Functional Outcomes After Treatment of Posterior Inferior Cerebellar Artery Aneurysms
Bibliographic record
Abstract
Objective Aneurysms of the posterior inferior cerebellar artery (PICA) are a rare cause of subarachnoid hemorrhage. Treatment for this type of aneurysm may be microsurgical clipping or endovascular. This decision is based on patient characteristics, aneurysm location and dimensions, along with surgeon and institutional experience. In this study we aim to assess the outcomes of surgical and endovascular treatment of PICA aneurysms. Methods We retrospectively reviewed the charts of 52 patients who were admitted to Vancouver General Hospital for ruptured or symptomatic PICA aneurysms between 2005 and 2015. Modified Rankin scores were assigned at the time of discharge and at two subsequent follow-up time points. The mean short-term follow-up period post-operatively was 11.1 months and the mean long-term follow-up period was 19.3 months. Clinical and radiological characteristics were collected for all patients. Results Of the 52 patients, two died prior to obtaining treatment. Of the 50 patients who were treated for their PICA aneurysm, 39 presented with subarachnoid hemorrhage while 11 had symptomatic unruptured PICA aneurysms. Overall, 11 patients had endovascular treatment (coil embolization) while 39 patients underwent microsurgical clipping/trapping of the aneurysm. At the time of hospital discharge, patients in the microsurgical group trended towards a better the modified Rankin Scale score (2.3) compared to the endovascular group, though this did not reach significance (3.0) (p=0.20). The long-term score in the endovascular group (1.6) was also comparable to the microsurgical group (1.9) (p=0.55). Conclusion While the early outcomes in patients treated endovascularly appear better, there is no statistically significant difference in outcomes between the microsurgical and endovascular treatment groups at short- and long-term follow-up.
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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 | 0.000 |
| 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 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".