Cognitive Impairments and Risk Factors After Ruptured Anterior Communicating Artery Aneurysm Treatment in Low-Grade Patients Without Severe Complications: A Multicenter Retrospective Study
Bibliographic record
Abstract
Background: Cognitive impairment is the main factor affecting quality of life in patients with low-grade aneurysmal subarachnoid hemorrhage. Objective: We explored cognitive impairments and risk factors after treatment for ruptured anterior communicating artery (AComA) aneurysms in low-grade (Hunt-Hess grade of 1–3) patients without severe complications. Methods: One-hundred-twenty-six patients with a Hunt-Hess grade of 1–3 who underwent microsurgical clipping or endovascular embolization for ruptured AComA aneurysm treatment at three academic institutions in China from January 2015 to December 2017 were assessed with the modified Telephone Interview for Cognitive Status (TICS-m), the modified Rankin Scale (mRS), and the instrumental activities of daily living (IADL) scale 2 or more years after microsurgical clipping or endovascular coiling. Multiple cox-regression analysis was used to identify variables independently associated with cognitive impairment. Results: Of the total of 126 patients, 115 (91.3%) achieved good clinical outcomes (mRS score 0–2) and 109 (86.5%) had excellent quality of life (IADL score 8). Twenty-eight (22.2%) patients showed cognitive impairments (TICS-m≤27). The multivariate COX regression analysis showed that the female patients and longer duration of loss of consciousness at onset of subarachnoid hemorrhage (SAH) were independently associated with cognitive impairment. Cognitive outcome at the latest follow-up was not significantly different between patients treated after surgical clipping and coiling. Conclusion: About one in five patients showed cognitive impairments after treatment for ruptured AComA aneurysms. Patients who are of the female sex, and who have a longer duration of a loss of consciousness at the onset of SAH may be at risk of cognitive impairment.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".