Does establishing a neurovascular unit improve the outcome after surgical clipping for aneurysmal subarachnoid hemorrhage? Results from a 5-year observational study in Kuwait
Bibliographic record
Abstract
Background: Failure to prevent rebleeding after cerebral subarachnoid hemorrhage (SAH) is the most frequent reason for high morbidity and mortality of aneurysmal SAH. Our study aims to identify the outcome after surgical clipping of aneurysmal SAH before and after the establishment of the neurovascular unit. The clarifications of the positive turnover in the outcome will be discussed. Methods: A retrospective cohort analysis was carried out on our experience with a controlled group of patients who underwent clipping for ruptured cerebral aneurysms ( n = 61) from January 2015 to December 2019. A modified Rankin scale (mRS) was used to determine the outcome after 6 months of follow-up. Results: The median mRS score (i.e., outcome) on admission was 4, whereas it was with a median score of 2 six months after clipping ( P ≤ 0.001). Overall, the cases with a good outcome were 63.9% of the sample, while the poor outcome conditions were 36.1%. The most cases with an improved outcome were after introducing the neurovascular unit, representing a transition of aneurysmal clipping practice in our center. The good outcome was changed from 42% to 76.7%, and the poor outcome was changed from 58% to 23.3% ( P = 0.019). The crude mortality rate was similar to the rate worldwide (18%), with a noticeable decrease after organizing a neurovascular subspecialty. Conclusion: The outcome after clipping of ruptured SAH can be largely affected by the surgeon’s experience and postoperative intensive care. Organizing a neurovascular team is one of the major factors to achieve good outcomes.
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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 | 0.001 |
| 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 | 0.001 |
| 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".