed to determine the effects of endovascular coiling of unruptured intracranial aneurysms (UIAs) on cognition to inform treatment decisions. We present the first study using the Montreal Cognitive Assessment (MoCA) to determine neurocognitive changes after endovascular coiling. METHODS: We prospectively collected data on all patients with UIAs undergoing endovascular coiling, primary or assisted. Patients completed the MoCA prior to intervention and 1 month and 6 months' post-procedure. A repeated measures linear mixed effects model was used to compare pre-procedure and post-procedure cognition. RESULTS: Thirty-three patients with 33 aneurysms who underwent coiling from April 2017 to May 2020 were included (mean age 55.5, 81.8% female). All procedures used general anesthesia. There was no difference between baseline and post-procedure MoCA scores at any time interval (P>0.05). Mean MoCA scores at baseline, 1 month post-procedure, and 6 months' post-procedure were 25.4, 26.8, and 26.3 respectively. There was also no difference between pre- and post-procedure scores on any individual MoCA domain (visuospatial, naming, memory, attention, language, abstraction, delayed recall, and orientation) at any time interval (P>0.05). Seventeen patients had follow-up MRI or CT imaging, of which 11.8% showed radiographic changes or ischemia. 77.8% of patients with 6-month angiographic follow-up achieved class I, and 22.2% achieved class II Raymond-Roy Occlusion. Thirty-two out of 33 patients had follow-up mRS ≤2. CONCLUSION: Our study suggests that endovascular coiling does not diminish neurocognitive function. Patients with UIAs in our cohort also had baseline MoCA scores below the cut-off for mild cognitive impairment despite pre-procedure mRS and NIHSS of 0.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 teacher head, 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".